What Factors Predict Who Will Have a Strong Social Network Following a Stroke?

ERIC Educational Resources Information Center

Northcott, Sarah; Marshall, Jane; Hilari, Katerina

2016-01-01

Purpose: Measures of social networks assess the number and nature of a person's social contacts, and strongly predict health outcomes. We explored how social networks change following a stroke and analyzed concurrent and baseline predictors of social networks 6 months poststroke. Method: We conducted a prospective longitudinal observational study.…

Social network approaches to recruitment, HIV prevention, medical care, and medication adherence.

PubMed

Latkin, Carl A; Davey-Rothwell, Melissa A; Knowlton, Amy R; Alexander, Kamila A; Williams, Chyvette T; Boodram, Basmattee

2013-06-01

This article reviews the current issues and advancements in social network approaches to HIV prevention and care. Social network analysis can provide a method to understand health disparities in HIV rates, treatment access, and outcomes. Social network analysis is a valuable tool to link social structural factors to individual behaviors. Social networks provide an avenue for low-cost and sustainable HIV prevention interventions that can be adapted and translated into diverse populations. Social networks can be utilized as a viable approach to recruitment for HIV testing and counseling, HIV prevention interventions, optimizing HIV medical care, and medication adherence. Social network interventions may be face-to-face or through social media. Key issues in designing social network interventions are contamination due to social diffusion, network stability, density, and the choice and training of network members. There are also ethical issues involved in the development and implementation of social network interventions. Social network analyses can also be used to understand HIV transmission dynamics.

Use of social networking for dental hygiene program recruitment.

PubMed

Ennis, Rachel S

2011-01-01

Social networking has become a popular and effective means of communication used by students in the millennial generation. Academic admissions officers are beginning to utilize social networking methods for recruitment of students. However, the dental hygiene literature has reported little information about the use of social networking for recruitment strategies. This paper describes one institutions' process of creating and implementing a social network site for prospective and current students.

Incorporating profile information in community detection for online social networks

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2014-07-01

Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

Organizational Application of Social Networking Information Technologies

ERIC Educational Resources Information Center

Reppert, Jeffrey R.

2012-01-01

The focus of this qualitative research study using the Delphi method is to provide a framework for leaders to develop their own social networks. By exploring concerns in four areas, leaders may be able to better plan, implement, and manage social networking systems in organizations. The areas addressed are: (a) social networking using…

The challenge of social networking in the field of environment and health

PubMed Central

2012-01-01

Background The fields of environment and health are both interdisciplinary and trans-disciplinary, and until recently had little engagement in social networking designed to cross disciplinary boundaries. The EU FP6 project HENVINET aimed to establish integrated social network and networking facilities for multiple stakeholders in environment and health. The underlying assumption is that increased social networking across disciplines and sectors will enhance the quality of both problem knowledge and problem solving, by facilitating interactions. Inter- and trans-disciplinary networks are considered useful for this purpose. This does not mean that such networks are easily organized, as openness to such cooperation and exchange is often difficult to ascertain. Methods Different methods may enhance network building. Using a mixed method approach, a diversity of actions were used in order to investigate the main research question: which kind of social networking activities and structures can best support the objective of enhanced inter- and trans-disciplinary cooperation and exchange in the fields of environment and health. HENVINET applied interviews, a role playing session, a personal response system, a stakeholder workshop and a social networking portal as part of the process of building an interdisciplinary and trans-disciplinary network. Results The interviews provided support for the specification of requirements for an interdisciplinary and trans-disciplinary network. The role playing session, the personal response system and the stakeholder workshop were assessed as useful tools in forming such network, by increasing the awareness by different disciplines of other’s positions. The social networking portal was particularly useful in delivering knowledge, but the role of the scientist in social networking is not yet clear. Conclusions The main challenge in the field of environment and health is not so much a lack of scientific problem knowledge, but rather the ability to effectively communicate, share and use available knowledge for policy making. Structured social network facilities can be useful by policy makers to engage with the research community. It is beneficial for scientists to be able to integrate the perspective of policy makers in the research agenda, and to assist in co-production of policy-relevant information. A diversity of methods need to be applied for network building: according to the fit-for-purpose-principle. It is useful to know which combination of methods and in which time frame produces the best results. Networking projects such as HENVINET are created not only for the benefit of the network itself, but also because the applying of the different methods is a learning tool for future network building. Finally, it is clear that the importance of specialized professionals in enabling effective communication between different groups should not be underestimated. PMID:22759497

Enhancing to method for extracting Social network by the relation existence

NASA Astrophysics Data System (ADS)

Elfida, Maria; Matyuso Nasution, M. K.; Sitompul, O. S.

2018-01-01

To get the trusty information about the social network extracted from the Web requires a reliable method, but for optimal resultant required the method that can overcome the complexity of information resources. This paper intends to reveal ways to overcome the constraints of social network extraction leading to high complexity by identifying relationships among social actors. By changing the treatment of the procedure used, we obtain the complexity is smaller than the previous procedure. This has also been demonstrated in an experiment by using the denial sample.

Do Social Network Characteristics Predict Mammography Screening Practices?

ERIC Educational Resources Information Center

Allen, Jennifer D.; Stoddard, Anne M.; Sorensen, Glorian

2008-01-01

Background: Many breast cancer outreach programs assume that dissemination of information through social networks and provision of social support will promote screening. The authors prospectively examined the relationship between social network characteristics and adherence to screening guidelines. Method: Employed women age 40 years and older…

Similarity between community structures of different online social networks and its impact on underlying community detection

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2015-03-01

As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

Behavior Based Social Dimensions Extraction for Multi-Label Classification

PubMed Central

Li, Le; Xu, Junyi; Xiao, Weidong; Ge, Bin

2016-01-01

Classification based on social dimensions is commonly used to handle the multi-label classification task in heterogeneous networks. However, traditional methods, which mostly rely on the community detection algorithms to extract the latent social dimensions, produce unsatisfactory performance when community detection algorithms fail. In this paper, we propose a novel behavior based social dimensions extraction method to improve the classification performance in multi-label heterogeneous networks. In our method, nodes’ behavior features, instead of community memberships, are used to extract social dimensions. By introducing Latent Dirichlet Allocation (LDA) to model the network generation process, nodes’ connection behaviors with different communities can be extracted accurately, which are applied as latent social dimensions for classification. Experiments on various public datasets reveal that the proposed method can obtain satisfactory classification results in comparison to other state-of-the-art methods on smaller social dimensions. PMID:27049849

Google matrix analysis of directed networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Link prediction measures considering different neighbors’ effects and application in social networks

NASA Astrophysics Data System (ADS)

Luo, Peng; Wu, Chong; Li, Yongli

Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.

Using Virtual Social Networks for Case Finding in Clinical Studies: An Experiment from Adolescence, Brain, Cognition, and Diabetes Study.

PubMed

Pourabbasi, Ata; Farzami, Jalal; Shirvani, Mahbubeh-Sadat Ebrahimnegad; Shams, Amir Hossein; Larijani, Bagher

2017-01-01

One of the main usages of social networks in clinical studies is facilitating the process of sampling and case finding for scientists. The main focus of this study is on comparing two different methods of sampling through phone calls and using social network, for study purposes. One of the researchers started calling 214 families of children with diabetes during 90 days. After this period, phone calls stopped, and the team started communicating with families through telegram, a virtual social network for 30 days. The number of children who participated in the study was evaluated. Although the telegram method was 60 days shorter than the phone call method, researchers found that the number of participants from telegram (17.6%) did not have any significant differences compared with the ones being phone called (12.9%). Using social networks can be suggested as a beneficial method for local researchers who look for easier sampling methods, winning their samples' trust, following up with the procedure, and an easy-access database.

Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network.

PubMed

De Brún, Aoife; McAuliffe, Eilish

2018-03-13

Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.

PubMed

Fu, Zhaohao; Hao, Lingxin

2018-01-15

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Agent-based modeling of China's rural-urban migration and social network structure

NASA Astrophysics Data System (ADS)

Fu, Zhaohao; Hao, Lingxin

2018-01-01

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

An Algorithm for Critical Nodes Problem in Social Networks Based on Owen Value

PubMed Central

Wang, Xue-Guang

2014-01-01

Discovering critical nodes in social networks has many important applications. For finding out the critical nodes and considering the widespread community structure in social networks, we obtain each node's marginal contribution by Owen value. And then we can give a method for the solution of the critical node problem. We validate the feasibility and effectiveness of our method on two synthetic datasets and six real datasets. At the same time, the result obtained by using our method to analyze the terrorist network is in line with the actual situation. PMID:25006592

The challenge of social networking in the field of environment and health.

PubMed

van den Hazel, Peter; Keune, Hans; Randall, Scott; Yang, Aileen; Ludlow, David; Bartonova, Alena

2012-06-28

The fields of environment and health are both interdisciplinary and trans-disciplinary, and until recently had little engagement in social networking designed to cross disciplinary boundaries. The EU FP6 project HENVINET aimed to establish integrated social network and networking facilities for multiple stakeholders in environment and health. The underlying assumption is that increased social networking across disciplines and sectors will enhance the quality of both problem knowledge and problem solving, by facilitating interactions. Inter- and trans-disciplinary networks are considered useful for this purpose. This does not mean that such networks are easily organized, as openness to such cooperation and exchange is often difficult to ascertain. Different methods may enhance network building. Using a mixed method approach, a diversity of actions were used in order to investigate the main research question: which kind of social networking activities and structures can best support the objective of enhanced inter- and trans-disciplinary cooperation and exchange in the fields of environment and health. HENVINET applied interviews, a role playing session, a personal response system, a stakeholder workshop and a social networking portal as part of the process of building an interdisciplinary and trans-disciplinary network. The interviews provided support for the specification of requirements for an interdisciplinary and trans-disciplinary network. The role playing session, the personal response system and the stakeholder workshop were assessed as useful tools in forming such network, by increasing the awareness by different disciplines of other's positions. The social networking portal was particularly useful in delivering knowledge, but the role of the scientist in social networking is not yet clear. The main challenge in the field of environment and health is not so much a lack of scientific problem knowledge, but rather the ability to effectively communicate, share and use available knowledge for policy making. Structured social network facilities can be useful by policy makers to engage with the research community. It is beneficial for scientists to be able to integrate the perspective of policy makers in the research agenda, and to assist in co-production of policy-relevant information. A diversity of methods need to be applied for network building: according to the fit-for-purpose-principle. It is useful to know which combination of methods and in which time frame produces the best results.Networking projects such as HENVINET are created not only for the benefit of the network itself, but also because the applying of the different methods is a learning tool for future network building. Finally, it is clear that the importance of specialized professionals in enabling effective communication between different groups should not be underestimated.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Mixed-method Exploration of Social Network Links to Participation

PubMed Central

Kreider, Consuelo M.; Bendixen, Roxanna M.; Mann, William C.; Young, Mary Ellen; McCarty, Christopher

2015-01-01

The people who regularly interact with an adolescent form that youth's social network, which may impact participation. We investigated the relationship of social networks to participation using personal network analysis and individual interviews. The sample included 36 youth, age 11 – 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least one measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within social networks. Findings contribute to understanding the ways social networks are linked to youth participation and suggest the potential of social network factors for predicting rehabilitation outcomes. PMID:26594737

Do-it-yourself networks: a novel method of generating weighted networks.

PubMed

Shanafelt, D W; Salau, K R; Baggio, J A

2017-11-01

Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social-ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.

Social Insects: A Model System for Network Dynamics

NASA Astrophysics Data System (ADS)

Charbonneau, Daniel; Blonder, Benjamin; Dornhaus, Anna

Social insect colonies (ants, bees, wasps, and termites) show sophisticated collective problem-solving in the face of variable constraints. Individuals exchange information and materials such as food. The resulting network structure and dynamics can inform us about the mechanisms by which the insects achieve particular collective behaviors and these can be transposed to man-made and social networks. We discuss how network analysis can answer important questions about social insects, such as how effective task allocation or information flow is realized. We put forward the idea that network analysis methods are under-utilized in social insect research, and that they can provide novel ways to view the complexity of collective behavior, particularly if network dynamics are taken into account. To illustrate this, we present an example of network tasks performed by ant workers, linked by instances of workers switching from one task to another. We show how temporal network analysis can propose and test new hypotheses on mechanisms of task allocation, and how adding temporal elements to static networks can drastically change results. We discuss the benefits of using social insects as models for complex systems in general. There are multiple opportunities emergent technologies and analysis methods in facilitating research on social insect network. The potential for interdisciplinary work could significantly advance diverse fields such as behavioral ecology, computer sciences, and engineering.

A Markov chain model for image ranking system in social networks

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Toriu, Takashi; Hama, Hiromitsu

2014-03-01

In today world, different kinds of networks such as social, technological, business and etc. exist. All of the networks are similar in terms of distributions, continuously growing and expanding in large scale. Among them, many social networks such as Facebook, Twitter, Flickr and many others provides a powerful abstraction of the structure and dynamics of diverse kinds of inter personal connection and interaction. Generally, the social network contents are created and consumed by the influences of all different social navigation paths that lead to the contents. Therefore, identifying important and user relevant refined structures such as visual information or communities become major factors in modern decision making world. Moreover, the traditional method of information ranking systems cannot be successful due to their lack of taking into account the properties of navigation paths driven by social connections. In this paper, we propose a novel image ranking system in social networks by using the social data relational graphs from social media platform jointly with visual data to improve the relevance between returned images and user intentions (i.e., social relevance). Specifically, we propose a Markov chain based Social-Visual Ranking algorithm by taking social relevance into account. By using some extensive experiments, we demonstrated the significant and effectiveness of the proposed social-visual ranking method.

Investigation of Social Studies Teachers' Intended Uses of Social Networks in Terms of Various Variables

ERIC Educational Resources Information Center

Akgün, Ismail Hakan

2016-01-01

The aim of this research is to determine Social Studies teacher candidates' intended uses of social networks in terms of various variables. The research was carried out by using screening model of quantitative research methods. In the study, "The Social Network Intended Use Scale" was used as a data collection tool. As a result of the…

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

PubMed Central

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency. PMID:26609303

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

PubMed

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

Social networks and alcohol use among older adults: a comparison with middle-aged adults

PubMed Central

Kim, Seungyoun; Spilman, Samantha L.; Liao, Diana H.; Sacco, Paul; Moore, Alison A.

2017-01-01

Objectives This study compared the association between social networks and alcohol consumption among middle-aged (MA) and older adults (OA) to better understand the nature of the relationship between those two factors among OA and MA. Method We examined Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Current drinkers aged over 50 were subdivided into two age groups: MA (50–64, n = 5214) and OA (65 and older, n = 3070). Each age group was stratified into drinking levels (low-risk vs. at-risk) based on alcohol consumption. The size and diversity of social networks were measured. Logistic regression models were used to examine age differences in the association between the social networks (size and diversity) and the probability of at-risk drinking among two age groups. Results A significant association between the social networks diversity and lower odds of at-risk drinking was found among MA and OA. However, the relationship between the diversity of social networks and the likelihood of at-risk drinking was weaker for OA than for MA. The association between social networks size and at-risk drinking was not significant among MA and OA. Conclusion The current study suggests that the association between social networks diversity and alcohol use among OA differs from the association among MA, and few social networks were associated with alcohol use among OA. In the future, research should consider an in-depth exploration of the nature of social networks and alcohol consumption by using longitudinal designs and advanced methods of exploring drinking networks. PMID:28006983

Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

NASA Astrophysics Data System (ADS)

Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah

2017-03-01

Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

Walk-based measure of balance in signed networks: Detecting lack of balance in social networks

NASA Astrophysics Data System (ADS)

Estrada, Ernesto; Benzi, Michele

2014-10-01

There is a longstanding belief that in social networks with simultaneous friendly and hostile interactions (signed networks) there is a general tendency to a global balance. Balance represents a state of the network with a lack of contentious situations. Here we introduce a method to quantify the degree of balance of any signed (social) network. It accounts for the contribution of all signed cycles in the network and gives, in agreement with empirical evidence, more weight to the shorter cycles than to the longer ones. We found that, contrary to what is generally believed, many signed social networks, in particular very large directed online social networks, are in general very poorly balanced. We also show that unbalanced states can be changed by tuning the weights of the social interactions among the agents in the network.

Identifying influential user communities on the social network

NASA Astrophysics Data System (ADS)

Hu, Weishu; Gong, Zhiguo; Hou U, Leong; Guo, Jingzhi

2015-10-01

Nowadays social network services have been popularly used in electronic commerce systems. Users on the social network can develop different relationships based on their common interests and activities. In order to promote the business, it is interesting to explore hidden relationships among users developed on the social network. Such knowledge can be used to locate target users for different advertisements and to provide effective product recommendations. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a data set from Epinions, which demonstrates that our method achieves 4-11.8% accuracy improvement over the state-of-the-art method.

Increasing Scalability of Researcher Network Extraction from the Web

NASA Astrophysics Data System (ADS)

Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

Social networks, which describe relations among people or organizations as a network, have recently attracted attention. With the help of a social network, we can analyze the structure of a community and thereby promote efficient communications within it. We investigate the problem of extracting a network of researchers from the Web, to assist efficient cooperation among researchers. Our method uses a search engine to get the cooccurences of names of two researchers and calculates the streangth of the relation between them. Then we label the relation by analyzing the Web pages in which these two names cooccur. Research on social network extraction using search engines as ours, is attracting attention in Japan as well as abroad. However, the former approaches issue too many queries to search engines to extract a large-scale network. In this paper, we propose a method to filter superfluous queries and facilitates the extraction of large-scale networks. By this method we are able to extract a network of around 3000-nodes. Our experimental results show that the proposed method reduces the number of queries significantly while preserving the quality of the network as compared to former methods.

The Role of Gender in Adolescents' Social Networks and Alcohol, Tobacco, and Drug Use: A Systematic Review

ERIC Educational Resources Information Center

Jacobs, Wura; Goodson, Patricia; Barry, Adam E.; McLeroy, Kenneth R.

2016-01-01

Background: Despite previous research indicating an adolescents' alcohol, tobacco, and other drug (ATOD) use is dependent upon their sex and the sex composition of their social network, few social network studies consider sex differences and network sex composition as a determinant of adolescents' ATOD use behavior. Methods: This systematic…

[Social Networks of Children with Mentally Ill Parents].

PubMed

Stiawa, Maja; Kilian, Reinhold

2017-10-01

Social Networks of Children with Mentally Ill Parents Mental illness of parents can be a load situation for children. Supporting social relations might be an important source in such a situation. Social relations can be shown by social network analysis. Studies about social networks and mental health indicate differences regarding structure and potential for support when compared with social networks of healthy individuals. If and how mental illness of parents has an impact on their children's network is widely unknown. This systematic review shows methods and results of studies about social networks of children with mentally ill parents. By systematic search in electronic databases as well as manual search, two studies were found who met the target criteria. Both studies were conducted in the USA. Results of studies indicate that parental mental illness affects the state of mental health and social networks of children. Symptomatology of children changed due to perceived social support of network contacts. Impact of social support and strong network contacts seems to depend on age of children and the family situation. That's why support offers should be adapt to children's age. Focusing on social networks as potential resource for support and needs of the family affected seems appropriate during treatment.

Dynamic social community detection and its applications.

PubMed

Nguyen, Nam P; Dinh, Thang N; Shen, Yilin; Thai, My T

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.

Dynamic Social Community Detection and Its Applications

PubMed Central

Nguyen, Nam P.; Dinh, Thang N.; Shen, Yilin; Thai, My T.

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods. PMID:24722164

I Keep my Problems to Myself: Negative Social Network Orientation, Social Resources, and Health-Related Quality of Life in Cancer Survivors

PubMed Central

Symes, Yael; Campo, Rebecca A.; Wu, Lisa M.; Austin, Jane

2016-01-01

Background Cancer survivors treated with hematopoietic stem cell transplant rely on their social network for successful recovery. However, some survivors have negative attitudes about using social resources (negative social network orientation) that are critical for their recovery. Purpose We examined the association between survivors’ social network orientation and health-related quality of life (HRQoL) and whether it was mediated by social resources (network size, perceived support, and negative and positive support-related social exchanges). Methods In a longitudinal study, 255 survivors completed validated measures of social network orientation, HRQoL, and social resources. Hypotheses were tested using path analysis. Results More negative social network orientation predicted worse HRQoL (p < .001). This association was partially mediated by lower perceived support and more negative social exchanges. Conclusions Survivors with negative social network orientation may have poorer HRQoL in part due to deficits in several key social resources. Findings highlight a subgroup at risk for poor transplant outcomes and can guide intervention development. PMID:26693932

Trauma-Exposed Latina Immigrants’ Networks: A Social Network Analysis Approach

PubMed Central

Hurtado-de-Mendoza, Alejandra; Serrano, Adriana; Gonzales, Felisa A.; Fernandez, Nicole C.; Cabling, Mark; Kaltman, Stacey

2015-01-01

Objective Trauma exposure among Latina immigrants is common. Social support networks can buffer the impact of trauma on mental health. This study characterizes the social networks of trauma-exposed Latina immigrants using a social network analysis perspective. Methods In 2011–2012 a convenience sample (n=28) of Latina immigrants with trauma exposure and presumptive depression or posttraumatic stress disorder was recruited from a community clinic in Washington DC. Participants completed a social network assessment and listed up to ten persons in their network (alters). E-Net was used to describe the aggregate structural, interactional, and functional characteristics of networks and Node-XL was used in a case study to diagram one network. Results Most participants listed children (93%), siblings (82%), and friends (71%) as alters, and most alters lived in the US (69%). Perceived emotional support and positive social interaction were higher compared to tangible, language, information, and financial support. A case study illustrates the use of network visualizations to assess the strengths and weaknesses of social networks. Conclusions Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted. PMID:28078194

Investigating Patterns of Interaction in Networked Learning and Computer-Supported Collaborative Learning: A Role for Social Network Analysis

ERIC Educational Resources Information Center

de Laat, Maarten; Lally, Vic; Lipponen, Lasse; Simons, Robert-Jan

2007-01-01

The focus of this study is to explore the advances that Social Network Analysis (SNA) can bring, in combination with other methods, when studying Networked Learning/Computer-Supported Collaborative Learning (NL/CSCL). We present a general overview of how SNA is applied in NL/CSCL research; we then go on to illustrate how this research method can…

Social and spatial processes associated with childhood diarrheal disease in Matlab, Bangladesh.

PubMed

Perez-Heydrich, Carolina; Furgurson, Jill M; Giebultowicz, Sophia; Winston, Jennifer J; Yunus, Mohammad; Streatfield, Peter Kim; Emch, Michael

2013-01-01

We develop novel methods for conceptualizing geographic space and social networks to evaluate their respective and combined contributions to childhood diarrheal incidence. After defining maternal networks according to direct familial linkages between females, and road networks using satellite imagery of the study area, we use a spatial econometrics model to evaluate the significance of correlation terms relating childhood diarrheal incidence to the incidence observed within respective networks. Disease was significantly clustered within road networks across time, but only inconsistently correlated within maternal networks. These methods could be widely applied to systems in which both social and spatial processes jointly influence health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Community Structure in Online Collegiate Social Networks

NASA Astrophysics Data System (ADS)

Traud, Amanda; Kelsic, Eric; Mucha, Peter; Porter, Mason

2009-03-01

Online social networking sites have become increasingly popular with college students. The networks we studied are defined through ``friendships'' indicated by Facebook users from UNC, Oklahoma, Caltech, Georgetown, and Princeton. We apply the tools of network science to study the Facebook networks from these five different universities at a single point in time. We investigate each single-institution network's community structure, which we obtain through partitioning the graph using an eigenvector method. We use both graphical and quantitative tools, including pair-counting methods, which we interpret through statistical analysis and permutation tests to measure the correlations between the network communities and a set of characteristics given by each user (residence, class year, major, and high school). We also analyze the single gender subsets of these networks, and the impact of missing demographical data. Our study allows us to compare the online social networks for the five schools as well as infer differences in offline social interactions. At the schools studied, we were able to define which characteristics of the Facebook users correlate best with friendships.

A systematic review protocol: social network analysis of tobacco use.

PubMed

Maddox, Raglan; Davey, Rachel; Lovett, Ray; van der Sterren, Anke; Corbett, Joan; Cochrane, Tom

2014-08-08

Tobacco use is the single most preventable cause of death in the world. Evidence indicates that behaviours such as tobacco use can influence social networks, and that social network structures can influence behaviours. Social network analysis provides a set of analytic tools to undertake methodical analysis of social networks. We will undertake a systematic review to provide a comprehensive synthesis of the literature regarding social network analysis and tobacco use. The review will answer the following research questions: among participants who use tobacco, does social network structure/position influence tobacco use? Does tobacco use influence peer selection? Does peer selection influence tobacco use? We will follow the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines and search the following databases for relevant articles: CINAHL (Cumulative Index to Nursing and Allied Health Literature); Informit Health Collection; PsycINFO; PubMed/MEDLINE; Scopus/Embase; Web of Science; and the Wiley Online Library. Keywords include tobacco; smoking; smokeless; cigarettes; cigar and 'social network' and reference lists of included articles will be hand searched. Studies will be included that provide descriptions of social network analysis of tobacco use.Qualitative, quantitative and mixed method data that meets the inclusion criteria for the review, including methodological rigour, credibility and quality standards, will be synthesized using narrative synthesis. Results will be presented using outcome statistics that address each of the research questions. This systematic review will provide a timely evidence base on the role of social network analysis of tobacco use, forming a basis for future research, policy and practice in this area. This systematic review will synthesise the evidence, supporting the hypothesis that social network structures can influence tobacco use. This will also include exploring the relationship between social network structure, social network position, peer selection, peer influence and tobacco use across all age groups, and across different demographics. The research will increase our understanding of social networks and their impact on tobacco use, informing policy and practice while highlighting gaps in the literature and areas for further research.

Social Network Positions and Smoking Experimentation among Chinese Adolescents

ERIC Educational Resources Information Center

Fang, Xiaoyi; Li, Xiaoming; Stanton, Bonita; Dong, Qi

2003-01-01

Objective: To explore the relationship between peer social network positions and smoking experimentation among Chinese adolescents. Methods: Self-administered questionnaires were administered to 1040 adolescents in grades 6, 8, and 10. Paired-friendship linkages were used to assign participants into 3 mutually exclusive social network positions.…

Social Network Type and Subjective Well-Being in a National Sample of Older Americans

ERIC Educational Resources Information Center

Litwin, Howard; Shiovitz-Ezra, Sharon

2011-01-01

Purpose: The study considers the social networks of older Americans, a population for whom there have been few studies of social network type. It also examines associations between network types and well-being indicators: loneliness, anxiety, and happiness. Design and Methods: A subsample of persons aged 65 years and older from the first wave of…

Social Network Decay as Potential Recovery from Homelessness: A Mixed Methods Study in Housing First Programming

PubMed Central

Golembiewski, Elizabeth; Watson, Dennis P.; Robison, Lisa; Coberg, John W.

2017-01-01

The positive relationship between social support and mental health has been well documented, but individuals experiencing chronic homelessness face serious disruptions to their social networks. Housing First (HF) programming has been shown to improve health and stability of formerly chronically homeless individuals. However, researchers are only just starting to understand the impact HF has on residents’ individual social integration. The purpose of the current study was to describe and understand changes in social networks of residents living in a HF program. Researchers employed a longitudinal, convergent parallel mixed method design, collecting quantitative social network data through structured interviews (n = 13) and qualitative data through semi-structured interviews (n = 20). Quantitative results demonstrated a reduction in network size over the course of one year. However, increases in both network density and frequency of contact with network members increased. Qualitative interviews demonstrated a strengthening in the quality of relationships with family and housing providers and a shedding of burdensome and abusive relationships. These results suggest network decay is a possible indicator of participants’ recovery process as they discontinued negative relationships and strengthened positive ones. PMID:28890807

Performance of an Abbreviated Version of the Lubben Social Network Scale among Three European Community-Dwelling Older Adult Populations

ERIC Educational Resources Information Center

Lubben, James; Blozik, Eva; Gillmann, Gerhard; Iliffe, Steve; von Renteln-Kruse, Wolfgang; Beck, John C.; Stuck, Andreas E.

2006-01-01

Purpose: There is a need for valid and reliable short scales that can be used to assess social networks and social supports and to screen for social isolation in older persons. Design and Methods: The present study is a cross-national and cross-cultural evaluation of the performance of an abbreviated version of the Lubben Social Network Scale…

Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China

PubMed Central

Li, Jibin; Lau, Joseph T. F.; Mo, Phoenix K. H.; Su, Xuefen; Wu, Anise M. S.; Tang, Jie; Qin, Zuguo

2016-01-01

Background Online social networking use has been integrated into adolescents’ daily life and the intensity of online social networking use may have important consequences on adolescents’ well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. Methods A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Results Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach’s alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, p<0.001). As expected, the SNAIS and its subscale scores were correlated significantly with emotional connection to social networking, social networking addiction, Internet addiction, and characteristics related to social networking use. Conclusions The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population. PMID:27798699

Social networks and alcohol use disorders: findings from a nationally representative sample

PubMed Central

Mowbray, Orion; Quinn, Adam; Cranford, James A.

2014-01-01

Background While some argue that social network ties of individuals with alcohol use disorders (AUD) are robust, there is evidence to suggest that individuals with AUDs have few social network ties, which are a known risk factor for health and wellness. Objectives Social network ties to friends, family, co-workers and communities of individuals are compared among individuals with a past-year diagnosis of alcohol dependence or alcohol abuse to individuals with no lifetime diagnosis of AUD. Method Respondents from Wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC) were assessed for the presence of past-year alcohol dependence or past-year alcohol abuse, social network ties, sociodemographics and clinical characteristics. Results Bivariate analyses showed that both social network size and social network diversity was significantly smaller among individuals with alcohol dependence, compared to individuals with alcohol abuse or no AUD. When social and clinical factors related to AUD status were controlled, multinomial logistic models showed that social network diversity remained a significant predictor of AUD status, while social network size did not differ among AUD groups. Conclusion Social networks of individuals with AUD may be different than individuals with no AUD, but this claim is dependent on specific AUD diagnosis and how social networks are measured. PMID:24405256

Enabling Community Through Social Media

PubMed Central

Haythornthwaite, Caroline

2013-01-01

Background Social network analysis provides a perspective and method for inquiring into the structures that comprise online groups and communities. Traces from interaction via social media provide the opportunity for understanding how a community is formed and maintained online. Objective The paper aims to demonstrate how social network analysis provides a vocabulary and set of techniques for examining interaction patterns via social media. Using the case of the #hcsmca online discussion forum, this paper highlights what has been and can be gained by approaching online community from a social network perspective, as well as providing an inside look at the structure of the #hcsmca community. Methods Social network analysis was used to examine structures in a 1-month sample of Twitter messages with the hashtag #hcsmca (3871 tweets, 486 unique posters), which is the tag associated with the social media–supported group Health Care Social Media Canada. Network connections were considered present if the individual was mentioned, replied to, or had a post retweeted. Results Network analyses revealed patterns of interaction that characterized the community as comprising one component, with a set of core participants prominent in the network due to their connections with others. Analysis showed the social media health content providers were the most influential group based on in-degree centrality. However, there was no preferential attachment among people in the same professional group, indicating that the formation of connections among community members was not constrained by professional status. Conclusions Network analysis and visualizations provide techniques and a vocabulary for understanding online interaction, as well as insights that can help in understanding what, and who, comprises and sustains a network, and whether community emerges from a network of online interactions. PMID:24176835

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

Burstiness and tie activation strategies in time-varying social networks.

PubMed

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-13

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Using Social Network Methods to Study School Leadership

ERIC Educational Resources Information Center

Pitts, Virginia M.; Spillane, James P.

2009-01-01

Social network analysis is increasingly used in the study of policy implementation and school leadership. A key question that remains is that of instrument validity--that is, the question of whether these social network survey instruments measure what they purport to measure. In this paper, we describe our work to examine the validity of the…

How Social Network Position Relates to Knowledge Building in Online Learning Communities

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

Social Network Analysis, Statistical Analysis, Content Analysis and other research methods were used to research online learning communities at Capital Normal University, Beijing. Analysis of the two online courses resulted in the following conclusions: (1) Social networks of the two online courses form typical core-periphery structures; (2)…

Systematic Review of Social Network Analysis in Adolescent Cigarette Smoking Behavior

ERIC Educational Resources Information Center

Seo, Dong-Chul; Huang, Yan

2012-01-01

Background: Social networks are important in adolescent smoking behavior. Previous research indicates that peer context is a major causal factor of adolescent smoking behavior. To date, however, little is known about the influence of peer group structure on adolescent smoking behavior. Methods: Studies that examined adolescent social networks with…

Social networking versus facebook advertising to recruit survey respondents: a quasi-experimental study.

PubMed

Gilligan, Conor; Kypri, Kypros; Bourke, Jesse

2014-09-17

Increasingly, social contact and knowledge of other people's attitudes and behavior are mediated by online social media such as Facebook. The main research to which this recruitment study pertains investigates the influence of parents on adolescent alcohol consumption. Given the pervasiveness of online social media use, Facebook may be an effective means of recruitment and intervention delivery. The objective of the study was to determine the efficacy of study recruitment via social networks versus paid advertising on Facebook. We conducted a quasi-experimental sequential trial with response rate as the outcome, and estimates of cost-effectiveness. The target population was parents of 13-17 year old children attending high schools in the Hunter region of New South Wales, Australia. Recruitment occurred via: method (1) social recruitment using Facebook, email-based, social networks, and media coverage followed by method (2) Facebook advertising. Using a range of online and other social network approaches only: method (1) 74 parents were recruited to complete a survey over eight months, costing AUD58.70 per completed survey. After Facebook advertising: method (2) 204 parents completed the survey over four weeks, costing AUD5.94 per completed survey. Participants were representative of the parents recruited from the region's schools using standard mail and email. Facebook advertising is a cost-effective means of recruiting parents, a group difficult to reach by other methods.

Co-authorship network analysis in health research: method and potential use.

PubMed

Fonseca, Bruna de Paula Fonseca E; Sampaio, Ricardo Barros; Fonseca, Marcus Vinicius de Araújo; Zicker, Fabio

2016-04-30

Scientific collaboration networks are a hallmark of contemporary academic research. Researchers are no longer independent players, but members of teams that bring together complementary skills and multidisciplinary approaches around common goals. Social network analysis and co-authorship networks are increasingly used as powerful tools to assess collaboration trends and to identify leading scientists and organizations. The analysis reveals the social structure of the networks by identifying actors and their connections. This article reviews the method and potential applications of co-authorship network analysis in health. The basic steps for conducting co-authorship studies in health research are described and common network metrics are presented. The application of the method is exemplified by an overview of the global research network for Chikungunya virus vaccines.

Topological relationships between brain and social networks.

PubMed

Sakata, Shuzo; Yamamori, Tetsuo

2007-01-01

Brains are complex networks. Previously, we revealed that specific connected structures are either significantly abundant or rare in cortical networks. However, it remains unknown whether systems from other disciplines have similar architectures to brains. By applying network-theoretical methods, here we show topological similarities between brain and social networks. We found that the statistical relevance of specific tied structures differs between social "friendship" and "disliking" networks, suggesting relation-type-specific topology of social networks. Surprisingly, overrepresented connected structures in brain networks are more similar to those in the friendship networks than to those in other networks. We found that balanced and imbalanced reciprocal connections between nodes are significantly abundant and rare, respectively, whereas these results are unpredictable by simply counting mutual connections. We interpret these results as evidence of positive selection of balanced mutuality between nodes. These results also imply the existence of underlying common principles behind the organization of brain and social networks.

Identification of influential users by neighbors in online social networks

NASA Astrophysics Data System (ADS)

Sheikhahmadi, Amir; Nematbakhsh, Mohammad Ali; Zareie, Ahmad

2017-11-01

Identification and ranking of influential users in social networks for the sake of news spreading and advertising has recently become an attractive field of research. Given the large number of users in social networks and also the various relations that exist among them, providing an effective method to identify influential users has been gradually considered as an essential factor. In most of the already-provided methods, those users who are located in an appropriate structural position of the network are regarded as influential users. These methods do not usually pay attention to the interactions among users, and also consider those relations as being binary in nature. This paper, therefore, proposes a new method to identify influential users in a social network by considering those interactions that exist among the users. Since users tend to act within the frame of communities, the network is initially divided into different communities. Then the amount of interaction among users is used as a parameter to set the weight of relations existing within the network. Afterward, by determining the neighbors' role for each user, a two-level method is proposed for both detecting users' influence and also ranking them. Simulation and experimental results on twitter data shows that those users who are selected by the proposed method, comparing to other existing ones, are distributed in a more appropriate distance. Moreover, the proposed method outperforms the other ones in terms of both the influential speed and capacity of the users it selects.

Social Network Analysis: A New Methodology for Counseling Research.

ERIC Educational Resources Information Center

Koehly, Laura M.; Shivy, Victoria A.

1998-01-01

Social network analysis (SNA) uses indices of relatedness among individuals to produce representations of social structures and positions inherent in dyads or groups. SNA methods provide quantitative representations of ongoing transactional patterns in a given social environment. Methodological issues, applications and resources are discussed…

The feasibility of measuring social networks among older adults in assisted living and dementia special care units.

PubMed

Abbott, Katherine M; Bettger, Janet Prvu; Hampton, Keith N; Kohler, Hans-Peter

2015-03-01

Studies indicate that social integration has a significant influence on physical and mental health. Older adults experience an increased risk of social isolation as their social networks decline with fewer traditional opportunities to add new social relationships. Deaths of similar aged friends, cognitive and functional impairments, and relocating to a nursing home (NH) or assisted-living (AL) facility contribute to difficulties in maintaining one's social network. Due to the paucity of research examining the social networks of people residing in AL and NH, this study was designed to develop and test the feasibility of using a combination of methodological approaches to capture social network data among older adults living in AL and a dementia special care unit NH. Social network analysis of both egocentric and sociocentric networks was conducted to visualize the social networks of 15 residents of an AL neighborhood and 12 residents of a dementia special care unit NH and to calculate measures network size, centrality, and reciprocity. The combined egocentric and sociocentric method was feasible and provided a robust indicator of resident social networks highlighting individuals who were socially integrated as well as isolated. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Social Networks of Lesbian, Gay, Bisexual, and Transgender Older Adults

PubMed Central

Erosheva, Elena A.; Kim, Hyun-Jun; Emlet, Charles; Fredriksen-Goldsen, Karen I.

2015-01-01

Purpose This study examines global social networks—including friendship, support, and acquaintance networks—of lesbian, gay, bisexual, and transgender (LGBT) older adults. Design and Methods Utilizing data from a large community-based study, we employ multiple regression analyses to examine correlates of social network size and diversity. Results Controlling for background characteristics, network size was positively associated with being female, transgender identity, employment, higher income, having a partner or a child, identity disclosure to a neighbor, engagement in religious activities, and service use. Controlling in addition for network size, network diversity was positively associated with younger age, being female, transgender identity, identity disclosure to a friend, religious activity, and service use. Implications According to social capital theory, social networks provide a vehicle for social resources that can be beneficial for successful aging and well-being. This study is a first step at understanding the correlates of social network size and diversity among LGBT older adults. PMID:25882129

Social Networking Versus Facebook Advertising to Recruit Survey Respondents: A Quasi-Experimental Study

PubMed Central

Kypri, Kypros; Bourke, Jesse

2014-01-01

Background Increasingly, social contact and knowledge of other people’s attitudes and behavior are mediated by online social media such as Facebook. The main research to which this recruitment study pertains investigates the influence of parents on adolescent alcohol consumption. Given the pervasiveness of online social media use, Facebook may be an effective means of recruitment and intervention delivery. Objective The objective of the study was to determine the efficacy of study recruitment via social networks versus paid advertising on Facebook. Methods We conducted a quasi-experimental sequential trial with response rate as the outcome, and estimates of cost-effectiveness. The target population was parents of 13-17 year old children attending high schools in the Hunter region of New South Wales, Australia. Recruitment occurred via: method (1) social recruitment using Facebook, email-based, social networks, and media coverage followed by method (2) Facebook advertising. Results Using a range of online and other social network approaches only: method (1) 74 parents were recruited to complete a survey over eight months, costing AUD58.70 per completed survey. After Facebook advertising: method (2) 204 parents completed the survey over four weeks, costing AUD5.94 per completed survey. Participants were representative of the parents recruited from the region’s schools using standard mail and email. Conclusions Facebook advertising is a cost-effective means of recruiting parents, a group difficult to reach by other methods. PMID:25230740

Social Network Analysis Reveals the Negative Effects of Attention-Deficit/Hyperactivity Disorder (ADHD) Symptoms on Friend-Based Student Networks

PubMed Central

Kim, Jun Won; Kim, Bung-Nyun; Kim, Johanna Inhyang; Lee, Young Sik; Min, Kyung Joon; Kim, Hyun-Jin; Lee, Jaewon

2015-01-01

Introduction Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students. Methods A total of 562 sixth-graders from two elementary schools (300 males) provided the names of their best friends (maximum 10 names). Their teachers rated each student’s ADHD symptoms using an ADHD rating scale. Results The results showed that 10.2% of the students were at high risk for ADHD. Significant group differences were observed between the high-risk students and other students in two of the three network parameters (degree, centrality and closeness) used to assess friendship quality, with the high-risk group showing significantly lower values of degree and closeness compared to the other students. Moreover, negative correlations were found between the ADHD rating and two social network analysis parameters. Conclusion Our findings suggest that the severity of ADHD symptoms is strongly correlated with the quality of social and interpersonal relationships in students with ADHD symptoms. PMID:26562777

Analyzing big data in social media: Text and network analyses of an eating disorder forum.

PubMed

Moessner, Markus; Feldhege, Johannes; Wolf, Markus; Bauer, Stephanie

2018-05-10

Social media plays an important role in everyday life of young people. Numerous studies claim negative effects of social media and media in general on eating disorder risk factors. Despite the availability of big data, only few studies have exploited the possibilities so far in the field of eating disorders. Methods for data extraction, computerized content analysis, and network analysis will be introduced. Strategies and methods will be exemplified for an ad-hoc dataset of 4,247 posts and 34,118 comments by 3,029 users of the proed forum on Reddit. Text analysis with latent Dirichlet allocation identified nine topics related to social support and eating disorder specific content. Social network analysis describes the overall communication patterns, and could identify community structures and most influential users. A linear network autocorrelation model was applied to estimate associations in language among network neighbors. The supplement contains R code for data extraction and analyses. This paper provides an introduction to investigating social media data, and will hopefully stimulate big data social media research in eating disorders. When applied in real-time, the methods presented in this manuscript could contribute to improving the safety of ED-related online communication. © 2018 Wiley Periodicals, Inc.

Using social-network research to improve outcomes in natural resource management.

PubMed

Groce, Julie E; Farrelly, Megan A; Jorgensen, Bradley S; Cook, Carly N

2018-05-08

The conservation and management of natural resources operates within social-ecological systems, in which resource users are embedded in social and environmental contexts that influence their management decisions. Characterizing social networks of resource users has received growing interest as an approach for understanding social influences on decision-making, and social network analysis (SNA) has emerged as a useful technique to explore these relationships. In this review, we synthesize how SNA has been used in studies of natural resource management. To present our findings, we developed a theory of change which outlines the influence between social networks and social processes (e.g., interactions between individuals), which in turn influence social outcomes (e.g., decisions or actions) that impact environmental outcomes (e.g., improved condition). Our review of 85 studies demonstrate frequent use of descriptive methods to characterize social processes, yet few studies considered social outcomes or examined network structure relative to environmental outcomes. Only 4 studies assessed network interventions intended to impact relevant processes or outcomes. The heterogeneity in case studies, methods, and analyses preclude general lessons. Thus, we offer a typology of appropriate measures for each stage of our theory of change, to structure and progress our learning about the role of social networks in achieving environmental outcomes. In addition, we suggest shifts in research foci towards intervention studies, to aid in understanding causality and inform the design of conservation initiatives. We also identify the need for developing clearer justification and guidance around the proliferation of network measures. The use of SNA in natural resource management is expanding rapidly, thus now is the ideal time for the conservation community to build a more rigorous evidence base to demonstrate the extent to which social networks can play a role in achieving desired social and environmental outcomes. This article is protected by copyright. All rights reserved.

Improving Family Forest Knowledge Transfer through Social Network Analysis

ERIC Educational Resources Information Center

Gorczyca, Erika L.; Lyons, Patrick W.; Leahy, Jessica E.; Johnson, Teresa R.; Straub, Crista L.

2012-01-01

To better engage Maine's family forest landowners our study used social network analysis: a computational social science method for identifying stakeholders, evaluating models of engagement, and targeting areas for enhanced partnerships. Interviews with researchers associated with a research center were conducted to identify how social network…

Social networking and young adults' drinking practices: innovative qualitative methods for health behavior research.

PubMed

Lyons, Antonia C; Goodwin, Ian; McCreanor, Tim; Griffin, Christine

2015-04-01

Understandings of health behaviors can be enriched by using innovative qualitative research designs. We illustrate this with a project that used multiple qualitative methods to explore the confluence of young adults' drinking behaviors and social networking practices in Aotearoa, New Zealand. Participants were 18-25 year old males and females from diverse ethnic, class, and occupational backgrounds. In Stage 1, 34 friendship focus group discussions were video-recorded with 141 young adults who talked about their drinking and social networking practices. In Stage 2, 23 individual interviews were conducted using screen-capture software and video to record participants showing and discussing their Facebook pages. In Stage 3, a database of Web-based material regarding drinking and alcohol was developed and analyzed. In friendship group data, young adults co-constructed accounts of drinking practices and networking about drinking via Facebook as intensely social and pleasurable. However, this pleasure was less prominent in individual interviews, where there was greater explication of unpleasant or problematic experiences and practices. The pleasure derived from drinking and social networking practices was also differentiated by ethnicity, gender, and social class. Juxtaposing the Web-based data with participants' talk about their drinking and social media use showed the deep penetration of online alcohol marketing into young people's social worlds. Multiple qualitative methods, generating multimodal datasets, allowed valuable nuanced insights into young adults' drinking practices and social networking behaviors. This knowledge can usefully inform health policy, health promotion strategies, and targeted health interventions. (c) 2015 APA, all rights reserved).

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Actor and partner effects of perceived HIV stigma on social network components among people living with HIV/AIDS and their caregivers

PubMed Central

Hao, Chun; Liu, Hongjie

2014-01-01

Background Few studies have investigated the relationship between HIV stigma and social network components at the dyadic level. The objective of this study was to examine the actor and partner effects of perceived HIV stigma by people living with HIV/AIDS (PLWHAs) and their caregivers on social network variables at the dyadic level. Method An egocentric social network study was conducted among 147 dyads consisting of one PLWHA and one caregiver (294 participants) in Nanning, China. The actor-partner interdependence model (APIM) was used to analyze the relationships between perceived HIV stigma and social network components (network relations, network structures, and network functions) at the dyadic level. Results We found in this dyadic analysis that: (1) social network components were similar between PLWHAs and their caregivers; (2) HIV stigma perceived by PLWHAs influenced their own social network components, whereas this influence did not exist between caregivers' perceived HIV stigma and their own social network components; (3) a few significant partner effects were observed between HIV stigma and social network components among both PLWHAs and caregivers. Conclusion The interrelationships between HIV stigma and social network components were complex at the dyadic level. Future interventions programs targeting HIV stigma should focus on the interpersonal relationship at the dyadic level, beyond the intrapersonal factors. PMID:25085478

Social networks of patients with psychosis: a systematic review.

PubMed

Palumbo, Claudia; Volpe, Umberto; Matanov, Aleksandra; Priebe, Stefan; Giacco, Domenico

2015-10-12

Social networks are important for mental health outcomes as they can mobilise resources and help individuals to cope with social stressors. Individuals with psychosis may have specific difficulties in establishing and maintaining social relationships which impacts on their well-being and quality of life. There has been a growing interest in developing social network interventions for patients with psychotic disorders. A systematic literature review was conducted to investigate the size of social networks of patients with psychotic disorders, as well as their friendship networks. A systematic electronic search was carried out in MEDLINE, EMBASE and PsychINFO databases using a combination of search terms relating to 'social network', 'friendship' and 'psychotic disorder'. The search identified 23 relevant papers. Out of them, 20 reported patient social network size. Four papers reported the mean number of friends in addition to whole network size, while three further papers focused exclusively on the number of friends. Findings varied substantially across the studies, with a weighted mean size of 11.7 individuals for whole social networks and 3.4 individuals for friendship networks. On average, 43.1 % of the whole social network was composed of family members, while friends accounted for 26.5 %. Studies assessing whole social network size and friendship networks of people with psychosis are difficult to compare as different concepts and methods of assessment were applied. The extent of the overlap between different social roles assessed in the networks was not always clear. Greater conceptual and methodological clarity is needed in order to help the development of effective strategies to increase social resources of patients with psychosis.

Social contagion theory: examining dynamic social networks and human behavior

PubMed Central

Christakis, Nicholas A.; Fowler, James H.

2013-01-01

Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ‘three degrees of influence’ property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. PMID:22711416

Digital Social Network Mining for Topic Discovery

NASA Astrophysics Data System (ADS)

Moradianzadeh, Pooya; Mohi, Maryam; Sadighi Moshkenani, Mohsen

Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. This paper mainly focused on discovering the topic of exchanging information in digital social network. In brief, our method is to use a hierarchical dictionary of related topics and words that mapped to a graph. Then, with comparing the extracted keywords from the context of social network with graph nodes, probability of relation between context and desired topics will be computed. This model can be used in many applications such as advertising, viral marketing and high-risk group detection.

Social Network, Social Support, and Risk of Incident Stroke: The Atherosclerosis Risk in Communities Study

PubMed Central

Nagayoshi, Mako; Everson-Rose, Susan A.; Iso, Hiroyasu; Mosley, Thomas H.; Rose, Kathryn M.; Lutsey, Pamela L.

2014-01-01

Background and Purpose Having a small social network and lack of social support have been associated with incident coronary heart disease, however epidemiologic evidence for incident stroke is limited. We assessed the longitudinal association of a small social network and lack of social support with risk of incident stroke, and evaluated whether the association was partly mediated by vital exhaustion and inflammation. Methods The Atherosclerosis Risk in Communities (ARIC) Study measured social network and social support in 13,686 men and women (mean, 57±5.7 years, 56% female, 24% black; 76% white) without a history of stroke. Social network was assessed by the 10-item Lubben Social Network Scale, and social support by a 16-item Interpersonal Support Evaluation List-Short Form (ISEL-SF). Results Over a median follow-up of 18.6-years, 905 incident strokes occurred. Relative to participants with a large social network, those with a small social network had a higher risk of stroke [HR (95% CI): 1.44 (1.02–2.04)] after adjustment for demographics, socioeconomic variables and marital status, behavioral risk factors and major stroke risk factors. Vital exhaustion, but not inflammation, partly mediated the association between a small social network and incident stroke. Social support was unrelated to incident stroke. Conclusions In this sample of US community-dwelling men and women, having a small social network was associated with excess risk of incident stroke. As with other cardiovascular conditions, having a small social network may be associated with a modestly increased risk of incident stroke. PMID:25139878

Access, engagement, networks, and norms: Dimensions of social capital at work in a first grade classroom

NASA Astrophysics Data System (ADS)

Wexler-Robock, Stephanie

Social capital refers to access and use of resources available through one's networks to solve problems, and the norms that reflect inclusive or exclusive access to those networks and resources. Research has found positive relationships between social capital, academic achievement, and attainment. Studies, however, have generally examined social capital through factors that occur outside the classroom; students who have social capital, acquired through their family and community relationships, seem to be more successful academically. Limited research has explored what if any factors within the classroom might impact the production, and nature of social capital, or its workings in a classroom. The purpose of this study was to explore the workings and nature of classroom social capital, including its possible relationships to engagement and cognition among 5 student participants. Using methods of qualitative data collection, mixed methods were used to analyze information resources, participants' networking, student work, and classroom discourse. Eight interdependent networking factors and 3 overarching patterns of norms were discovered. The networking factors reflected the structure, content, processes, purposes, and acceptability of participants' networking. The norms, also working interdependently, appeared to promote or inhibit among other things, engagement in networking, help seeking, access, sharing, and intertextual use of diverse, often complex sources of information. Through interaction of the 8 factors and 3 overarching norms, ongoing outcomes of networking appeared to include the creation of bridging (inclusive) and bonding (exclusive) forms of social capital, and depth of scientific conceptual understanding, in this case, about birds. Bridging social capital appeared related to willingness to engage in strong and weak tie networking, help seeking, intertextuality, and possibly to mastery goal orientation for all participants, regardless of reading level. Expository sources more so than narrative texts generated intertextually dense, social and cognitive networks, often between members with weak ties. Together the networking factors and norms shed light on the way discourse, resources, and practice might impact social capital, suggesting that forms of social capital may be produced, accumulated, and depleted by factors and norms that are open to variation and occur within the classroom.

Impacts of Social Network on Therapeutic Community Participation: A Follow-up Survey of Data Gathered after Ya’an Earthquake

PubMed Central

LI, Zhichao; CHEN, Yao; SUO, Liming

2015-01-01

Abstract Background In recent years, natural disasters and the accompanying health risks have become more frequent, and rehabilitation work has become an important part of government performance. On one hand, social networks play an important role in participants’ therapeutic community participation and physical & mental recovery. On the other hand, therapeutic communities with widespread participation can also contribute to community recovery after disaster. Methods This paper described a field study in an earthquake-stricken area of Ya’an. A set of 3-stage follow-up data was obtained concerning with the villagers’ participation in therapeutic community, social network status, demographic background, and other factors. The Hierarchical linear Model (HLM) method was used to investigate the determinants of social network on therapeutic community participation. Results First, social networks have significantly impacts on the annual changes of therapeutic community participation. Second, there were obvious differences in education between groups mobilized by the self-organization and local government. However, they all exerted the mobilization force through the acquaintance networks. Third, local cadre networks of villagers could negatively influence the activities of self-organized therapeutic community, while with positively influence in government-organized therapeutic activities. Conclusion This paper suggests that relevant government departments need to focus more on the reconstruction and cultivation of villagers’ social network and social capital in the process of post-disaster recovery. These findings contribute to better understandings of how social networks influence therapeutic community participation, and what role local government can play in post-disaster recovery and public health improvement after natural disasters. PMID:26060778

Considerations for Public Health Organizations Attempting to Implement a Social Media Presence: A Qualitative Study

PubMed Central

2016-01-01

Background In the past decade, social media has become an integral part of our everyday lives, but research on how this tool is used by public health workers and organizations is still developing. Budget cuts and staff reduction in county departments have required employees to take on more responsibilities. These reductions have caused a reduction in the time for training or collaborating with others in the field. To make up for the loss, many employees are seeking collaboration through social media sites but are unable to do so because state departments block these Internet sites. Objective This study sought to highlight the key considerations and decision-making process for a public health organization deciding whether to implement a social media presence for their organization. Methods Using 3 structured interviews, 15 stakeholders were questioned on their personal experience with social media, experience within the context of public health, and their thoughts on implementation for their center. Interviews were coded using constant comparative qualitative methods. Results The following themes emerged from the interviews: (1) personal experience with technology and social networking sites, (2) use of social networking sites in public health, (3) use of social networking sites in work environments, (4) social networking sites access, (5) ways the Rural South Public Health Training Center could use social networking sites, and (6) perceived outcomes of social networking site usage for the Rural South Public Health Training Center (positive and negative). Conclusions The collective voice of the center showed a positive perceived perception of social media implementation, with the benefits outweighing the risks. Despite the benefits, there is a cautious skepticism of the importance of social networking site use. PMID:27227160

Assessing Social Networks in Patients with Psychotic Disorders: A Systematic Review of Instruments

PubMed Central

Priebe, Stefan

2015-01-01

Background Evidence suggests that social networks of patients with psychotic disorders influence symptoms, quality of life and treatment outcomes. It is therefore important to assess social networks for which appropriate and preferably established instruments should be used. Aims To identify instruments assessing social networks in studies of patients with psychotic disorders and explore their properties. Method A systematic search of electronic databases was conducted to identify studies that used a measure of social networks in patients with psychotic disorders. Results Eight instruments were identified, all of which had been developed before 1991. They have been used in 65 studies (total N of patients = 8,522). They assess one or more aspects of social networks such as their size, structure, dimensionality and quality. Most instruments have various shortcomings, including questionable inter-rater and test-retest reliability. Conclusions The assessment of social networks in patients with psychotic disorders is characterized by a variety of approaches which may reflect the complexity of the construct. Further research on social networks in patients with psychotic disorders would benefit from advanced and more precise instruments using comparable definitions of and timescales for social networks across studies. PMID:26709513

Social Network Types and Mental Health Among LGBT Older Adults

PubMed Central

Kim, Hyun-Jun; Fredriksen-Goldsen, Karen I.; Bryan, Amanda E. B.; Muraco, Anna

2017-01-01

Purpose of the Study: This study was designed to identify social network types among lesbian, gay, bisexual, and transgender (LGBT) older adults and examine the relationship between social network type and mental health. Design and Methods: We analyzed the 2014 survey data of LGBT adults aged 50 and older (N = 2,450) from Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Latent profile analyses were conducted to identify clusters of social network ties based on 11 indicators. Multiple regression analysis was performed to examine the association between social network types and mental health. Results: We found five social network types. Ordered from greatest to least access to family, friend, and other non-family network ties, they were diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. The friend-centered/restricted (33%) and diverse/no children network types (31%) were the most prevalent. Among individuals with the friend-centered/restricted type, access to social networks was limited to friends, and across both types children were not present. The least prevalent type was the fully restricted network type (6%). Social network type was significantly associated with mental health, after controlling for background characteristics and total social network size; those with the fully restricted type showed the poorest mental health. Implications: Unique social network types (diverse/no children and friend-centered/restricted) emerge among LGBT older adults. Moreover, individuals with fully restricted social networks are at particular risk due to heightened health needs and limited social resources. This study highlights the importance of understanding heterogeneous social relations and developing tailored interventions to promote social connectedness and mental health in LGBT older adults. PMID:28087798

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

PubMed Central

Wu, Jun; Su, Zhou; Li, Jianhua

2017-01-01

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

PubMed

Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

2017-07-30

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Use and Views on Social Networking Sites of Pharmacy Students in the United Kingdom

PubMed Central

Hanna, Lezley-Anne; Huey, Gwyneth

2013-01-01

Objective. To investigate students' use and views on social networking sites and assess differences in attitudes between genders and years in the program. Methods. All pharmacy undergraduate students were invited via e-mail to complete an electronic questionnaire consisting of 21 questions relating to social networking. Results. Most (91.8%) of the 377 respondents reported using social networking Web sites, with 98.6% using Facebook and 33.7% using Twitter. Female students were more likely than male students to agree that they had been made sufficiently aware of the professional behavior expected of them when using social networking sites (76.6% vs 58.1% p=0.002) and to agree that students should have the same professional standards whether on placement or using social networking sites (76.3% vs 61.6%; p<0.001). Conclusions. A high level of social networking use and potentially inappropriate attitudes towards professionalism were found among pharmacy students. Further training may be useful to ensure pharmacy students are aware of how to apply codes of conduct when using social networking sites. PMID:23459621

Use and views on social networking sites of pharmacy students in the United kingdom.

PubMed

Hall, Maurice; Hanna, Lezley-Anne; Huey, Gwyneth

2013-02-12

Objective. To investigate students' use and views on social networking sites and assess differences in attitudes between genders and years in the program.Methods. All pharmacy undergraduate students were invited via e-mail to complete an electronic questionnaire consisting of 21 questions relating to social networking.Results. Most (91.8%) of the 377 respondents reported using social networking Web sites, with 98.6% using Facebook and 33.7% using Twitter. Female students were more likely than male students to agree that they had been made sufficiently aware of the professional behavior expected of them when using social networking sites (76.6% vs 58.1% p=0.002) and to agree that students should have the same professional standards whether on placement or using social networking sites (76.3% vs 61.6%; p<0.001).Conclusions. A high level of social networking use and potentially inappropriate attitudes towards professionalism were found among pharmacy students. Further training may be useful to ensure pharmacy students are aware of how to apply codes of conduct when using social networking sites.

Emotion shapes the diffusion of moralized content in social networks

PubMed Central

Wills, Julian A.; Jost, John T.; Tucker, Joshua A.; Van Bavel, Jay J.

2017-01-01

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks. PMID:28652356

Emotion shapes the diffusion of moralized content in social networks.

PubMed

Brady, William J; Wills, Julian A; Jost, John T; Tucker, Joshua A; Van Bavel, Jay J

2017-07-11

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call "moral contagion." Using a large sample of social media communications about three polarizing moral/political issues ( n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

Measuring, Understanding, and Responding to Covert Social Networks: Passive and Active Tomography

DTIC Science & Technology

2017-11-29

Methods for generating a random sample of networks with desired properties are important tools for the analysis of social , biological, and information...on Theoretical Foundations for Statistical Network Analysis at the Isaac Newton Institute for Mathematical Sciences at Cambridge U. (organized by...Approach SOCIAL SCIENCES STATISTICS EECS Problems span three disciplines Scientific focus is needed at the interfaces

To Post, or Not to Post, That Is the Question: Teachers Candidates' Social Networking Decisions and Professional Development Needs

ERIC Educational Resources Information Center

Crompton, Helen; Rippard, Kelly; Sommerfeldt, Jody

2016-01-01

This rise in the use of social networks presents new ethical, legal, and professional challenges for educators. Pre-service teachers need professional development to be cognizant of the content they are posting to personal social networks. The purpose of this mixed-methods study was to develop professional development guidelines to help…

Exploration of the integration of care for persons with a traumatic brain injury using social network analysis methodology

PubMed Central

Lamontagne, Marie-Eve

2013-01-01

Introduction Integration is a popular strategy to increase the quality of care within systems of care. However, there is no common language, approach or tool allowing for a valid description, comparison and evaluation of integrated care. Social network analysis could be a viable methodology to provide an objective picture of integrated networks. Goal of the article To illustrate social network analysis use in the context of systems of care for traumatic brain injury. Method We surveyed members of a network using a validated questionnaire to determine the links between them. We determined the density, centrality, multiplexity, and quality of the links reported. Results The network was described as moderately dense (0.6), the most prevalent link was knowledge, and four organisation members of a consortium were central to the network. Social network analysis allowed us to create a graphic representation of the network. Conclusion Social network analysis is a useful methodology to objectively characterise integrated networks. PMID:24250281

Structure and inference in annotated networks

PubMed Central

Newman, M. E. J.; Clauset, Aaron

2016-01-01

For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network. Here we demonstrate how this ‘metadata' can be used to improve our understanding of network structure. We focus in particular on the problem of community detection in networks and develop a mathematically principled approach that combines a network and its metadata to detect communities more accurately than can be done with either alone. Crucially, the method does not assume that the metadata are correlated with the communities we are trying to find. Instead, the method learns whether a correlation exists and correctly uses or ignores the metadata depending on whether they contain useful information. We demonstrate our method on synthetic networks with known structure and on real-world networks, large and small, drawn from social, biological and technological domains. PMID:27306566

Structure and inference in annotated networks

NASA Astrophysics Data System (ADS)

Newman, M. E. J.; Clauset, Aaron

2016-06-01

For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network. Here we demonstrate how this `metadata' can be used to improve our understanding of network structure. We focus in particular on the problem of community detection in networks and develop a mathematically principled approach that combines a network and its metadata to detect communities more accurately than can be done with either alone. Crucially, the method does not assume that the metadata are correlated with the communities we are trying to find. Instead, the method learns whether a correlation exists and correctly uses or ignores the metadata depending on whether they contain useful information. We demonstrate our method on synthetic networks with known structure and on real-world networks, large and small, drawn from social, biological and technological domains.

How can social network analysis contribute to social behavior research in applied ethology?

PubMed

Makagon, Maja M; McCowan, Brenda; Mench, Joy A

2012-05-01

Social network analysis is increasingly used by behavioral ecologists and primatologists to describe the patterns and quality of interactions among individuals. We provide an overview of this methodology, with examples illustrating how it can be used to study social behavior in applied contexts. Like most kinds of social interaction analyses, social network analysis provides information about direct relationships (e.g. dominant-subordinate relationships). However, it also generates a more global model of social organization that determines how individual patterns of social interaction relate to individual and group characteristics. A particular strength of this approach is that it provides standardized mathematical methods for calculating metrics of sociality across levels of social organization, from the population and group levels to the individual level. At the group level these metrics can be used to track changes in social network structures over time, evaluate the effect of the environment on social network structure, or compare social structures across groups, populations or species. At the individual level, the metrics allow quantification of the heterogeneity of social experience within groups and identification of individuals who may play especially important roles in maintaining social stability or information flow throughout the network.

Perspectives on Social Network Analysis for Observational Scientific Data

NASA Astrophysics Data System (ADS)

Singh, Lisa; Bienenstock, Elisa Jayne; Mann, Janet

This chapter is a conceptual look at data quality issues that arise during scientific observations and their impact on social network analysis. We provide examples of the many types of incompleteness, bias and uncertainty that impact the quality of social network data. Our approach is to leverage the insights and experience of observational behavioral scientists familiar with the challenges of making inference when data are not complete, and suggest avenues for extending these to relational data questions. The focus of our discussion is on network data collection using observational methods because they contain high dimensionality, incomplete data, varying degrees of observational certainty, and potential observer bias. However, the problems and recommendations identified here exist in many other domains, including online social networks, cell phone networks, covert networks, and disease transmission networks.

Effective spreading from multiple leaders identified by percolation in the susceptible-infected-recovered (SIR) model

NASA Astrophysics Data System (ADS)

Ji, Shenggong; Lü, Linyuan; Yeung, Chi Ho; Hu, Yanqing

2017-07-01

Social networks constitute a new platform for information propagation, but its success is crucially dependent on the choice of spreaders who initiate the spreading of information. In this paper, we remove edges in a network at random and the network segments into isolated clusters. The most important nodes in each cluster then form a set of influential spreaders, such that news propagating from them would lead to extensive coverage and minimal redundancy. The method utilizes the similarities between the segmented networks before percolation and the coverage of information propagation in each social cluster to obtain a set of distributed and coordinated spreaders. Our tests of implementing the susceptible-infected-recovered model on Facebook and Enron email networks show that this method outperforms conventional centrality-based methods in terms of spreadability and coverage redundancy. The suggested way of identifying influential spreaders thus sheds light on a new paradigm of information propagation in social networks.

Bringing the Best of Two Worlds Together for Social Capital Research in Education: Social Network Analysis and Symbolic Interactionism

ERIC Educational Resources Information Center

Lee, Moosung

2014-01-01

This article proposes an analytical consideration for social capital research in education by exploring a pragmatic combination of social network analysis (SNA) and symbolic interactionism (SI) as a research method. The article first delineates the theoretical linkages of social capital theory with SNA and SI. The article then discusses how SNA…

Social network properties and self-rated health in later life: comparisons from the Korean social life, health, and aging project and the national social life, health and aging project

PubMed Central

2014-01-01

Background This paper has two objectives. Firstly, it provides an overview of the social network module, data collection procedures, and measurement of ego-centric and complete-network properties in the Korean Social Life, Health, and Aging Project (KSHAP). Secondly, it directly compares the KSHAP structure and results to the ego-centric network structure and results of the National Social Life, Health, and Aging Project (NSHAP), which conducted in-home interviews with 3,005 persons 57 to 85 years of age in the United States. Methods The structure of the complete social network of 814 KSHAP respondents living in Township K was measured and examined at two levels of networks. Ego-centric network properties include network size, composition, volume of contact with network members, density, and bridging potential. Complete-network properties are degree centrality, closeness centrality, betweenness centrality, and brokerage role. Results We found that KSHAP respondents with a smaller number of social network members were more likely to be older and tended to have poorer self-rated health. Compared to the NSHAP, the KSHAP respondents maintained a smaller network size with a greater network density among their members and lower bridging potential. Further analysis of the complete network properties of KSHAP respondents revealed that more brokerage roles inside the same neighborhood (Ri) were significantly associated with better self-rated health. Socially isolated respondents identified by network components had the worst self-rated health. Conclusions The findings demonstrate the importance of social network analysis for the study of older adults’ health status in Korea. The study also highlights the importance of complete-network data and its ability to reveal mechanisms beyond ego-centric network data. PMID:25217892

Burstiness and tie activation strategies in time-varying social networks

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-01

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Mapping Extension's Networks: Using Social Network Analysis to Explore Extension's Outreach

ERIC Educational Resources Information Center

Bartholomay, Tom; Chazdon, Scott; Marczak, Mary S.; Walker, Kathrin C.

2011-01-01

The University of Minnesota Extension conducted a social network analysis (SNA) to examine its outreach to organizations external to the University of Minnesota. The study found that its outreach network was both broad in its reach and strong in its connections. The study found that SNA offers a unique method for describing and measuring Extension…

Motivation for and Use of Social Networking Sites: Comparisons among College Students with and without Histories of Non-Suicidal Self-Injury

ERIC Educational Resources Information Center

Jarvi, Stephanie M.; Swenson, Lance P.; Batejan, Kristen L.

2017-01-01

Objective: This research examines potential differences in social network use and motivation for social network use by non-suicidal self-injury (NSSI) status. Participants: 367 (73% women; M[subscript age] = 20.60) college students were recruited in November-December 2011. Methods: A random sample of 2,500 students was accessed through a…

Systemwide Reform in Districts under Pressure: The Role of Social Networks in Defining, Acquiring, Using, and Diffusing Research Evidence

ERIC Educational Resources Information Center

Finnigan, Kara S.; Daly, Alan J.; Che, Jing

2013-01-01

Purpose: The purpose of this paper is to examine the way in which low-performing schools and their district define, acquire, use, and diffuse research-based evidence. Design/methodology/approach: The mixed methods case study builds upon the prior research on research evidence and social networks, drawing on social network analyses, survey data and…

The investigation of social networks based on multi-component random graphs

NASA Astrophysics Data System (ADS)

Zadorozhnyi, V. N.; Yudin, E. B.

2018-01-01

The methods of non-homogeneous random graphs calibration are developed for social networks simulation. The graphs are calibrated by the degree distributions of the vertices and the edges. The mathematical foundation of the methods is formed by the theory of random graphs with the nonlinear preferential attachment rule and the theory of Erdôs-Rényi random graphs. In fact, well-calibrated network graph models and computer experiments with these models would help developers (owners) of the networks to predict their development correctly and to choose effective strategies for controlling network projects.

Youth's social network structures and peer influences: study protocol MyMovez project - Phase I.

PubMed

Bevelander, Kirsten E; Smit, Crystal R; van Woudenberg, Thabo J; Buijs, Laura; Burk, William J; Buijzen, Moniek

2018-04-16

Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and peers) that co-determine their dietary intake and physical activity. However, there is a lack of systematic and comprehensive research on the implementation of a social network approach in health campaigns. The MyMovez research project aims to fill this gap by developing a method for effective social network campaign implementation. This protocol paper describes the design and methods of Phase I of the MyMovez project, aiming to unravel youth's social network structures in combination with individual, psychosocial, and environmental factors related to energy intake and expenditure. In addition, the Wearable Lab is developed to enable an attractive and state-of-the-art way of collecting data and online campaign implementation via social networks. Phase I of the MyMovez project consists of a large-scale cross-sequential cohort study (N = 953; 8-12 and 12-15 y/o). In five waves during a 3-year period (2016-2018), data are collected about youth's social network exposure, media consumption, socialization experiences, psychological determinants of behavior, physical environment, dietary intake (snacking and drinking behavior) and physical activity using the Wearable Lab. The Wearable Lab exists of a smartphone-based research application (app) connected to an activity tracking bracelet, that is developed throughout the duration of the project. It generates peer- and self-reported (e.g., sociometric data and surveys) and experience sampling data, social network beacon data, real-time physical activity data (i.e., steps and cycling), location information, photos and chat conversation data from the app's social media platform Social Buzz. The MyMovez project - Phase I is an innovative cross-sequential research project that investigates how social influences co-determine youth's energy intake and expenditure. This project utilizes advanced research technologies (Wearable Lab) that provide unique opportunities to better understand the underlying processes that impact youths' health-related behaviors. The project is theoretically and methodologically pioneering and produces a unique and useful method for successfully implementing and improving health campaigns.

Social networks and mental health in post-conflict Mitrovica, Kosova.

PubMed

Nakayama, Risa; Koyanagi, Ai; Stickley, Andrew; Kondo, Tetsuo; Gilmour, Stuart; Arenliu, Aliriza; Shibuya, Kenji

2014-11-17

To investigate the relation between social networks and mental health in the post-conflict municipality of Mitrovica, Kosovo. Using a three-stage stratified sampling method, 1239 respondents aged 16 years or above were recruited in the Greater Mitrovica region. Social network depth was measured by the frequency of contacts with friends, relatives and strangers. Depression and anxiety were measured using the Hospital Anxiety and Depression Scale (HADS). Multivariate logistic regression was used to examine the association between social network depth and mental health. The analytical sample consisted of 993 respondents. The prevalence of depression (54.3%) and anxiety (64.4%) were extremely high. In multiple regression analysis, a lower depth of social network (contact with friends) was associated with higher levels of both depression and anxiety. This study has shown that only one variety of social network--contact with friends--was important in terms of mental health outcomes in a population living in an area heavily affected by conflict. This suggests that the relation between social networks and mental health may be complex in that the effects of different forms of social network on mental health are not uniform and may depend on the way social networks are operationalised and the particular context in which the relationship is examined.

Leveraging the Methodological Affordances of Facebook: Social Networking Strategies in Longitudinal Writing Research

ERIC Educational Resources Information Center

Sheffield, Jenna Pack; Kimme Hea, Amy C.

2016-01-01

While composition studies researchers have examined the ways social media are impacting our lives inside and outside of the classroom, less attention has been given to the ways in which social media--specifically Social Network Sites (SNSs)--may enhance our own research methods and methodologies by helping to combat research participant attrition…

College Students' Uses and Perceptions of Social Networking Sites for Health and Wellness Information

ERIC Educational Resources Information Center

Zhang, Yan

2012-01-01

Introduction: This study explores college students' use of social networking sites for health and wellness information and their perceptions of this use. Method: Thirty-eight college students were interviewed. Analysis: The interview transcripts were analysed using the qualitative content analysis method. Results: Those who had experience using…

Hierarchical Network Models for Education Research: Hierarchical Latent Space Models

ERIC Educational Resources Information Center

Sweet, Tracy M.; Thomas, Andrew C.; Junker, Brian W.

2013-01-01

Intervention studies in school systems are sometimes aimed not at changing curriculum or classroom technique, but rather at changing the way that teachers, teaching coaches, and administrators in schools work with one another--in short, changing the professional social networks of educators. Current methods of social network analysis are…

Transitions in Smokers’ Social Networks After Quit Attempts: A Latent Transition Analysis

PubMed Central

Smith, Rachel A.; Piper, Megan E.; Roberts, Linda J.; Baker, Timothy B.

2016-01-01

Introduction: Smokers’ social networks vary in size, composition, and amount of exposure to smoking. The extent to which smokers’ social networks change after a quit attempt is unknown, as is the relation between quitting success and later network changes. Methods: Unique types of social networks for 691 smokers enrolled in a smoking-cessation trial were identified based on network size, new network members, members’ smoking habits, within network smoking, smoking buddies, and romantic partners’ smoking. Latent transition analysis was used to identify the network classes and to predict transitions in class membership across 3 years from biochemically assessed smoking abstinence. Results: Five network classes were identified: Immersed (large network, extensive smoking exposure including smoking buddies), Low Smoking Exposure (large network, minimal smoking exposure), Smoking Partner (small network, smoking exposure primarily from partner), Isolated (small network, minimal smoking exposure), and Distant Smoking Exposure (small network, considerable nonpartner smoking exposure). Abstinence at years 1 and 2 was associated with shifts in participants’ social networks to less contact with smokers and larger networks in years 2 and 3. Conclusions: In the years following a smoking-cessation attempt, smokers’ social networks changed, and abstinence status predicted these changes. Networks defined by high levels of exposure to smokers were especially associated with continued smoking. Abstinence, however, predicted transitions to larger social networks comprising less smoking exposure. These results support treatments that aim to reduce exposure to smoking cues and smokers, including partners who smoke. Implications: Prior research has shown that social network features predict the likelihood of subsequent smoking cessation. The current research illustrates how successful quitting predicts social network change over 3 years following a quit attempt. Specifically, abstinence predicts transitions to networks that are larger and afford less exposure to smokers. This suggests that quitting smoking may expand a person’s social milieu rather than narrow it. This effect, plus reduced exposure to smokers, may help sustain abstinence. PMID:27613925

Volunteerism: Social Network Dynamics and Education

PubMed Central

Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

2016-01-01

Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

Intergenerational Social Networks and Health Behaviors Among Children Living in Public Housing

PubMed Central

Schwartz, Heather; Thornton, Rachel Johnson; Griffin, Beth Ann; Green, Harold D.; Kennedy, David P.; Burkhauser, Susan; Pollack, Craig Evan

2015-01-01

Objectives. In a survey of families living in public housing, we investigated whether caretakers’ social networks are linked with children’s health status. Methods. In 2011, 209 children and their caretakers living in public housing in suburban Montgomery County, Maryland, were surveyed regarding their health and social networks. We used logistic regression models to examine the associations between the perceived health composition of caretaker social networks and corresponding child health characteristics (e.g., exercise, diet). Results. With each 10% increase in the proportion of the caretaker’s social network that exercised regularly, the child’s odds of exercising increased by 34% (adjusted odds ratio = 1.34; 95% confidence interval = 1.07, 1.69) after the caretaker’s own exercise behavior and the composition of the child’s peer network had been taken into account. Although children’s overweight or obese status was associated with caretakers’ social networks, the results were no longer significant after adjustment for caretakers’ own weight status. Conclusions. We found that caretaker social networks are independently associated with certain aspects of child health, suggesting the importance of the broader social environment for low-income children’s health. PMID:26378821

To friend or not to friend: the use of social media in clinical oncology.

PubMed

Wiener, Lori; Crum, Caroline; Grady, Christine; Merchant, Melinda

2012-03-01

Online social networking has replaced more traditional methods of personal and professional communication in many segments of society today. The wide reach and immediacy of social media facilitate dissemination of knowledge in advocacy and cancer education, but the usefulness of social media in personal relationships between patients and providers is still unclear. Although professional guidelines regarding e-mail communication may be relevant to social media, the inherent openness in social networks creates potential boundary and privacy issues in the provider-patient context. This commentary seeks to increase provider awareness of unique issues and challenges raised by the integration of social networking into oncology communications.

Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Social Network Analysis for Assessing College-Aged Adults' Health: A Systematic Review.

PubMed

Patterson, Megan S; Go Odson, Patricia

2018-04-13

Social network analysis (SNA) is a useful, emerging method for studying health. College students are especially prone to social influence when it comes to health. This review aimed to identify network variables related to college student health and determine how SNA was used in the literature. A systematic review of relevant literature was conducted in October 2015. Studies employing egocentric or whole network analysis to study college student health were included. We used Garrard's Matrix Method to extract data from reviewed articles (n = 15). Drinking, smoking, aggression, homesickness, and stress were predicted by network variables in the reviewed literature. Methodological inconsistencies concerning boundary specification, data collection, nomination limits, and statistical analyses were revealed across studies. Results show the consistent relationship between network variables and college health outcomes, justifying further use of SNA to research college health. Suggestions and considerations for future use of SNA are provided.

Social networks and social support for healthy eating among Latina breast cancer survivors: Implications for social and behavioral interventions

PubMed Central

Crookes, Danielle M.; Shelton, Rachel C.; Tehranifar, Parisa; Aycinena, Corina; Gaffney, Ann Ogden; Koch, Pam; Contento, Isobel R.; Greenlee, Heather

2015-01-01

Purpose Little is known about Latina breast cancer survivors' social networks or their perceived social support to achieve and maintain a healthy diet. This paper describes the social networks and perceived support for healthy eating in a sample of breast cancer survivors of predominantly Dominican descent living in New York City. Methods Spanish-speaking Latina breast cancer survivors enrolled in a randomized controlled trial of a culturally-tailored dietary intervention. Social networks were assessed using Cohen's Social Network Index and a modified General Social Survey Social Networks Module that included assessments of shared health promoting behaviors. Perceived social support from family and friends for healthy, food-related behaviors was assessed. Results Participants' networks consisted predominantly of family and friends. Family members were more likely than other individuals to be identified as close network members. Participants were more likely to share food-related activities than exercise activities with close network members. Perceived social support for healthy eating was high, although perceived support from spouses and children was higher than support from friends. Despite high levels of perceived support, family was also identified as a barrier to eating healthy foods by nearly half of women. Conclusions Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. Implications for Cancer Survivors Involving family members in dietary interventions for Latina breast cancer survivors may tap into positive sources of support for women, which could facilitate uptake and maintenance of healthy eating behaviors. PMID:26202538

Fishing in the Amazonian forest: a gendered social network puzzle

PubMed Central

Díaz-Reviriego, I.; Fernández-Llamazares, Á.; Howard, P.L; Molina, JL; Reyes-García, V

2016-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers’ emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane’ Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers’ expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers’ expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use. PMID:28479670

Fishing in the Amazonian forest: a gendered social network puzzle.

PubMed

Díaz-Reviriego, I; Fernández-Llamazares, Á; Howard, P L; Molina, J L; Reyes-García, V

2017-01-01

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers' emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane' Amerindians of the Bolivian Amazonia. A multiple regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between the fishers' expertise, their socio-demographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers' expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise as well as natural resource access and use.

Improving social connection through a communities-of-practice-inspired cognitive work analysis approach.

PubMed

Euerby, Adam; Burns, Catherine M

2014-03-01

Increasingly, people work in socially networked environments. With growing adoption of enterprise social network technologies, supporting effective social community is becoming an important factor in organizational success. Relatively few human factors methods have been applied to social connection in communities. Although team methods provide a contribution, they do not suit design for communities. Wenger's community of practice concept, combined with cognitive work analysis, provided one way of designing for community. We used a cognitive work analysis approach modified with principles for supporting communities of practice to generate a new website design. Over several months, the community using the site was studied to examine their degree of social connectedness and communication levels. Social network analysis and communications analysis, conducted at three different intervals, showed increases in connections between people and between people and organizations, as well as increased communication following the launch of the new design. In this work, we suggest that human factors approaches can be effective in social environments, when applied considering social community principles. This work has implications for the development of new human factors methods as well as the design of interfaces for sociotechnical systems that have community building requirements.

An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback

PubMed Central

Fagan, Jesse M; Collins, Tom

2017-01-01

Background Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky. Objective We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky. Methods A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio. Results OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher’s perspective, and hindering practicality in the field. Conclusions OpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations. PMID:28642217

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

PubMed Central

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S.

2017-01-01

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages. PMID:28771201

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

PubMed

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Effectiveness of link prediction for face-to-face behavioral networks.

PubMed

Tsugawa, Sho; Ohsaki, Hiroyuki

2013-01-01

Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30-0.45 and a recall of 0.10-0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks.

Polarity related influence maximization in signed social networks.

PubMed

Li, Dong; Xu, Zhi-Ming; Chakraborty, Nilanjan; Gupta, Anika; Sycara, Katia; Li, Sheng

2014-01-01

Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust) between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust) between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC) model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P) diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.

Polarity Related Influence Maximization in Signed Social Networks

PubMed Central

Li, Dong; Xu, Zhi-Ming; Chakraborty, Nilanjan; Gupta, Anika; Sycara, Katia; Li, Sheng

2014-01-01

Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust) between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust) between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC) model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P) diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods. PMID:25061986

Implementing a Standardized Social Networks Testing Strategy in a Low HIV Prevalence Jurisdiction.

PubMed

Schumann, Casey; Kahn, Danielle; Broaddus, Michelle; Dougherty, Jacob; Elderbrook, Megan; Vergeront, James; Westergaard, Ryan

2018-05-15

Alternative HIV testing strategies are needed to engage individuals not reached by traditional clinical or non-clinical testing programs. A social networks recruitment strategy, in which people at risk for or living with HIV are enlisted and trained by community-based agencies to recruit individuals from their social, sexual, or drug-using networks for HIV testing, demonstrates higher positivity rates compared to other non-clinical recruitment strategies in some jurisdictions. During 2013-2015, a social networks testing protocol was implemented in Wisconsin to standardize an existing social networks testing program. Six community-based, non-clinical agencies with multiple sites throughout the state implemented the protocol over the 2-year period. Both quantitative and qualitative data were collected. The new positivity rate (0.49%) through social networks testing did not differ from that of traditional counseling, testing, and referral recruitment methods (0.48%). Although social networks testing did not yield a higher new positivity rate compared to other testing strategies, it proved to be successful at reaching high risk individuals who may not otherwise engage in HIV testing.

The Pearl in the Middle: A Case Study of Social Interactions in an Individual with a Severe Intellectual Disability

ERIC Educational Resources Information Center

Johnson, Hilary; Douglas, Jacinta; Bigby, Christine; Iacono, Teresa

2010-01-01

Background: People with severe intellectual disability have limited communication skills, small social networks, and may experience isolation. Little is known about how interactions occur with social network members and the role of social support. Method: An adult with a severe intellectual disability was observed in her daily environments. Her…

An Online Social Networking Approach to Reinforce Learning of Rocks and Minerals

ERIC Educational Resources Information Center

Kennelly, Patrick

2009-01-01

Numerous and varied methods are used in introductory Earth science and geology classes to help students learn about rocks and minerals, such as classroom lectures, laboratory specimen identification, and field trips. This paper reports on a method using online social networking. The choice of this forum was based on two criteria. First, many…

Attitudes toward Using Social Networking Sites in Educational Settings with Underperforming Latino Youth: A Mixed Methods Study

ERIC Educational Resources Information Center

Howard, Keith E.; Curwen, Margie Sauceda; Howard, Nicol R.; Colón-Muñiz, Anaida

2015-01-01

The researchers examined the online social networking attitudes of underperforming Latino high school students in an alternative education program that uses technology as the prime venue for learning. A sequential explanatory mixed methods study was used to cross-check multiple sources of data explaining students' levels of comfort with utilizing…

Estimation of Global Network Statistics from Incomplete Data

PubMed Central

Bliss, Catherine A.; Danforth, Christopher M.; Dodds, Peter Sheridan

2014-01-01

Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week. PMID:25338183

Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes.

PubMed

Young, Sean D; Rivers, Caitlin; Lewis, Bryan

2014-06-01

Recent availability of "big data" might be used to study whether and how sexual risk behaviors are communicated on real-time social networking sites and how data might inform HIV prevention and detection. This study seeks to establish methods of using real-time social networking data for HIV prevention by assessing 1) whether geolocated conversations about HIV risk behaviors can be extracted from social networking data, 2) the prevalence and content of these conversations, and 3) the feasibility of using HIV risk-related real-time social media conversations as a method to detect HIV outcomes. In 2012, tweets (N=553,186,061) were collected online and filtered to include those with HIV risk-related keywords (e.g., sexual behaviors and drug use). Data were merged with AIDSVU data on HIV cases. Negative binomial regressions assessed the relationship between HIV risk tweeting and prevalence by county, controlling for socioeconomic status measures. Over 9800 geolocated tweets were extracted and used to create a map displaying the geographical location of HIV-related tweets. There was a significant positive relationship (p<.01) between HIV-related tweets and HIV cases. Results suggest the feasibility of using social networking data as a method for evaluating and detecting Human immunodeficiency virus (HIV) risk behaviors and outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Information dynamics algorithm for detecting communities in networks

NASA Astrophysics Data System (ADS)

Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

2012-11-01

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

Social Network Influences on Service Use among Urban, African American Youth with Mental Health Problems

PubMed Central

Lindsey, Michael A.; Barksdale, Crystal L.; Lambert, Sharon F.; Ialongo, Nicholas S.

2010-01-01

Objective To examine the associations between the size and quality of African American adolescents' social networks and their mental health service use, and to examine whether these social networks characteristics moderate the association between need for services due to emotional or behavioral difficulties and use of services. Method Participants were a community sample of African American adolescents (N=465; 46.2% female; mean age 14.78) initially recruited in 1st grade for participation in an evaluation of two preventive intervention trials. Social network influences and adolescents' mental health service use in schools and the community were accessed. Results A significant positive association between adolescents' perception that their social network was helpful and their use of school mental health services was identified. The significant associations between need for services for anxiety, depression, or behavior problems, and school and outpatient service use were moderated by size of the social network. Specifically, among youth in need of services for anxiety or depression, school-based service use was higher for those with larger social networks. Conclusions Implications for enhancing access to formal mental health services include further examination of key social network influences that potentially serve as facilitators or barriers to formal help-seeking. The findings also suggest that it might be important to integrate social network members into interventions to address the mental health needs of adolescents. PMID:20864006

An Appraisal of Social Network Theory and Analysis as Applied to Public Health: Challenges and Opportunities.

PubMed

Valente, Thomas W; Pitts, Stephanie R

2017-03-20

The use of social network theory and analysis methods as applied to public health has expanded greatly in the past decade, yielding a significant academic literature that spans almost every conceivable health issue. This review identifies several important theoretical challenges that confront the field but also provides opportunities for new research. These challenges include (a) measuring network influences, (b) identifying appropriate influence mechanisms, (c) the impact of social media and computerized communications, (d) the role of networks in evaluating public health interventions, and (e) ethics. Next steps for the field are outlined and the need for funding is emphasized. Recently developed network analysis techniques, technological innovations in communication, and changes in theoretical perspectives to include a focus on social and environmental behavioral influences have created opportunities for new theory and ever broader application of social networks to public health topics.

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Social Network Type and Subjective Well-being in a National Sample of Older Americans

PubMed Central

Litwin, Howard; Shiovitz-Ezra, Sharon

2011-01-01

Purpose: The study considers the social networks of older Americans, a population for whom there have been few studies of social network type. It also examines associations between network types and well-being indicators: loneliness, anxiety, and happiness. Design and Methods: A subsample of persons aged 65 years and older from the first wave of the National Social Life, Health, and Aging Project was employed (N = 1,462). We applied K-means cluster analysis to derive social network types using 7 criterion variables. In the multivariate stage, the well-being outcomes were regressed on the network type construct and on background and health characteristics by means of logistic regression. Results: Five social network types were derived: “diverse,” “friend,” “congregant,” “family,” and “restricted.” Social network type was found to be associated with each of the well-being indicators after adjusting for demographic and health confounders. Respondents embedded in network types characterized by greater social capital tended to exhibit better well-being in terms of less loneliness, less anxiety, and greater happiness. Implications: Knowledge about differing network types should make gerontological practitioners more aware of the varying interpersonal milieus in which older people function. Adopting network type assessment as an integral part of intake procedures and tracing network shifts over time can serve as a basis for risk assessment as well as a means for determining the efficacy of interventions. PMID:21097553

Social Media and Electronic Networking Use and Preferences among Undergraduate Turf Science Students

ERIC Educational Resources Information Center

Bigelow, Cale A.; Kaminski, John E., III

2016-01-01

Most undergraduate students arrive on campus fluent in electronic communication methods and social media (SM). This cultural or communication shift presents both opportunities and challenges in pedagogy. Social media allows users to share and network with geographically diverse individuals and has the potential for engaging students both inside…

Social networks and alcohol use among older adults: a comparison with middle-aged adults.

PubMed

Kim, Seungyoun; Spilman, Samantha L; Liao, Diana H; Sacco, Paul; Moore, Alison A

2018-04-01

This study compared the association between social networks and alcohol consumption among middle-aged (MA) and older adults (OA) to better understand the nature of the relationship between those two factors among OA and MA. We examined Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Current drinkers aged over 50 were subdivided into two age groups: MA (50-64, n = 5214) and OA (65 and older, n = 3070). Each age group was stratified into drinking levels (low-risk vs. at-risk) based on alcohol consumption. The size and diversity of social networks were measured. Logistic regression models were used to examine age differences in the association between the social networks (size and diversity) and the probability of at-risk drinking among two age groups. A significant association between the social networks diversity and lower odds of at-risk drinking was found among MA and OA. However, the relationship between the diversity of social networks and the likelihood of at-risk drinking was weaker for OA than for MA. The association between social networks size and at-risk drinking was not significant among MA and OA. The current study suggests that the association between social networks diversity and alcohol use among OA differs from the association among MA, and few social networks were associated with alcohol use among OA. In the future, research should consider an in-depth exploration of the nature of social networks and alcohol consumption by using longitudinal designs and advanced methods of exploring drinking networks.

Simulating Social Networks of Online Communities: Simulation as a Method for Sociability Design

NASA Astrophysics Data System (ADS)

Ang, Chee Siang; Zaphiris, Panayiotis

We propose the use of social simulations to study and support the design of online communities. In this paper, we developed an Agent-Based Model (ABM) to simulate and study the formation of social networks in a Massively Multiplayer Online Role Playing Game (MMORPG) guild community. We first analyzed the activities and the social network (who-interacts-with-whom) of an existing guild community to identify its interaction patterns and characteristics. Then, based on the empirical results, we derived and formalized the interaction rules, which were implemented in our simulation. Using the simulation, we reproduced the observed social network of the guild community as a means of validation. The simulation was then used to examine how various parameters of the community (e.g. the level of activity, the number of neighbors of each agent, etc) could potentially influence the characteristic of the social networks.

To Friend or Not to Friend: The Use of Social Media in Clinical Oncology

PubMed Central

Wiener, Lori; Crum, Caroline; Grady, Christine; Merchant, Melinda

2012-01-01

Online social networking has replaced more traditional methods of personal and professional communication in many segments of society today. The wide reach and immediacy of social media facilitate dissemination of knowledge in advocacy and cancer education, but the usefulness of social media in personal relationships between patients and providers is still unclear. Although professional guidelines regarding e-mail communication may be relevant to social media, the inherent openness in social networks creates potential boundary and privacy issues in the provider-patient context. This commentary seeks to increase provider awareness of unique issues and challenges raised by the integration of social networking into oncology communications. PMID:23077437

Testing a model of facilitated reflection on network feedback: a mixed method study on integration of rural mental healthcare services for older people.

PubMed

Fuller, Jeffrey; Oster, Candice; Muir Cochrane, Eimear; Dawson, Suzanne; Lawn, Sharon; Henderson, Julie; O'Kane, Deb; Gerace, Adam; McPhail, Ruth; Sparkes, Deb; Fuller, Michelle; Reed, Richard L

2015-11-11

To test a management model of facilitated reflection on network feedback as a means to engage services in problem solving the delivery of integrated primary mental healthcare to older people. Participatory mixed methods case study evaluating the impact of a network management model using organisational network feedback (through social network analysis, key informant interviews and policy review). A model of facilitated network reflection using network theory and methods. A rural community in South Australia. 32 staff from 24 services and 12 senior service managers from mental health, primary care and social care services. Health and social care organisations identified that they operated in clustered self-managed networks within sectors, with no overarching purposive older people's mental healthcare network. The model of facilitated reflection revealed service goal and role conflicts. These discussions helped local services to identify as a network, and begin the problem-solving communication and referral links. A Governance Group assisted this process. Barriers to integrated servicing through a network included service funding tied to performance of direct care tasks and the lack of a clear lead network administration organisation. A model of facilitated reflection helped organisations to identify as a network, but revealed sensitivity about organisational roles and goals, which demonstrated that conflict should be expected. Networked servicing needed a neutral network administration organisation with cross-sectoral credibility, a mandate and the resources to monitor the network, to deal with conflict, negotiate commitment among the service managers, and provide opportunities for different sectors to meet and problem solve. This requires consistency and sustained intersectoral policies that include strategies and funding to facilitate and maintain health and social care networks in rural communities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Feasibility of using social networking technologies for health research among men who have sex with men: a mixed methods study.

PubMed

Young, Sean D; Jaganath, Devan

2014-01-01

This study aims to assess the feasibility and acceptability of using social networking as a health research platform among men who have sex with men (MSM). Fifty-five MSM (primarily African American and Latino) were invited to join a "secret" group on the social networking website, Facebook. Peer leaders, trained in health education, posted health-related content to groups. The study and analysis used mixed (qualitative and quantitative) methods. Facebook conversations were thematically analyzed. Latino and African American participants voluntarily used social networking to discuss health-related knowledge and personal topics (exercise, nutrition, mental health, disease prevention, and substance abuse) with other group participants (N=564 excerpts). Although Latinos comprised 60% of the sample and African Americans 25.5%, Latinos contributed 82% of conversations and African Americans contributed only 15% of all conversations. Twenty-four percent of posts from Latinos and 7% of posts from African Americans were related to health topics. Results suggest that Facebook is an acceptable and engaging platform for facilitating and documenting health discussions for mixed methods research among MSM. An understanding of population differences is needed for crafting effective online social health interventions.

Feasibility of using social networking technologies for health research among men who have sex with men: A mixed methods study

PubMed Central

Young, Sean D.; Jaganath, Devan

2013-01-01

This study aims to assess the feasibility and acceptability of using social networking as a health research platform among men who have sex with men (MSM). Fifty-five MSM (primarily African American and Latino) were invited to join a “secret” group on the social networking website, Facebook. Peer leaders, trained in health education, posted health-related content to groups. The study and analysis used mixed (qualitative and quantitative) methods. Facebook conversations were thematically analyzed. Latino and African-American participants voluntarily used social networking to discuss health-related knowledge and personal topics (exercise, nutrition, mental health, disease prevention, and substance abuse) with other group participants (N=564 excerpts). Although Latinos comprised 60% of the sample and African Americans 25.5%, Latinos contributed 82% of conversations and African Americans contributed only 15% of all conversations. Twenty-four percent (24%) of posts from Latinos and 7% of posts from African Americans were related to health topics. Results suggest that Facebook is an acceptable and engaging platform for facilitating and documenting health discussions for mixed methods research among MSM. An understanding of population differences is needed for crafting effective online social health interventions. PMID:23407600

Problematic use of social networking sites among urban school going teenagers

PubMed Central

Meena, Parth Singh; Mittal, Pankaj Kumar; Solanki, Ram Kumar

2012-01-01

Background: Social networking sites like Facebook, Orkut and Twitter are virtual communities where users can create individual public profiles, interact with real-life friends and meet other people based on shared interests. An exponential rise in usage of Social Networking Sites have been seen within the last few years. Their ease of use and immediate gratification effect on users has changed the way people in general and students in particular spend their time. Young adults, particularly teenagers tended to be unaware of just how much time they really spent on social networking sites. Negative correlates of Social Networking Sites usage include the decrease in real life social community participation and academic achievement, as well as relationship problems, each of which may be indicative of potential addiction. Aims: the aim of the study was to find out whether teenagers, specially those living in cities spend too much time on social networking websites. Materials and Methods: 200 subjects, both boys and girls were included in the cross sectional study who were given a 20 item Young's internet addiction test modified for social networking sites. The responses were analyzed using chi square test and Fisher's exact test. Results: 24.74% of the students were having occasional or ‘frequency’ problems while 2.02% of them were experiencing severe problems due to excessive time spent using social networking sites. Conclusion: With the ever increasing popularity of social media, teenagers are devoting significant time to social networking on websites and are prone to get ‘addicted’ to such form of online social interaction. PMID:24250039

Validation of the Social Networking Activity Intensity Scale among Junior Middle School Students in China.

PubMed

Li, Jibin; Lau, Joseph T F; Mo, Phoenix K H; Su, Xuefen; Wu, Anise M S; Tang, Jie; Qin, Zuguo

2016-01-01

Online social networking use has been integrated into adolescents' daily life and the intensity of online social networking use may have important consequences on adolescents' well-being. However, there are few validated instruments to measure social networking use intensity. The present study aims to develop the Social Networking Activity Intensity Scale (SNAIS) and validate it among junior middle school students in China. A total of 910 students who were social networking users were recruited from two junior middle schools in Guangzhou, and 114 students were retested after two weeks to examine the test-retest reliability. The psychometrics of the SNAIS were estimated using appropriate statistical methods. Two factors, Social Function Use Intensity (SFUI) and Entertainment Function Use Intensity (EFUI), were clearly identified by both exploratory and confirmatory factor analyses. No ceiling or floor effects were observed for the SNAIS and its two subscales. The SNAIS and its two subscales exhibited acceptable reliability (Cronbach's alpha = 0.89, 0.90 and 0.60, and test-retest Intra-class Correlation Coefficient = 0.85, 0.87 and 0.67 for Overall scale, SFUI and EFUI subscale, respectively, p<0.001). As expected, the SNAIS and its subscale scores were correlated significantly with emotional connection to social networking, social networking addiction, Internet addiction, and characteristics related to social networking use. The SNAIS is an easily self-administered scale with good psychometric properties. It would facilitate more research in this field worldwide and specifically in the Chinese population.

Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction.

PubMed

Gupta, Shashank; Pawar, Sachin; Ramrakhiyani, Nitin; Palshikar, Girish Keshav; Varma, Vasudeva

2018-06-13

Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-health monitoring tasks, specifically for pharmacovigilance. We study the problem of extraction of Adverse-Drug-Reaction (ADR) mentions from social media, particularly from Twitter. Medical information extraction from social media is challenging, mainly due to short and highly informal nature of text, as compared to more technical and formal medical reports. Current methods in ADR mention extraction rely on supervised learning methods, which suffer from labeled data scarcity problem. The state-of-the-art method uses deep neural networks, specifically a class of Recurrent Neural Network (RNN) which is Long-Short-Term-Memory network (LSTM). Deep neural networks, due to their large number of free parameters rely heavily on large annotated corpora for learning the end task. But in the real-world, it is hard to get large labeled data, mainly due to the heavy cost associated with the manual annotation. To this end, we propose a novel semi-supervised learning based RNN model, which can leverage unlabeled data also present in abundance on social media. Through experiments we demonstrate the effectiveness of our method, achieving state-of-the-art performance in ADR mention extraction. In this study, we tackle the problem of labeled data scarcity for Adverse Drug Reaction mention extraction from social media and propose a novel semi-supervised learning based method which can leverage large unlabeled corpus available in abundance on the web. Through empirical study, we demonstrate that our proposed method outperforms fully supervised learning based baseline which relies on large manually annotated corpus for a good performance.

A geovisual analytic approach to understanding geo-social relationships in the international trade network.

PubMed

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly 'balkanized' (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

A Geovisual Analytic Approach to Understanding Geo-Social Relationships in the International Trade Network

PubMed Central

Luo, Wei; Yin, Peifeng; Di, Qian; Hardisty, Frank; MacEachren, Alan M.

2014-01-01

The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly ‘balkanized’ (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above. PMID:24558409

Effectiveness of Link Prediction for Face-to-Face Behavioral Networks

PubMed Central

Tsugawa, Sho; Ohsaki, Hiroyuki

2013-01-01

Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30–0.45 and a recall of 0.10–0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks. PMID:24339956

Social Disadvantage and Network Turnover

PubMed Central

2015-01-01

Objectives. Research shows that socially disadvantaged groups—especially African Americans and people of low socioeconomic status (SES)—experience more unstable social environments. I argue that this causes higher rates of turnover within their personal social networks. This is a particularly important issue among disadvantaged older adults, who may benefit from stable networks. This article, therefore, examines whether social disadvantage is related to various aspects of personal network change. Method. Social network change was assessed using longitudinal egocentric network data from the National Social Life, Health, and Aging Project, a study of older adults conducted between 2005 and 2011. Data collection in Wave 2 included a technique for comparing respondents’ confidant network rosters between waves. Rates of network losses, deaths, and additions were modeled using multivariate Poisson regression. Results. African Americans and low-SES individuals lost more confidants—especially due to death—than did whites and college-educated respondents. African Americans also added more confidants than whites. However, neither African Americans nor low-SES individuals were able to match confidant losses with new additions to the extent that others did, resulting in higher levels of confidant network shrinkage. These trends are partly, but not entirely, explained by disadvantaged individuals’ poorer health and their greater risk of widowhood or marital dissolution. Discussion. Additional work is needed to shed light on the role played by race- and class-based segregation on group differences in social network turnover. Social gerontologists should examine the role these differences play in explaining the link between social disadvantage and important outcomes in later life, such as health decline. PMID:24997286

On Deep Learning for Trust-Aware Recommendations in Social Networks.

PubMed

Deng, Shuiguang; Huang, Longtao; Xu, Guandong; Wu, Xindong; Wu, Zhaohui

2017-05-01

With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user's trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users' interests and their trusted friends' interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.

Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

PubMed Central

Portela, Javier; García Villalba, Luis Javier; Silva Trujillo, Alejandra Guadalupe; Sandoval Orozco, Ana Lucila; Kim, Tai-Hoon

2016-01-01

Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks. PMID:27809275

Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks.

PubMed

Portela, Javier; García Villalba, Luis Javier; Silva Trujillo, Alejandra Guadalupe; Sandoval Orozco, Ana Lucila; Kim, Tai-Hoon

2016-11-01

Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users' network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders' or receivers' identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.

Social networking site (SNS) use by adolescent mothers: Can social support and social capital be enhanced by online social networks? - A structured review of the literature.

PubMed

Nolan, Samantha; Hendricks, Joyce; Ferguson, Sally; Towell, Amanda

2017-05-01

to critically appraise the available literature and summarise the evidence relating to adolescent mothers' use of social networking sites in terms of any social support and social capital they may provide and to identify areas for future exploration. social networking sites have been demonstrated to provide social support to marginalised individuals and provide psycho-social benefits to members of such groups. Adolescent mothers are at risk of; social marginalisation; anxiety disorders and depressive symptoms; and poorer health and educational outcomes for their children. Social support has been shown to benefit adolescent mothers thus online mechanisms require consideration. a review of original research articles METHOD: key terms and Boolean operators identified research reports across a 20-year timeframe pertaining to the area of enquiry in: CINAHL, Cochrane Library, Medline, Scopus, ERIC, ProQuest, PsychINFO, Web of Science, Health Collection (Informit) and Google Scholar databases. Eight original research articles met the inclusion criteria for this review. studies demonstrate that adolescent mothers actively search for health information using the Internet and social networking sites, and that social support and social capital can be attributed to their use of specifically created online groups from within targeted health interventions. Use of a message board forum for pregnant and parenting adolescents also demonstrates elements of social support. There are no studies to date pertaining to adolescent mothers' use of globally accessible social networking sites in terms of social support provision and related outcomes. further investigation is warranted to explore the potential benefits of adolescent mothers' use of globally accessible social networking sites in terms of any social support provision and social capital they may provide. Copyright © 2017 Elsevier Ltd. All rights reserved.

Social Trust Prediction Using Heterogeneous Networks

PubMed Central

HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

2014-01-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776

Social Trust Prediction Using Heterogeneous Networks.

PubMed

Huang, Jin; Nie, Feiping; Huang, Heng; Tu, Yi-Cheng; Lei, Yu

2013-11-01

Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method.

Social networking in nursing education: integrative literature review

PubMed Central

Kakushi, Luciana Emi; Évora, Yolanda Dora Martinez

2016-01-01

Abstract Objective: to identify the use of social networking in nursing education. Method: integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. Results: of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%), originating from the United States and United Kingdom (77.8%). It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning) and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%), Ning (28.5%), Twitter (21.4%) and MySpace (7.1%), by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. Conclusion: few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process. PMID:27384465

Identifying emerging research collaborations and networks: method development.

PubMed

Dozier, Ann M; Martina, Camille A; O'Dell, Nicole L; Fogg, Thomas T; Lurie, Stephen J; Rubinstein, Eric P; Pearson, Thomas A

2014-03-01

Clinical and translational research is a multidisciplinary, collaborative team process. To evaluate this process, we developed a method to document emerging research networks and collaborations in our medical center to describe their productivity and viability over time. Using an e-mail survey, sent to 1,620 clinical and basic science full- and part-time faculty members, respondents identified their research collaborators. Initial analyses, using Pajek software, assessed the feasibility of using social network analysis (SNA) methods with these data. Nearly 400 respondents identified 1,594 collaborators across 28 medical center departments resulting in 309 networks with 5 or more collaborators. This low-burden approach yielded a rich data set useful for evaluation using SNA to: (a) assess networks at several levels of the organization, including intrapersonal (individuals), interpersonal (social), organizational/institutional leadership (tenure and promotion), and physical/environmental (spatial proximity) and (b) link with other data to assess the evolution of these networks.

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras

PubMed Central

Shakya, Holly B; Stafford, Derek; Hughes, D Alex; Keegan, Thomas; Negron, Rennie; Broome, Jai; McKnight, Mark; Nicoll, Liza; Nelson, Jennifer; Iriarte, Emma; Ordonez, Maria; Airoldi, Edo; Fowler, James H; Christakis, Nicholas A

2017-01-01

Introduction Despite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change. Methods and analysis We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions. Ethics and dissemination The Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a ‘toolkit’ for practitioners to use in network-based intervention efforts, including public release of our network mapping software. Trial registration number NCT02694679; Pre-results. PMID:28289044

Investigating Sociodemographic Factors and HIV Risk Behaviors Associated With Social Networking Among Adolescents in Soweto, South Africa: A Cross-Sectional Survey

PubMed Central

Laher, Fatima; Hornschuh, Stefanie; Nkala, Busisiwe; Chimoyi, Lucy; Otwombe, Kennedy; Kaida, Angela; Gray, Glenda Elisabeth; Miller, Cari

2016-01-01

Background Internet access via mobile phones and computers facilitates interaction and potential health communication among individuals through social networking. Many South African adolescents own mobile phones and can access social networks via apps. Objective We investigated sociodemographic factors and HIV risk behaviors of adolescent social networking users in Soweto, South Africa. Methods We conducted an interviewer-administered, cross-sectional survey of adolescents aged 14-19 years. Independent covariates of social networking were assessed by multivariate logistic regression analysis. Results Of 830 adolescents, 57% (475/830) were females and the median age was found to be 18 years (interquartile range 17-18). Social networking was used by 60% of adolescents (494/830); more than half, that is, 87% (396/494) accessed social networks through mobile phones and 56% (275/494) spent more than 4 hours per day using their mobile phones. Social networking was independently associated with mobile usage 2-4 hours (adjusted odds ratio [AOR]: 3.06, CI: 1.69-5.51) and more than 4 hours per day (AOR: 6.16, CI: 3.46-10.9) and one (AOR: 3.35, CI: 1.79-6.27) or more sexual partner(s) (AOR: 2.58, CI: 1.05-6.36). Conclusions Mobile phone–based social networking is prevalent among sexually active adolescents living in Soweto and may be used as an entry point for health promotion and initiation of low-cost adolescent health interventions. PMID:27683173

The Peer Social Networks of Young Children with Down Syndrome in Classroom Programmes

PubMed Central

Guralnick, Michael J.; Connor, Robert T.; Johnson, L. Clark

2010-01-01

Background The nature and characteristics of the peer social networks of young children with Down syndrome in classroom settings were examined within a developmental framework. Method Comparisons were made with younger typically developing children matched on mental age and typically developing children matched on chronological age. Results Similar patterns were found for all three groups for most peer social network measures. However, group differences were obtained for measures of teacher assistance and peer interactions in unstructured situations. Conclusions Positive patterns appeared to be related to the social orientation of children with Down syndrome and the special efforts of teachers to support children’s peer social networks. Findings also suggested that fundamental peer competence problems for children with Down syndrome remain and may best be addressed within the framework of contemporary models of peer-related social competence. PMID:21765644

Organisational adaptation in an activist network: social networks, leadership, and change in al-Muhajiroun.

PubMed

Kenney, Michael; Horgan, John; Horne, Cale; Vining, Peter; Carley, Kathleen M; Bigrigg, Michael W; Bloom, Mia; Braddock, Kurt

2013-09-01

Social networks are said to facilitate learning and adaptation by providing the connections through which network nodes (or agents) share information and experience. Yet, our understanding of how this process unfolds in real-world networks remains underdeveloped. This paper explores this gap through a case study of al-Muhajiroun, an activist network that continues to call for the establishment of an Islamic state in Britain despite being formally outlawed by British authorities. Drawing on organisation theory and social network analysis, we formulate three hypotheses regarding the learning capacity and social network properties of al-Muhajiroun (AM) and its successor groups. We then test these hypotheses using mixed methods. Our methods combine quantitative analysis of three agent-based networks in AM measured for structural properties that facilitate learning, including connectedness, betweenness centrality and eigenvector centrality, with qualitative analysis of interviews with AM activists focusing organisational adaptation and learning. The results of these analyses confirm that al-Muhajiroun activists respond to government pressure by changing their operations, including creating new platforms under different names and adjusting leadership roles among movement veterans to accommodate their spiritual leader's unwelcome exodus to Lebanon. Simple as they are effective, these adaptations have allowed al-Muhajiroun and its successor groups to continue their activism in an increasingly hostile environment. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Oral health related quality of life in pregnant and post partum women in two social network domains; predominantly home-based and work-based networks

PubMed Central

2012-01-01

Background Individuals connected to supportive social networks have better general and oral health quality of life. The objective of this study was to assess whether there were differences in oral health related quality of life (OHRQoL) between women connected to either predominantly home-based and work-based social networks. Methods A follow-up prevalence study was conducted on 1403 pregnant and post-partum women (mean age of 25.2 ± 6.3 years) living in two cities in the State of Rio de Janeiro, Brazil. Women were participants in an established cohort followed from pregnancy (baseline) to post-partum period (follow-up). All participants were allocated to two groups; 1. work-based social network group - employed women with paid work, and, 2. home-based social network group - women with no paid work, housewives or unemployed women. Measures of social support and social network were used as well as questions on sociodemographic characteristics and OHRQoL and health related behaviors. Multinomial logistic regression was performed to obtain OR of relationships between occupational contexts, affectionate support and positive social interaction on the one hand, and oral health quality of life, using the Oral Health Impacts Profile (OHIP) measure, adjusted for age, ethnicity, family income, schooling, marital status and social class. Results There was a modifying effect of positive social interaction on the odds of occupational context on OHRQoL. The odds of having a poorer OHIP score, ≥4, was significantly higher for women with home-based social networks and moderate levels of positive social interactions [OR 1.64 (95% CI: 1.08-2.48)], and for women with home-based social networks and low levels of positive social interactions [OR 2.15 (95% CI: 1.40-3.30)] compared with women with work-based social networks and high levels of positive social interactions. Black ethnicity was associated with OHIP scores ≥4 [OR 1.73 (95% CI: 1.23-2.42)]. Conclusions Pregnant and post-partum Brazilian women in paid employment outside the home and having social supports had better OHRQoL than those with home-based social networks. PMID:22244015

Mathematical modelling of complex contagion on clustered networks

NASA Astrophysics Data System (ADS)

O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James

2015-09-01

The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

Eb&D: A new clustering approach for signed social networks based on both edge-betweenness centrality and density of subgraphs

NASA Astrophysics Data System (ADS)

Qi, Xingqin; Song, Huimin; Wu, Jianliang; Fuller, Edgar; Luo, Rong; Zhang, Cun-Quan

2017-09-01

Clustering algorithms for unsigned social networks which have only positive edges have been studied intensively. However, when a network has like/dislike, love/hate, respect/disrespect, or trust/distrust relationships, unsigned social networks with only positive edges are inadequate. Thus we model such kind of networks as signed networks which can have both negative and positive edges. Detecting the cluster structures of signed networks is much harder than for unsigned networks, because it not only requires that positive edges within clusters are as many as possible, but also requires that negative edges between clusters are as many as possible. Currently, we have few clustering algorithms for signed networks, and most of them requires the number of final clusters as an input while it is actually hard to predict beforehand. In this paper, we will propose a novel clustering algorithm called Eb &D for signed networks, where both the betweenness of edges and the density of subgraphs are used to detect cluster structures. A hierarchically nested system will be constructed to illustrate the inclusion relationships of clusters. To show the validity and efficiency of Eb &D, we test it on several classical social networks and also hundreds of synthetic data sets, and all obtain better results compared with other methods. The biggest advantage of Eb &D compared with other methods is that the number of clusters do not need to be known prior.

The Association between Social Network Betweenness and Coronary Calcium: A Baseline Study of Patients with a High Risk of Cardiovascular Disease

PubMed Central

Joo, Won-tak; Lee, Chan Joo; Oh, Jaewon; Kim, In-Cheol; Lee, Sang-Hak; Kang, Seok-Min; Kim, Hyeon Chang; Park, Sungha; Youm, Yoosik

2018-01-01

Aim: The association of social networks with cardiovascular disease (CVD) has been demonstrated through various studies. This study aimed to examine the association between social network betweenness–a network position of mediating between diverse social groups–and coronary artery calcium. Methods: The data of 1,384 participants from the Cardiovascular and Metabolic Disease Etiology Research Center–High Risk Cohort, a prospective cohort study enrolling patients with a high risk of developing CVD (clinicaltrials.gov: NCT02003781), were analyzed. The deficiency in social network betweenness was measured in two ways: only-family networks, in which a respondent had networks with only family members, and no-cutpoint networks, in which the respondent does not function as a point of bridging between two or more social groups that are not directly connected. Results: Participants who had higher coronary artery calcium scores (CACSs) were likely to have a smaller network size (p < 0.001), only-family networks (p < 0.001), and no-cutpoint networks (p < 0.001). Multiple logistic regression analyses revealed no significant association between network size and CACS. Only no-cutpoint networks had a significant relationship with CACS > 400 (odds ratio, 1.72; 95% confidence interval, 1.07–2.77; p = 0.026). The association was stronger among older (age > 60 years) and female respondents. Conclusion: Deficiency in social network betweenness is closely related to coronary calcium in participants with a high risk of CVD. To generalize these results to a general population, further study should be performed. PMID:28740058

The structural and functional brain networks that support human social networks.

PubMed

Noonan, M P; Mars, R B; Sallet, J; Dunbar, R I M; Fellows, L K

2018-02-20

Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Social support networks and eating disorders: an integrative review of the literature

PubMed Central

Leonidas, Carolina; dos Santos, Manoel Antônio

2014-01-01

Aims This study aimed to analyze the scientific literature about social networks and social support in eating disorders (ED). Methods By combining keywords, an integrative review was performed. It included publications from 2006–2013, retrieved from the MEDLINE, LILACS, PsycINFO, and CINAHL databases. The selection of articles was based on preestablished inclusion and exclusion criteria. Results A total of 24 articles were selected for data extraction. There was a predominance of studies that used nonexperimental and descriptive designs, and which were published in international journals. This review provided evidence of the fact that fully consolidated literature regarding social support and social networks in patients with ED is not available, given the small number of studies dedicated to the subject. We identified evidence that the family social network of patients with ED has been widely explored by the literature, although there is a lack of studies about other networks and sources of social support outside the family. Conclusion The evidence presented in this study shows the need to include other social networks in health care. This expansion beyond family networks would include significant others – such as friends, colleagues, neighbors, people from religious groups, among others – who could help the individual coping with the disorder. The study also highlights the need for future research on this topic, as well as a need for greater investment in publications on the various dimensions of social support and social networks. PMID:24899810

The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

PubMed Central

Reafee, Waleed; Salim, Naomie; Khan, Atif

2016-01-01

The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

Exploring Student Use of Social Networking Services (SNS) Surrounding Moral Development, Gender, Campus Crime, Safety, and the Clery Act: A Mixed Methods Study

ERIC Educational Resources Information Center

Baum, Haley

2017-01-01

The purpose of this explanatory sequential mixed methods study was to explore college students' use of social networking services (SNS); examining how and why they communicate about campus safety information. This study took place at Stockton University, a regional state institution in NJ. Undergraduate students took part in an online quantitative…

Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

ERIC Educational Resources Information Center

Firdausiah Mansur, Andi Besse; Yusof, Norazah

2013-01-01

Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

The Role of the Social Network in Access to Psychosocial Services for Migrant Elderly—A Qualitative Study

PubMed Central

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-01-01

Background: Despite high prevalence of mental problems among elderly migrants in The Netherlands, the use of psychosocial care services by this group is low. Scientific evidence points at the crucial role of social support for mental health and the use of psychosocial services. We therefore explored the role of social networks in the access to psychosocial care among elderly migrants in The Netherlands. Methods: A qualitative study was conducted using semi-structured group interviews and individual interviews. The eight group and eleven individual interviews (respectively n = 58 and n = 11) were conducted in The Netherlands with Turkish, Moroccan, Surinamese, and Dutch elderly. The data were analysed through coding and comparing fragments and recognizing patterns. Results: Support of the social network is important to navigate to psychosocial care and is most frequently provided by children. However, the social network of elderly migrants is generally not able to meet the needs of the elderly. This is mostly due to poor mental health literacy of the social network, taboo, and stigma around mental illness and the busy lives of the social network members. Conclusions: Strategies to address help-seeking barriers should consider mental health literacy in elderly migrants as well as their social networks, and counteract taboos and stigma of mental health problems. PMID:29019961

The Role of the Social Network in Access to Psychosocial Services for Migrant Elderly-A Qualitative Study.

PubMed

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-10-11

Abstract : Background: Despite high prevalence of mental problems among elderly migrants in The Netherlands, the use of psychosocial care services by this group is low. Scientific evidence points at the crucial role of social support for mental health and the use of psychosocial services. We therefore explored the role of social networks in the access to psychosocial care among elderly migrants in The Netherlands. Methods: A qualitative study was conducted using semi-structured group interviews and individual interviews. The eight group and eleven individual interviews (respectively n = 58 and n = 11) were conducted in The Netherlands with Turkish, Moroccan, Surinamese, and Dutch elderly. The data were analysed through coding and comparing fragments and recognizing patterns. Results: Support of the social network is important to navigate to psychosocial care and is most frequently provided by children. However, the social network of elderly migrants is generally not able to meet the needs of the elderly. This is mostly due to poor mental health literacy of the social network, taboo, and stigma around mental illness and the busy lives of the social network members. Conclusion s : Strategies to address help-seeking barriers should consider mental health literacy in elderly migrants as well as their social networks, and counteract taboos and stigma of mental health problems.

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites

PubMed Central

2017-01-01

Abstract Objectives: This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Method: Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Results: Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Discussion: Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. PMID:28329871

Predicting Node Degree Centrality with the Node Prominence Profile

PubMed Central

Yang, Yang; Dong, Yuxiao; Chawla, Nitesh V.

2014-01-01

Centrality of a node measures its relative importance within a network. There are a number of applications of centrality, including inferring the influence or success of an individual in a social network, and the resulting social network dynamics. While we can compute the centrality of any node in a given network snapshot, a number of applications are also interested in knowing the potential importance of an individual in the future. However, current centrality is not necessarily an effective predictor of future centrality. While there are different measures of centrality, we focus on degree centrality in this paper. We develop a method that reconciles preferential attachment and triadic closure to capture a node's prominence profile. We show that the proposed node prominence profile method is an effective predictor of degree centrality. Notably, our analysis reveals that individuals in the early stage of evolution display a distinctive and robust signature in degree centrality trend, adequately predicted by their prominence profile. We evaluate our work across four real-world social networks. Our findings have important implications for the applications that require prediction of a node's future degree centrality, as well as the study of social network dynamics. PMID:25429797

A methodological approach to the analysis of egocentric social networks in public health research: a practical example.

PubMed

Djomba, Janet Klara; Zaletel-Kragelj, Lijana

2016-12-01

Research on social networks in public health focuses on how social structures and relationships influence health and health-related behaviour. While the sociocentric approach is used to study complete social networks, the egocentric approach is gaining popularity because of its focus on individuals, groups and communities. One of the participants of the healthy lifestyle health education workshop 'I'm moving', included in the study of social support for exercise was randomly selected. The participant was denoted as the ego and members of her/his social network as the alteri. Data were collected by personal interviews using a self-made questionnaire. Numerical methods and computer programmes for the analysis of social networks were used for the demonstration of analysis. The size, composition and structure of the egocentric social network were obtained by a numerical analysis. The analysis of composition included homophily and homogeneity. Moreover, the analysis of the structure included the degree of the egocentric network, the strength of the ego-alter ties and the average strength of ties. Visualisation of the network was performed by three freely available computer programmes, namely: Egonet.QF, E-net and Pajek. The computer programmes were described and compared by their usefulness. Both numerical analysis and visualisation have their benefits. The decision what approach to use is depending on the purpose of the social network analysis. While the numerical analysis can be used in large-scale population-based studies, visualisation of personal networks can help health professionals at creating, performing and evaluation of preventive programmes, especially if focused on behaviour change.

Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

PubMed Central

Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

2016-01-01

Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

Young Men's Social Network Characteristics and Associations with Sexual Partnership Concurrency in Tanzania.

PubMed

Yamanis, Thespina J; Fisher, Jacob C; Moody, James W; Kajula, Lusajo J

2016-06-01

Social network influence on young people's sexual behavior is understudied in sub-Saharan Africa. Previous research identified networks of mostly young men in Dar es Salaam who socialize in "camps". This study describes network characteristics within camps and their relationship to young men's concurrent sexual partnerships. We conducted surveys with a nearly complete census of ten camp networks (490 men and 160 women). Surveys included name generators to identify camp-based networks. Fifty seven percent of sexually active men (n = 471) reported past year concurrency, measured using the UNAIDS method. In a multivariable model, men's individual concurrency was associated with being a member of a closer knit camp in which concurrency was the normative behavior. Younger men who had older members in their networks were more likely to engage in concurrency. Respondent concurrency was also associated with inequitable personal gender norms. Our findings suggest strategies for leveraging social networks for HIV prevention among young men.

Predicting Positive and Negative Relationships in Large Social Networks.

PubMed

Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

2015-01-01

In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

Social Networks and Well-being: A Comparison of Older People in Mediterranean and Non-Mediterranean Countries

PubMed Central

2010-01-01

Objectives. This study examined whether the social networks of older persons in Mediterranean and non-Mediterranean countries were appreciably different and whether they functioned in similar ways in relation to well-being outcomes. Methods. The sample included family household respondents aged 60 years and older from the first wave of the Survey of Health, Ageing and Retirement in Europe in 5 Mediterranean (n = 3,583) and 7 non-Mediterranean (n = 5,471) countries. Region was regressed separately by gender on variables from 4 network domains: structure and interaction, exchange, engagement and relationship quality, and controlling for background and health characteristics. In addition, 2 well-being outcomes—depressive symptoms and perceived income inadequacy—were regressed on the study variables, including regional social network interaction terms. Results. The results revealed differences across the 2 regional settings in each of the realms of social network, above and beyond the differences that exist in background characteristics and health status. The findings also showed that the social network variables had different effects on the well-being outcomes in the respective settings. Discussion. The findings underscore that the social network phenomenon is contextually bound. The social networks of older people should be seen within their unique regional milieu and in relation to the values and social norms that prevail in different sets of societies. PMID:20008485

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks

PubMed Central

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-01-01

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C/2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C/2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi’s model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments. PMID:29401668

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks.

PubMed

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.

An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback.

PubMed

Eddens, Katherine S; Fagan, Jesse M; Collins, Tom

2017-06-22

Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky. We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky. A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio. OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools. Respondents enjoyed the social network survey component, and visualizing social networks produced thoughtful responses from participants about leveraging or changing network content and structure for specific health-promoting purposes. Areas for improved literacy and functionality of the tool were identified. However, technical issues led to substantial (50%) data loss, limiting the success of its implementation from a researcher's perspective, and hindering practicality in the field. OpenEddi is a promising data collection tool for use in geographically isolated and socioeconomically disadvantaged populations. Future development will mitigate technical problems, improve usability and literacy, and test new methods of data collection. These changes will support goals for use of this tool in the delivery of network-based health communication and social support interventions to socioeconomically disadvantaged populations. ©Katherine S Eddens, Jesse M Fagan, Tom Collins. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 22.06.2017.

Social Networks of Adults with an Intellectual Disability from South Asian and White Communities in the United Kingdom: A Comparison

ERIC Educational Resources Information Center

Bhardwaj, Anjali K.; Forrester-Jones, Rachel V. E.; Murphy, Glynis H.

2018-01-01

Background: Little research exists comparing the social networks of people with intellectual disability (ID) from South Asian and White backgrounds. This UK study reports on the barriers that South Asian people with intellectual disability face in relation to social inclusion compared to their White counterparts. Materials and methods: A…

Linguistic Politeness and Interpersonal Ties among Bengalis on the Social Network Site Orkut[R]: The Bulge Theory Revisited

ERIC Educational Resources Information Center

Das, Anupam

2010-01-01

This study examined linguistic politeness behaviors and their relationship to social distance among members of a diasporic Bengali community on the social network site "Orkut"[R]. Using data from computer-mediated communication (CMC), specifically text messages posted on "Orkut"[R] "scrapbooks," it developed a method to test the claims of the…

The analysis of social network data: an exciting frontier for statisticians.

PubMed

O'Malley, A James

2013-02-20

The catalyst for this paper is the recent interest in the relationship between social networks and an individual's health, which has arisen following a series of papers by Nicholas Christakis and James Fowler on person- to-person spread of health behaviors. In this issue, they provide a detailed explanation of their methods that offers insights, justifications, and responses to criticisms. In this paper, we introduce some of the key statistical methods used in social network analysis and indicate where those used by Christakis and Fowler (CF) fit into the general framework. The intent is to provide the background necessary for readers to be able to make their own evaluation of the work by CF and understand the challenges of research involving social networks. We entertain possible solutions to some of the difficulties encountered in accounting for confounding effects in analyses of peer effects and provide comments on the contributions of CF. Copyright © 2012 John Wiley & Sons, Ltd.

Auxiliary Parameter MCMC for Exponential Random Graph Models

NASA Astrophysics Data System (ADS)

Byshkin, Maksym; Stivala, Alex; Mira, Antonietta; Krause, Rolf; Robins, Garry; Lomi, Alessandro

2016-11-01

Exponential random graph models (ERGMs) are a well-established family of statistical models for analyzing social networks. Computational complexity has so far limited the appeal of ERGMs for the analysis of large social networks. Efficient computational methods are highly desirable in order to extend the empirical scope of ERGMs. In this paper we report results of a research project on the development of snowball sampling methods for ERGMs. We propose an auxiliary parameter Markov chain Monte Carlo (MCMC) algorithm for sampling from the relevant probability distributions. The method is designed to decrease the number of allowed network states without worsening the mixing of the Markov chains, and suggests a new approach for the developments of MCMC samplers for ERGMs. We demonstrate the method on both simulated and actual (empirical) network data and show that it reduces CPU time for parameter estimation by an order of magnitude compared to current MCMC methods.

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women

PubMed Central

Oshri, Assaf; Himelboim, Itai; Kwon, Josephine A.; Sutton, Tara E.; Mackillop, James

2015-01-01

Objective: The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. Method: A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals’ Facebook network. Results: Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. Conclusions: Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions. PMID:26562592

Overlapping Modularity at the Critical Point of k-Clique Percolation

NASA Astrophysics Data System (ADS)

Tóth, Bálint; Vicsek, Tamás; Palla, Gergely

2013-05-01

One of the most remarkable social phenomena is the formation of communities in social networks corresponding to families, friendship circles, work teams, etc. Since people usually belong to several different communities at the same time, the induced overlaps result in an extremely complicated web of the communities themselves. Thus, uncovering the intricate community structure of social networks is a non-trivial task with great potential for practical applications, gaining a notable interest in the recent years. The Clique Percolation Method (CPM) is one of the earliest overlapping community finding methods, which was already used in the analysis of several different social networks. In this approach the communities correspond to k-clique percolation clusters, and the general heuristic for setting the parameters of the method is to tune the system just below the critical point of k-clique percolation. However, this rule is based on simple physical principles and its validity was never subject to quantitative analysis. Here we examine the quality of the partitioning in the vicinity of the critical point using recently introduced overlapping modularity measures. According to our results on real social and other networks, the overlapping modularities show a maximum close to the critical point, justifying the original criteria for the optimal parameter settings.

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study

PubMed Central

Choi, Jun-Ho; Lee, Jong-Seok

2016-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods. PMID:26793137

Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

PubMed Central

Dean, Danielle O.; Bauer, Daniel J.; Prinstein, Mitchell J.

2018-01-01

A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common—as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed. PMID:28463022

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study.

PubMed

Choi, Jun-Ho; Lee, Jong-Seok

2015-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

Utopia Providing Trusted Social Network Relationships within an Un-trusted Environment

NASA Astrophysics Data System (ADS)

Gauvin, William; Liu, Benyuan; Fu, Xinwen; Wang, Jie

This paper introduces an unobtrusive method and distributed solution set to aid users of on-line social networking sites, by creating a trusted environment in which every member has the ability to identify each other within their private social network by name, gender, age, location, and the specific usage patterns adopted by the group. Utopia protects members by understanding how the social network is created and the specific aspects of the group that make it unique and identifiable. The main focus of Utopia is the protection of the group, and their privacy within a social network from predators and spammers that characteristically do not fit within the well defined usage boundaries of the social network as a whole. The solution set provides defensive, as well as offensive tools to identify these threats. Once identified, client desktop tools are used to prevent these predators from further interaction within the group. In addition, offensive tools are used to determine the origin of the predator to allow actions to be taken by automated tools and law enforcement to alleviate the threat.

Integration of Spatial and Social Network Analysis in Disease Transmission Studies.

PubMed

Emch, Michael; Root, Elisabeth D; Giebultowicz, Sophia; Ali, Mohammad; Perez-Heydrich, Carolina; Yunus, Mohammad

2012-01-01

This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The paper first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database which consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties between households using a complete network design and distance matrices are also created to model spatial relationships. Moran's I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects-spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always clusters in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases however kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study has offered several strategies on how.

Integration of Spatial and Social Network Analysis in Disease Transmission Studies

PubMed Central

Root, Elisabeth D; Giebultowicz, Sophia; Ali, Mohammad; Perez-Heydrich, Carolina; Yunus, Mohammad

2013-01-01

This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The paper first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database which consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties between households using a complete network design and distance matrices are also created to model spatial relationships. Moran's I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects-spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always clusters in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases however kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study has offered several strategies on how. PMID:24163443

Interests diffusion in social networks

NASA Astrophysics Data System (ADS)

D'Agostino, Gregorio; D'Antonio, Fulvio; De Nicola, Antonio; Tucci, Salvatore

2015-10-01

We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.

Sexual networks: the integration of social and genetic data.

PubMed

Day, S; Ward, H; Ison, C; Bell, G; Weber, J

1998-12-01

New methods for studying sexual networks are presented, drawing upon routine procedures followed in genitourinary medicine clinics in the UK for tracing partners and identifying strains of infection. The routine social procedures were developed to incorporate a structured interview. The routine microbiological diagnosis of gonorrhoea was augmented by phenotyping and the development of new genetic techniques for the fine discrimination of gonococcal strains (opa-typing). Selected results from a study in Sheffield, UK show that each method has limitations, when conducted separately, but these are minimised when the methods are combined. Moreover, the use of simple and routine methods of data collection resolve issues of scale and sample that have beset other network studies, as they provide a means of covering a larger and defined population. Popular concepts about these methods are discussed in the conclusion. The integrated approach employed in our research raises questions both about social methods, 'of people who lie, particularly when they talk about sex', and about microbiological methods, 'of genes that tell the truth' and bypass what people say and think altogether. We argue that these stereotypes are misleading insofar as they suggest that genetic techniques can substitute for the social, and we suggest that even the finest discrimination of organisms at the genetic level will never obviate the need for their interpretation in the light of social data.

Enhancing social networks: a qualitative study of health and social care practice in UK mental health services.

PubMed

Webber, Martin; Reidy, Hannah; Ansari, David; Stevens, Martin; Morris, David

2015-03-01

People with severe mental health problems such as psychosis have access to less social capital, defined as resources within social networks, than members of the general population. However, a lack of theoretically and empirically informed models hampers the development of social interventions which seek to enhance an individual's social networks. This paper reports the findings of a qualitative study, which used ethnographic field methods in six sites in England to investigate how workers helped people recovering from psychosis to enhance their social networks. This study drew upon practice wisdom and lived experience to provide data for intervention modelling. Data were collected from 73 practitioners and 51 people who used their services in two phases. Data were selected and coded using a grounded theory approach to depict the key themes that appeared to underpin the generation of social capital within networks. Findings are presented in four over-arching themes - worker skills, attitudes and roles; connecting people processes; role of the agency; and barriers to network development. The sub-themes which were identified included worker attitudes; person-centred approach; equality of worker-individual relationship; goal setting; creating new networks and relationships; engagement through activities; practical support; existing relationships; the individual taking responsibility; identifying and overcoming barriers; and moving on. Themes were consistent with recovery models used within mental health services and will provide the basis for the development of an intervention model to enhance individuals' access to social capital within networks. © 2014 John Wiley & Sons Ltd.

Design and Methods of a Social Network Isolation Study for Reducing Respiratory Infection Transmission: The eX-FLU Cluster Randomized Trial

PubMed Central

Aiello, Allison E.; Simanek, Amanda M.; Eisenberg, Marisa C.; Walsh, Alison R.; Davis, Brian; Volz, Erik; Cheng, Caroline; Rainey, Jeanette J.; Uzicanin, Amra; Gao, Hongjiang; Osgood, Nathaniel; Knowles, Dylan; Stanley, Kevin; Tarter, Kara; Monto, Arnold S.

2016-01-01

Background Social networks are increasingly recognized as important points of intervention, yet relatively few intervention studies of respiratory infection transmission have utilized a network design. Here we describe the design, methods, and social network structure of a randomized intervention for isolating respiratory infection cases in a university setting over a 10-week period. Methodology/Principal Findings 590 students in six residence halls enrolled in the eX-FLU study during a chain-referral recruitment process from September 2012-January 2013. Of these, 262 joined as “seed” participants, who nominated their social contacts to join the study, of which 328 “nominees” enrolled. Participants were cluster-randomized by 117 residence halls. Participants were asked to respond to weekly surveys on health behaviors, social interactions, and influenza-like illness (ILI) symptoms. Participants were randomized to either a 3-Day dorm room isolation intervention or a control group (no isolation) upon illness onset. ILI cases reported on their isolation behavior during illness and provided throat and nasal swab specimens at onset, day-three, and day-six of illness. A subsample of individuals (N=103) participated in a sub-study using a novel smartphone application, iEpi, which collected sensor and contextually-dependent survey data on social interactions. Within the social network, participants were significantly positively assortative by intervention group, enrollment type, residence hall, iEpi participation, age, gender, race, and alcohol use (all P<0.002). Conclusions/Significance We identified a feasible study design for testing the impact of isolation from social networks in a university setting. These data provide an unparalleled opportunity to address questions about isolation and infection transmission, as well as insights into social networks and behaviors among college-aged students. Several important lessons were learned over the course of this project, including feasible isolation durations, the need for extensive organizational efforts, as well as the need for specialized programmers and server space for managing survey and smartphone data. PMID:27266848

Do We Really Need to Catch Them All? A New User-Guided Social Media Crawling Method

NASA Astrophysics Data System (ADS)

Erlandsson, Fredrik; Bródka, Piotr; Boldt, Martin; Johnson, Henric

2017-12-01

With the growing use of popular social media services like Facebook and Twitter it is challenging to collect all content from the networks without access to the core infrastructure or paying for it. Thus, if all content cannot be collected one must consider which data are of most importance. In this work we present a novel User-guided Social Media Crawling method (USMC) that is able to collect data from social media, utilizing the wisdom of the crowd to decide the order in which user generated content should be collected to cover as many user interactions as possible. USMC is validated by crawling 160 public Facebook pages, containing content from 368 million users including 1.3 billion interactions, and it is compared with two other crawling methods. The results show that it is possible to cover approximately 75% of the interactions on a Facebook page by sampling just 20% of its posts, and at the same time reduce the crawling time by 53%. In addition, the social network constructed from the 20% sample contains more than 75% of the users and edges compared to the social network created from all posts, and it has similar degree distribution.

Social Relations in Lebanon: Convoys Across the Life Course

PubMed Central

Antonucci, Toni C.; Ajrouch, Kristine J.; Abdulrahim, Sawsan

2015-01-01

Objectives: This study systematically analyzed convoys of social relations to investigate the ways in which gender and income shape patterns of social relations across the life course in Lebanon. Methods: Data were drawn from a representative sample of adults aged 18 and older in Greater Beirut, Lebanon (N = 500). Multiple linear regression and multilevel models were conducted to examine main and interactive effects of age, gender, and income on social relations. Results: Findings indicate main effects of age, income, and gender on network structure and relationship quality. Older age was associated with larger network size, greater proportion of kin in network, higher positive and lower negative relationship quality. Higher income was associated with larger network size and decreased contact frequency. Female gender was also associated with decreased contact frequency. Gender interacted with income to influence network size and network composition. Higher income was associated with a larger network size and higher proportion of kin for women. Discussion: Findings suggest diversity in the experience of social relations. Such nuance is particularly relevant to the Lebanese context where family is the main source of support in old age. Policy makers and program planners may need to refrain from viewing social relations simplistically. PMID:24501252

Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest

PubMed Central

Mayhew, Jessica A.; Mulcahy, John B.

2018-01-01

Different aspects of sociality bear considerable weight on the individual- and group-level welfare of captive nonhuman primates. Social Network Analysis (SNA) is a useful tool for gaining a holistic understanding of the dynamic social relationships of captive primate groups. Gaining a greater understanding of captive chimpanzees through investigations of centrality, preferred and avoided relationships, dominance hierarchy, and social network diagrams can be useful in advising current management practices in sanctuaries and other captive settings. In this study, we investigated the dyadic social relationships, group-level social networks, and dominance hierarchy of seven chimpanzees (Pan troglodytes) at Chimpanzee Sanctuary Northwest. We used focal-animal and instantaneous scan sampling to collect 106.75 total hours of associative, affiliative, and agonistic data from June to September 2016. We analyzed our data using SOCPROG to derive dominance hierarchies and network statistics, and we diagrammed the group’s social networks in NetDraw. Three individuals were most central in the grooming network, while two others had little connection. Through agonistic networks, we found that group members reciprocally exhibited agonism, and the group’s dominance hierarchy was statistically non-linear. One chimpanzee emerged as the most dominant through agonism but was least connected to other group members across affiliative networks. Our results indicate that the conventional methods used to calculate individuals’ dominance rank may be inadequate to wholly depict a group’s social relationships in captive sanctuary populations. Our results have an applied component that can aid sanctuary staff in a variety of ways to best ensure the improvement of group welfare. PMID:29444112

Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest.

PubMed

Funkhouser, Jake A; Mayhew, Jessica A; Mulcahy, John B

2018-01-01

Different aspects of sociality bear considerable weight on the individual- and group-level welfare of captive nonhuman primates. Social Network Analysis (SNA) is a useful tool for gaining a holistic understanding of the dynamic social relationships of captive primate groups. Gaining a greater understanding of captive chimpanzees through investigations of centrality, preferred and avoided relationships, dominance hierarchy, and social network diagrams can be useful in advising current management practices in sanctuaries and other captive settings. In this study, we investigated the dyadic social relationships, group-level social networks, and dominance hierarchy of seven chimpanzees (Pan troglodytes) at Chimpanzee Sanctuary Northwest. We used focal-animal and instantaneous scan sampling to collect 106.75 total hours of associative, affiliative, and agonistic data from June to September 2016. We analyzed our data using SOCPROG to derive dominance hierarchies and network statistics, and we diagrammed the group's social networks in NetDraw. Three individuals were most central in the grooming network, while two others had little connection. Through agonistic networks, we found that group members reciprocally exhibited agonism, and the group's dominance hierarchy was statistically non-linear. One chimpanzee emerged as the most dominant through agonism but was least connected to other group members across affiliative networks. Our results indicate that the conventional methods used to calculate individuals' dominance rank may be inadequate to wholly depict a group's social relationships in captive sanctuary populations. Our results have an applied component that can aid sanctuary staff in a variety of ways to best ensure the improvement of group welfare.

Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators.

PubMed

Gunn, Christine M; Parker, Victoria A; Bak, Sharon M; Ko, Naomi; Nelson, Kerrie P; Battaglia, Tracy A

2017-08-01

Minority women in the U.S. continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models like patient navigation focus on social barriers, but evidence demonstrating how these models increase social capital is lacking. This pilot study describes the social networks of newly diagnosed breast cancer patients and explores the contributing role of patient navigators. Twenty-five women completed a one hour interview about their social networks related to cancer care support. Network metrics identified important structural attributes and influential individuals. Bivariate associations between network metrics, type of network, and whether the network included a navigator were measured. Secondary analyses explored associations between network structures and clinical outcomes. We identified three types of networks: kin-based, role and/or affect-based, or heterogeneous. Network metrics did not vary significantly by network type. There was a low prevalence of navigators included in the support networks (25%). Network density scores were significantly higher in those networks without a navigator. Network metrics were not predictive of clinical outcomes in multivariate models. Patient navigators were not frequently included in support networks, but provided distinctive types of support. If navigators can identify patients with poorly integrated (less dense) social networks, or who have unmet tangible support needs, the intensity of navigation services could be tailored. Services and systems that address gaps and variations in patient social networks should be explored for their potential to reduce cancer health disparities. This study used a new method to identify the breadth and strength of social support following a diagnosis of breast cancer, especially examining the role of patient navigators in providing support. While navigators were only included in one quarter of patient support networks, they did provide essential supports to some individuals. Health care providers and systems need to better understand the contributions of social supports both within and outside of health care to design and tailor interventions that seek to reduce health care disparities and improve cancer outcomes. © AlphaMed Press 2017.

Social Networks and Sexual Orientation Disparities in Tobacco and Alcohol Use

PubMed Central

Hatzenbuehler, Mark L; McLaughlin, Katie A; Xuan, Ziming

2015-01-01

Objective: The purpose of this study was to examine whether the composition of social networks contributes to sexual orientation disparities in substance use and misuse. Method: Data were obtained from the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative cohort study of adolescents (N = 20,745). Wave 1 collected extensive information about the social networks of participants through peer nomination inventories. Results: Same- and both-sex–attracted youths had higher frequency/quantity of tobacco use in their peer networks than did opposite-sex–attracted youths, and both-sex–attracted youths had higher frequency/quantity of alcohol use and misuse in their peer networks than opposite-sex–attracted youths. Among same- and both-sex–attracted youths, greater frequency/quantity of tobacco use in one’s social network predicted greater use of cigarettes. In addition, greater frequency/quantity of peers’ drinking and drinking to intoxication predicted more alcohol use and alcohol misuse in the both-sex–attracted group. These social network factors mediated sexual orientation–related disparities in tobacco use for both- and same-sex–attracted youths. Moreover, sexual orientation disparities in alcohol misuse were mediated by social network characteristics for the same-sex and both-sex–attracted youths. Importantly, sexual minority adolescents were no more likely to have other sexual minorities in their social networks than were sexual majority youths, ruling out an alternative explanation for our results. Conclusions: These findings highlight the importance of social networks as correlates of substance use behaviors among sexual minority youths and as potential pathways explaining sexual orientation disparities in substance use outcomes. PMID:25486400

Social Network Analysis Reveals the Negative Effects of Attention-Deficit/Hyperactivity Disorder (ADHD) Symptoms on Friend-Based Student Networks.

PubMed

Kim, Jun Won; Kim, Bung-Nyun; Kim, Johanna Inhyang; Lee, Young Sik; Min, Kyung Joon; Kim, Hyun-Jin; Lee, Jaewon

2015-01-01

Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students. A total of 562 sixth-graders from two elementary schools (300 males) provided the names of their best friends (maximum 10 names). Their teachers rated each student's ADHD symptoms using an ADHD rating scale. The results showed that 10.2% of the students were at high risk for ADHD. Significant group differences were observed between the high-risk students and other students in two of the three network parameters (degree, centrality and closeness) used to assess friendship quality, with the high-risk group showing significantly lower values of degree and closeness compared to the other students. Moreover, negative correlations were found between the ADHD rating and two social network analysis parameters. Our findings suggest that the severity of ADHD symptoms is strongly correlated with the quality of social and interpersonal relationships in students with ADHD symptoms.

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Disease implications of animal social network structure: A synthesis across social systems.

PubMed

Sah, Pratha; Mann, Janet; Bansal, Shweta

2018-05-01

The disease costs of sociality have largely been understood through the link between group size and transmission. However, infectious disease spread is driven primarily by the social organization of interactions in a group and not its size. We used statistical models to review the social network organization of 47 species, including mammals, birds, reptiles, fish and insects by categorizing each species into one of three social systems, relatively solitary, gregarious and socially hierarchical. Additionally, using computational experiments of infection spread, we determined the disease costs of each social system. We find that relatively solitary species have large variation in number of social partners, that socially hierarchical species are the least clustered in their interactions, and that social networks of gregarious species tend to be the most fragmented. However, these structural differences are primarily driven by weak connections, which suggest that different social systems have evolved unique strategies to organize weak ties. Our synthetic disease experiments reveal that social network organization can mitigate the disease costs of group living for socially hierarchical species when the pathogen is highly transmissible. In contrast, highly transmissible pathogens cause frequent and prolonged epidemic outbreaks in gregarious species. We evaluate the implications of network organization across social systems despite methodological challenges, and our findings offer new perspective on the debate about the disease costs of group living. Additionally, our study demonstrates the potential of meta-analytic methods in social network analysis to test ecological and evolutionary hypotheses on cooperation, group living, communication and resilience to extrinsic pressures. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

User recommendation in healthcare social media by assessing user similarity in heterogeneous network.

PubMed

Jiang, Ling; Yang, Christopher C

2017-09-01

The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Experiments were conducted on a dataset collected from a popular online health social website, and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections between nodes in the network, while global structural approach takes the indirect connections into account. Therefore, the global similarity approach can deal with sparse networks and capture the implicit similarity between two users. Different approaches may capture different aspects of the similarity relationship between two users. When we combine different methods together, we could achieve a better performance than using each individual method. Copyright © 2017 Elsevier B.V. All rights reserved.

Social networks and secondary health conditions: The critical secondary team for individuals with spinal cord injury

PubMed Central

Guilcher, Sara J. T.; Casciaro, Tiziana; Lemieux-Charles, Louise; Craven, Catharine; McColl, Mary Ann; Jaglal, Susan B.

2012-01-01

Objectives To describe the structure of informal networks for individuals with spinal cord injury (SCI) living in the community, to understand the quality of relationship of informal networks, and to understand the role of informal networks in the prevention and management of secondary health conditions (SHCs). Design Mixed-method descriptive study. Setting Ontario, Canada Participants Community-dwelling adults with an SCI living in Ontario Interventions/methods The Arizona Social Support Interview Survey was used to measure social networks. Participants were asked the following open-ended questions: (1) What have been your experiences with your health care in the community? (2) What have been your experiences with care related to prevention and/or management of SHCs?, (3)What has been the role of your informal social networks (friends/family) related to SHCs? Results Fourteen key informant interviews were conducted (6 men, 8 women). The overall median for available informal networks was 11.0 persons (range 3–19). The informal network engaged in the following roles: (1) advice/validating concerns; (2) knowledge brokers; (3) advocacy; (4) preventing SHCs; (5) assisting with finances; and (6) managing SHCs. Participants described their informal networks as a “secondary team”; a critical and essential force in dealing with SHCs. Conclusions While networks are smaller for persons with SCI compared with the general population, these ties seems to be strong, which is essential when the roles involve a level of trust, certainty, tacit knowledge, and flexibility. These informal networks serve as essential key players in filling the gaps that exist within the formal health care system. PMID:23031170

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

PubMed

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.

Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation

PubMed Central

Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A.; Massafra, Andrea; Pellè, Piergiuseppe

2015-01-01

The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages. PMID:26617539

Analysis and Visualization of Relations in eLearning

NASA Astrophysics Data System (ADS)

Dráždilová, Pavla; Obadi, Gamila; Slaninová, Kateřina; Martinovič, Jan; Snášel, Václav

The popularity of eLearning systems is growing rapidly; this growth is enabled by the consecutive development in Internet and multimedia technologies. Web-based education became wide spread in the past few years. Various types of learning management systems facilitate development of Web-based courses. Users of these courses form social networks through the different activities performed by them. This chapter focuses on searching the latent social networks in eLearning systems data. These data consist of students activity records wherein latent ties among actors are embedded. The social network studied in this chapter is represented by groups of students who have similar contacts and interact in similar social circles. Different methods of data clustering analysis can be applied to these groups, and the findings show the existence of latent ties among the group members. The second part of this chapter focuses on social network visualization. Graphical representation of social network can describe its structure very efficiently. It can enable social network analysts to determine the network degree of connectivity. Analysts can easily determine individuals with a small or large amount of relationships as well as the amount of independent groups in a given network. When applied to the field of eLearning, data visualization simplifies the process of monitoring the study activities of individuals or groups, as well as the planning of educational curriculum, the evaluation of study processes, etc.

Cross-Sectional Study of Young Adults Diagnosed With Juvenile Fibromyalgia: Social Support and Its Impact on Functioning and Mood.

PubMed

Lynch-Jordan, Anne M; Sil, Soumitri; Bromberg, Maggie; Ting, Tracy V; Kashikar-Zuck, Susmita

2015-11-01

Juvenile-onset fibromyalgia (JFM) affects physical, social, and emotional functioning. Little is known about how social support and social interactions are impacted in the transition to young adulthood for patients diagnosed with JFM. Young adults (Mage = 21.6) diagnosed with JFM during adolescence (N = 94) and matched healthy controls (N = 33) completed measures of social network size and diversity, perceived social support, physical functioning, and depressive symptoms as part of a cross-sectional survey study. No difference in social network diversity was found, although JFM patients reported fewer total people within their social networks. JFM patients reported poorer emotional and tangible support and fewer positive social interactions than healthy controls. After controlling for condition and pain intensity, the level of perceived social support was a significant predictor of physical functioning and depressive symptoms, whereas social network size also contributed uniquely to physical functioning. Given the developmental importance of social support in adolescence and young adulthood, interventions should include methods of improving social support into fibromyalgia management. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Social networks and implementation of evidence-based practices in public youth-serving systems: a mixed-methods study

PubMed Central

2011-01-01

Background The present study examines the structure and operation of social networks of information and advice and their role in making decisions as to whether to adopt new evidence-based practices (EBPs) among agency directors and other program professionals in 12 California counties participating in a large randomized controlled trial. Methods Interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. Grounded-theory analytic methods were used to identify themes related to EBP adoption and network influences. A web-based survey collected additional quantitative information on members of information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) for examination of associations between advice seeking and network structure. Results Systems leaders develop and maintain networks of information and advice based on roles, responsibility, geography, and friendship ties. Networks expose leaders to information about EBPs and opportunities to adopt EBPs; they also influence decisions to adopt EBPs. Individuals in counties at the same stage of implementation accounted for 83% of all network ties. Networks in counties that decided not to implement a specific EBP had no extra-county ties. Implementation of EBPs at the two-year follow-up was associated with the size of county, urban versus rural counties, and in-degree centrality. Collaboration was viewed as critical to implementing EBPs, especially in small, rural counties where agencies have limited resources on their own. Conclusions Successful implementation of EBPs requires consideration and utilization of existing social networks of high-status systems leaders that often cut across service organizations and their geographic jurisdictions. Trial Registration NCT00880126 PMID:21958674

Creating Possible Selves: Information Disclosure Behaviour on Social Networks

ERIC Educational Resources Information Center

Bronstein, Jenny

2014-01-01

Introduction: This study investigates the creation of alternative identities or possible selves on social networks by examining self-presentation and self-disclosure as elements of the information disclosure behaviour of Facebook users. Method. An online questionnaire was distributed amongst library and information science students at Bar-Ilan…

Quantified Academic Selves: The Gamification of Research through Social Networking Services

ERIC Educational Resources Information Center

Hammarfelt, Björn; de Rijcke, Sarah; Rushforth, Alexander D.

2016-01-01

Introduction: Our study critically engages with techniques of self-quantification in contemporary academia, by demonstrating how social networking services enact research and scholarly communication as a "game". Method: The empirical part of the study involves an analysis of two leading platforms: Impactstory and ResearchGate. Observed…

Social networks of adults with an intellectual disability from South Asian and White communities in the United Kingdom: A comparison.

PubMed

Bhardwaj, Anjali K; Forrester-Jones, Rachel V E; Murphy, Glynis H

2018-03-01

Little research exists comparing the social networks of people with intellectual disability (ID) from South Asian and White backgrounds. This UK study reports on the barriers that South Asian people with intellectual disability face in relation to social inclusion compared to their White counterparts. A mixed-methods research design was adopted to explore the social lives of 27 men (15 White; 12 South Asian) and 20 women (10 White; 10 South Asian with intellectual disability). Descriptive and parametric tests were used to analyse the quantitative data. The average network size of the whole group was 32 members. South Asian participants had more family members whilst White participants had more service users and staff in their networks; 96% network members from White intellectual disability group were also of White background, whilst the South Asian group had mixed ethnic network members. Social networks of individuals with intellectual disability in this study were found to be larger overall in comparison with previous studies, whilst network structure differed between the White and South Asian population. These differences have implications relating to future service planning and appropriateness of available facilities. © 2017 John Wiley & Sons Ltd.

Social Networks, Sexual Networks and HIV Risk in Men Who Have Sex with Men

PubMed Central

Amirkhanian, Yuri A.

2014-01-01

Worldwide, men who have sex with men (MSM) remain one of the most HIV-vulnerable community populations. A global public health priority is developing new methods of reaching MSM, understanding HIV transmission patterns, and intervening to reduce their risk. Increased attention is being given to the role that MSM networks play in HIV epidemiology. This review of MSM network research studies demonstrates that: (1) Members of the same social network often share similar norms, attitudes, and HIV risk behavior levels; (2) Network interventions are feasible and powerful for reducing unprotected sex and potentially for increasing HIV testing uptake; (3) HIV vulnerability among African American MSM increases when an individual enters a high-risk sexual network characterized by high density and racial homogeneity; and (4) Networks are primary sources of social support for MSM, particularly for those living with HIV, with greater support predicting higher care uptake and adherence. PMID:24384832

What determines social capital in a social-ecological system? Insights from a network perspective.

PubMed

Barnes-Mauthe, Michele; Gray, Steven Allen; Arita, Shawn; Lynham, John; Leung, PingSun

2015-02-01

Social capital is an important resource that can be mobilized for purposive action or competitive gain. The distribution of social capital in social-ecological systems can determine who is more productive at extracting ecological resources and who emerges as influential in guiding their management, thereby empowering some while disempowering others. Despite its importance, the factors that contribute to variation in social capital among individuals have not been widely studied. We adopt a network perspective to examine what determines social capital among individuals in social-ecological systems. We begin by identifying network measures of social capital relevant for individuals in this context, and review existing evidence concerning their determinants. Using a complete social network dataset from Hawaii's longline fishery, we employ social network analysis and other statistical methods to empirically estimate these measures and determine the extent to which individual stakeholder attributes explain variation within them. We find that ethnicity is the strongest predictor of social capital. Measures of human capital (i.e., education, experience), years living in the community, and information-sharing attitudes are also important. Surprisingly, we find that when controlling for other factors, industry leaders and formal fishery representatives are generally not well connected. Our results offer new quantitative insights on the relationship between stakeholder diversity, social networks, and social capital in a coupled social-ecological system, which can aid in identifying barriers and opportunities for action to overcome resource management problems. Our results also have implications for achieving resource governance that is not only ecologically and economically sustainable, but also equitable.

What Determines Social Capital in a Social-Ecological System? Insights from a Network Perspective

NASA Astrophysics Data System (ADS)

Barnes-Mauthe, Michele; Gray, Steven Allen; Arita, Shawn; Lynham, John; Leung, PingSun

2015-02-01

Social capital is an important resource that can be mobilized for purposive action or competitive gain. The distribution of social capital in social-ecological systems can determine who is more productive at extracting ecological resources and who emerges as influential in guiding their management, thereby empowering some while disempowering others. Despite its importance, the factors that contribute to variation in social capital among individuals have not been widely studied. We adopt a network perspective to examine what determines social capital among individuals in social-ecological systems. We begin by identifying network measures of social capital relevant for individuals in this context, and review existing evidence concerning their determinants. Using a complete social network dataset from Hawaii's longline fishery, we employ social network analysis and other statistical methods to empirically estimate these measures and determine the extent to which individual stakeholder attributes explain variation within them. We find that ethnicity is the strongest predictor of social capital. Measures of human capital (i.e., education, experience), years living in the community, and information-sharing attitudes are also important. Surprisingly, we find that when controlling for other factors, industry leaders and formal fishery representatives are generally not well connected. Our results offer new quantitative insights on the relationship between stakeholder diversity, social networks, and social capital in a coupled social-ecological system, which can aid in identifying barriers and opportunities for action to overcome resource management problems. Our results also have implications for achieving resource governance that is not only ecologically and economically sustainable, but also equitable.

The importance of social networks on smoking: perspectives of women who quit smoking during pregnancy.

PubMed

Nguyen, Stephanie N; Von Kohorn, Isabelle; Schulman-Green, Dena; Colson, Eve R

2012-08-01

While up to 45% of women quit smoking during pregnancy, nearly 80% return to smoking within a year after delivery. Interventions to prevent relapse have had limited success. The study objective was to understand what influences return to smoking after pregnancy among women who quit smoking during pregnancy, with a focus on the role of social networks. We conducted in-depth, semi-structured interviews during the postpartum hospital stay with women who quit smoking while pregnant. Over 300 pages of transcripts were analyzed using qualitative methods to identify common themes. Respondents [n = 24] were predominately white (63%), had at least some college education (54%) and a mean age of 26 years (range = 18-36). When reflecting on the experience of being a smoker who quit smoking during pregnancy, all participants emphasized the importance of their relationships with other smokers and the changes in these relationships that ensued once they quit smoking. Three common themes were: (1) being enmeshed in social networks with prominent smoking norms (2) being tempted to smoke by members of their social networks, and (3) changing relationships with the smokers in their social networks as a result of their non-smoking status. We found that women who quit smoking during pregnancy found themselves confronted by a change in their social network since most of those in their social network were smokers. For this reason, smoking cessation interventions may be most successful if they help women consider restructuring or reframing their social network.

Health disparities in Europe’s ageing population: the role of social network

PubMed Central

Olofsson, Jenny; Malmberg, Gunnar

2018-01-01

ABSTRACT Background: Previous research suggests that the social network may play very different roles in relation to health in countries with differing welfare regimes. Objective: The study aimed to assess the interplay between social network, socioeconomic position, and self-rated health (SRH) in European countries. Methods: The study used cross-sectional data on individuals aged 50+ from the fourth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) and includes data from 16 countries. The outcome is poor SRH. All analyses are adjusted for age and stratified by gender. Results: Low satisfaction with the social network was associated with poor SRH among women in all country groups, but predicted poor SRH among males in West/Central and Eastern Europe only. The results from the multivariable analysis showed an increased likelihood of poor SRH among those with relatively lower education, as well as among those with low satisfaction with the social network (women from all country groups and men from Western/Central and Eastern Europe). However, the results from interaction analysis show that poor SRH for those with lower relative position in educational level was greater among those with higher satisfaction with the social network among male and female participants from Northern Europe. The health of individuals who are highly satisfied with their social network is more associated with socioeconomic status in Northern Europe. Conclusions: This study highlights the significance of social network and socioeconomic gradients in health among the elderly in Europe. PMID:29553305

Tracking cohesive subgroups over time in inferred social networks

NASA Astrophysics Data System (ADS)

Chin, Alvin; Chignell, Mark; Wang, Hao

2010-04-01

As a first step in the development of community trackers for large-scale online interaction, this paper shows how cohesive subgroup analysis using the Social Cohesion Analysis of Networks (SCAN; Chin and Chignell 2008) and Data-Intensive Socially Similar Evolving Community Tracker (DISSECT; Chin and Chignell 2010) methods can be applied to the problem of identifying cohesive subgroups and tracking them over time. Three case studies are reported, and the findings are used to evaluate how well the SCAN and DISSECT methods work for different types of data. In the largest of the case studies, variations in temporal cohesiveness are identified across a set of subgroups extracted from the inferred social network. Further modifications to the DISSECT methodology are suggested based on the results obtained. The paper concludes with recommendations concerning further research that would be beneficial in addressing the community tracking problem for online data.

Weighted social networks for a large scale artificial society

NASA Astrophysics Data System (ADS)

Fan, Zong Chen; Duan, Wei; Zhang, Peng; Qiu, Xiao Gang

2016-12-01

The method of artificial society has provided a powerful way to study and explain how individual behaviors at micro level give rise to the emergence of global social phenomenon. It also creates the need for an appropriate representation of social structure which usually has a significant influence on human behaviors. It has been widely acknowledged that social networks are the main paradigm to describe social structure and reflect social relationships within a population. To generate social networks for a population of interest, considering physical distance and social distance among people, we propose a generation model of social networks for a large-scale artificial society based on human choice behavior theory under the principle of random utility maximization. As a premise, we first build an artificial society through constructing a synthetic population with a series of attributes in line with the statistical (census) data for Beijing. Then the generation model is applied to assign social relationships to each individual in the synthetic population. Compared with previous empirical findings, the results show that our model can reproduce the general characteristics of social networks, such as high clustering coefficient, significant community structure and small-world property. Our model can also be extended to a larger social micro-simulation as an input initial. It will facilitate to research and predict some social phenomenon or issues, for example, epidemic transition and rumor spreading.

Advantages of Social Network Analysis in Educational Research

ERIC Educational Resources Information Center

Ushakov, K. M.; Kukso, K. N.

2015-01-01

Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…

Impacts of Social Network on Therapeutic Community Participation: A Follow-up Survey of Data Gathered after Ya'an Earthquake.

PubMed

Li, Zhichao; Chen, Yao; Suo, Liming

2015-01-01

In recent years, natural disasters and the accompanying health risks have become more frequent, and rehabilitation work has become an important part of government performance. On one hand, social networks play an important role in participants' therapeutic community participation and physical & mental recovery. On the other hand, therapeutic communities with widespread participation can also contribute to community recovery after disaster. This paper described a field study in an earthquake-stricken area of Ya'an. A set of 3-stage follow-up data was obtained concerning with the villagers' participation in therapeutic community, social network status, demographic background, and other factors. The Hierarchical linear Model (HLM) method was used to investigate the determinants of social network on therapeutic community participation. First, social networks have significantly impacts on the annual changes of therapeutic community participation. Second, there were obvious differences in education between groups mobilized by the self-organization and local government. However, they all exerted the mobilization force through the acquaintance networks. Third, local cadre networks of villagers could negatively influence the activities of self-organized therapeutic community, while with positively influence in government-organized therapeutic activities. This paper suggests that relevant government departments need to focus more on the reconstruction and cultivation of villagers' social network and social capital in the process of post-disaster recovery. These findings contribute to better understandings of how social networks influence therapeutic community participation, and what role local government can play in post-disaster recovery and public health improvement after natural disasters.

Contingent association between the size of the social support network and osteoporosis among Korean elderly women

PubMed Central

Seo, Da Hea; Kim, Kyoung Min; Lee, Eun Young; Kim, Hyeon Chang; Kim, Chang Oh; Youm, Yoosik; Rhee, Yumie

2017-01-01

Objective To investigate the association between the number of personal ties (or the size of the social support network) and the incidence of osteoporosis among older women in Korea. Methods Data from the Korean Urban Rural Elderly Study were used. Bone density was measured by dual-energy X-ray absorptiometry at the lumbar spine (L1–L4) and femur neck. T-score, the standardized bone density compared with what is normally expected in a healthy young adult, was measured and the presence of osteoporosis was determined, if the T-score was < -2.5. The social support network size was measured by self-responses (number of confidants and spouse). Results Of the 1,846 participants, 44.9% were diagnosed with osteoporosis. The association between the social support network size and the incidence of osteoporosis was curvilinear in both bivariate and multivariate analyses. Having more people in one’s social support network size was associated with lower risk of osteoporosis until it reached around four. Increasing the social support network size beyond four, in contrast, was associated with a higher risk of osteoporosis. This association was contingent on the average intimacy level of the social network. At the highest average intimacy level (“extremely close”), increasing the number of social support network members from one to six was associated with linear decrease in the predicted probability of osteoporosis from 45% to 30%. However, at the lowest average intimacy level (“not very close”), the predicted probability of osteoporosis dramatically increased from 48% to 80% as the size of the social network increased from one to six. Conclusion Our results show that maintaining a large and intimate social support network is associated with a lower risk of osteoporosis among elderly Korean women, while a large but less-intimate social relationship is associated with a higher risk. PMID:28700637

Considerations for Public Health Organizations Attempting to Implement a Social Media Presence: A Qualitative Study.

PubMed

Hart, Mark; Stetten, Nichole; Castaneda, Gail

2016-01-01

In the past decade, social media has become an integral part of our everyday lives, but research on how this tool is used by public health workers and organizations is still developing. Budget cuts and staff reduction in county departments have required employees to take on more responsibilities. These reductions have caused a reduction in the time for training or collaborating with others in the field. To make up for the loss, many employees are seeking collaboration through social media sites but are unable to do so because state departments block these Internet sites. This study sought to highlight the key considerations and decision-making process for a public health organization deciding whether to implement a social media presence for their organization. Using 3 structured interviews, 15 stakeholders were questioned on their personal experience with social media, experience within the context of public health, and their thoughts on implementation for their center. Interviews were coded using constant comparative qualitative methods. The following themes emerged from the interviews: (1) personal experience with technology and social networking sites, (2) use of social networking sites in public health, (3) use of social networking sites in work environments, (4) social networking sites access, (5) ways the Rural South Public Health Training Center could use social networking sites, and (6) perceived outcomes of social networking site usage for the Rural South Public Health Training Center (positive and negative). The collective voice of the center showed a positive perceived perception of social media implementation, with the benefits outweighing the risks. Despite the benefits, there is a cautious skepticism of the importance of social networking site use.

Social Representations of Hero and Everyday Hero: A Network Study from Representative Samples

PubMed Central

Keczer, Zsolt; File, Bálint; Orosz, Gábor; Zimbardo, Philip G.

2016-01-01

The psychological investigation of heroism is relatively new. At this stage, inductive methods can shed light on its main aspects. Therefore, we examined the social representations of Hero and Everyday Hero by collecting word associations from two separate representative samples in Hungary. We constructed two networks from these word associations. The results show that the social representation of Hero is more centralized and it cannot be divided into smaller units. The network of Everyday Hero is divided into five units and the significance moves from abstract hero characteristics to concrete social roles and occupations exhibiting pro-social values. We also created networks from the common associations of Hero and Everyday Hero. The structures of these networks show a moderate similarity and the connections are more balanced in case of Everyday Hero. While heroism in general can be the source of inspiration, the promotion of everyday heroism can be more successful in encouraging ordinary people to recognize their own potential for heroic behavior. PMID:27525418

The Role of Meaning in Life for the Quality of Life of Community-Dwelling Chinese Elders With Low Socioeconomic Status

PubMed Central

2018-01-01

Objectives: There is limited research on the meaning in life among Chinese elders. This study aims to examine the association among functional disabilities, meaning in life, social network, and quality of life in community-dwelling Chinese elders with low socioeconomic status. Methods: A cross-sectional survey was used to collect data from 339 poor community-dwelling Chinese elders aged 60 and above. Results: The results showed that meaning in life and social network were significantly related to quality of life. Moreover, social network was a mediator to the relationship between functional disability and quality of life, and meaning in life was a partial mediator to the relationship between social network and quality of life. Conclusion: Workshops should be organized by the elderly service providers for Chinese elders facing deterioration in health and activity levels to learn to live intentionally and purposefully. A social network among elders should also be fostered in the community. PMID:29780856

A comparative analysis of the statistical properties of large mobile phone calling networks.

PubMed

Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

2014-05-30

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

Social representations of electricity network technologies: exploring processes of anchoring and objectification through the use of visual research methods.

PubMed

Devine-Wright, Hannah; Devine-Wright, Patrick

2009-06-01

The aim of this study was to explore everyday thinking about the UK electricity network, in light of government policy to increase the generation of electricity from renewable energy sources. Existing literature on public perceptions of electricity network technologies was broadened by adopting a more socially embedded conception of the construction of knowledge using the theory of social representations (SRT) to explore symbolic associations with network technologies. Drawing and association tasks were administered within nine discussion groups held in two places: a Scottish town where significant upgrades to the local transmission network were planned and an English city with no such plans. Our results illustrate the ways in which network technologies, such as high voltage (HV) pylons, are objectified in talk and drawings. These invoked positive as well as negative symbolic and affective associations, both at the level of specific pylons, and the 'National Grid' as a whole and are anchored in understanding of other networks such as mobile telecommunications. We conclude that visual methods are especially useful for exploring beliefs about technologies that are widespread, proximal to our everyday experience but nevertheless unfamiliar topics of everyday conversation.

The role of social support and social networks in smoking behavior among middle and older aged people in rural areas of South Korea: A cross-sectional study

PubMed Central

2010-01-01

Background Although the number of studies on anti-smoking interventions has increased, studies focused on identifying social contextual factors in rural areas are scarce. The purpose of this study was to explore the role of social support and social networks in smoking behavior among middle and older aged people living in rural areas of South Korea. Methods The study employed a cross-sectional design. Participants included 1,057 adults, with a mean age of 60.7 years, residing in rural areas. Information on participants' tobacco use, stress, social support, and social networks was collected using structured questionnaires. The chi-square test, the t-test, ANOVA, and logistic regression were used for data analysis. Results The overall smoking prevalence in the study was 17.4% (men, 38.8%; women, 5.1%). Overall, stress was high among women, and social support was high among men. Smokers had high levels of social support (t = -2.90, p = .0038) and social networks (t = -2.22, p = .0271), as compared to non- and former smokers. Those in the high social support group were likely to be smokers (AOR = 2.21, 95% CI 1.15-4.26). Women with moderate social ties were less likely to smoke (AOR = 0.18, 95% CI 0.05-0.61). Conclusion There was a protective role of a moderate social network level among women, and a high level of social support was associated with smoking behaviors in rural areas. Findings suggest the need for a comprehensive understanding of the functions and characteristics of social contextual factors including social support and social networks in order to conduct more effective anti-smoking interventions in rural areas. PMID:20167103

Health Status and Social Networks as Predictors of Resilience in Older Adults Residing in Rural and Remote Environments

PubMed Central

Lee, Aaron; Carrico, Catherine; Bourassa, Katelynn; Slosser, Andrea

2016-01-01

Purpose. Health status and social networks are associated with resilience among older adults. Each of these factors may be important to the ability of adults to remain in rural and remote communities as they age. We examined the association of health status and social networks and resilience among older adults dwelling in a rural and remote county in the Western United States. Methods. We selected a random sample of 198 registered voters aged 65 years or older from a frontier Wyoming county. Hierarchical linear regression was used to examine the association of health status as well as social networks and resilience. We also examined health status as a moderator of the relationship between social networks and resilience. Results. Family networks (p = 0.024) and mental health status (p < 0.001) significantly predicted resilience. Mental health status moderated the relationship of family (p = 0.004) and friend (p = 0.021) networks with resilience. Smaller family and friend networks were associated with greater resilience when mental health status was low, but not when it was high. Conclusion. Efforts to increase mental health status may improve resilience among older adults in rural environments, particularly for those with smaller family and friends networks. PMID:27478639

A Systematic Review of Research on Social Networks of Older Adults.

PubMed

Ayalon, Liat; Levkovich, Inbar

2018-01-29

There has been a substantial interest in life course/life span changes in older adults' social networks and in the relationship between social networks and health and wellbeing. The study embarked on a systematic review to examine the existing knowledgebase on social network in the field of gerontology. Our focus was on studies in which both ego (respondents) and his or her alters (network members) are queried about their social ties. We searched for studies published in English before September, 2017, relied on quantitative methods to obtain data from both ego (60 years of age and older) and alters and provided a quantitative account of the social network properties. We searched the following data sets: APA Psychnet, Pubmed, Sociological abstracts, and Ageline. This was followed by a snowball search of relevant articles using Google Scholar. Titles and abstracts were reviewed and selected articles were extracted independently by two reviewers. A total of 5,519 records were retrieved. Of these, 3,994 records remained after the removal of duplicates. Ten records reporting on five original samples were kept for the systematic review. One study described a social network of community dwelling older adults and the remaining studies described social networks of institutional older adults. The present study points to a lacuna in current understanding of social networks in the field of gerontology. It provides a useful review and possible tools for the design of future studies to address current shortcomings in the field. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Influence of the social network on consumption in drug addicts exhibiting psychiatric comorbidity].

PubMed

Acier, D; Nadeau, L; Landry, M

2011-09-01

This research used a qualitative methodology and was conducted on a sample of 22 participants with concomitant substance-related and mental health disorders. Today, dual diagnosis patients represent the standard rather than the exception. Our objectives were to consider the elements and processes of the social network to explain variations in consumption of alcohol and drugs. The social network refers to all bonds established by patients, mainly family, couple, friends and therapist relationships. The 22 patients have used a specialized addiction treatment in Montreal (Canada). A focused qualitative interview was conducted with each participant using an audionumeric recording. The analysis follows the method of the mixed approach of Miles and Huberman, which combines the objectives of the grounded theory and the ethnography. All the interviews were transcribed then coded and analyzed with QSR N' Vivo 2.0. The method uses an iterative process making a constant return between verbatim and codes. The qualitative analyses present patients' perceptions on the increases and reductions in alcohol and drug consumption. Family network refers to participants where the family is named as supporting a decrease in drug consumption: couple network refers to intimate relations supporting a decrease in consumption. Mutual help network refers to alcoholics anonymous (AA) or other self-help groups. Several verbatim have been included. We propose strategies for the substance abuse treatment centers based on: (1) the paradox influence of the social network and the importance of clinical evaluation of patients of social networks; (2) emotions management, especially negative feelings, which include training of feeling, recognizing and naming, ability to the express and communicate to others; (3) importance of groups of mutual aid providing periods of sharing, validating individual experiences and pushing away loneliness; (4) function of social support of the clinical professionals as substitute of an overdrawn network. Copyright © 2011. Published by Elsevier Masson SAS.

A decentralized approach to reducing the social costs of cascading failures

NASA Astrophysics Data System (ADS)

Hines, Paul

Large cascading failures in electrical power networks come with enormous social costs. These can be direct financial costs, such as the loss of refrigerated foods in grocery stores, or more indirect social costs, such as the traffic congestion that results from the failure of traffic signals. While engineers and policy makers have made numerous technical and organizational changes to reduce the frequency and impact of large cascading failures, the existing data, as described in Chapter 2 of this work, indicate that the overall frequency and impact of large electrical blackouts in the United States are not decreasing. Motivated by the cascading failure problem, this thesis describes a new method for Distributed Model Predictive Control and a power systems application. The central goal of the method, when applied to power systems, is to reduce the social costs of cascading failures by making small, targeted reductions in load and generation and changes to generator voltage set points. Unlike some existing schemes that operate from centrally located control centers, the method is operated by software agents located at substations distributed throughout the power network. The resulting multi-agent control system is a new approach to decentralized control, combining Distributed Model Predictive Control and Reciprocal Altruism. Experimental results indicate that this scheme can in fact decrease the average size, and thus social costs, of cascading failures. Over 100 randomly generated disturbances to a model of the IEEE 300 bus test network, the method resulted in nearly an order of magnitude decrease in average event size (measured in cost) relative to cascading failure simulations without remedial control actions. Additionally, the communication requirements for the method are measured, and found to be within the bandwidth capabilities of current communications technology (on the order of 100kB/second). Experiments on several resistor networks with varying structures, including a random graph, a scale-free network and a power grid indicate that the effectiveness of decentralized control schemes, like the method proposed here, is a function of the structure of the network that is to be controlled.

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

Use of a mobile social networking intervention for weight management: a mixed-methods study protocol

PubMed Central

Lau, Annie Y S; Martin, Paige; Tong, Huong Ly; Coiera, Enrico

2017-01-01

Introduction Obesity and physical inactivity are major societal challenges and significant contributors to the global burden of disease and healthcare costs. Information and communication technologies are increasingly being used in interventions to promote behaviour change in diet and physical activity. In particular, social networking platforms seem promising for the delivery of weight control interventions. We intend to pilot test an intervention involving the use of a social networking mobile application and tracking devices (Fitbit Flex 2 and Fitbit Aria scale) to promote the social comparison of weight and physical activity, in order to evaluate whether mechanisms of social influence lead to changes in those outcomes over the course of the study. Methods and analysis Mixed-methods study involving semi-structured interviews and a pre–post quasi-experimental pilot with one arm, where healthy participants in different body mass index (BMI) categories, aged between 19 and 35 years old, will be subjected to a social networking intervention over a 6-month period. The primary outcome is the average difference in weight before and after the intervention. Secondary outcomes include BMI, number of steps per day, engagement with the intervention, social support and system usability. Semi-structured interviews will assess participants’ expectations and perceptions regarding the intervention. Ethics and dissemination Ethics approval was granted by Macquarie University’s Human Research Ethics Committee for Medical Sciences on 3 November 2016 (ethics reference number 5201600716). The social network will be moderated by a researcher with clinical expertise, who will monitor and respond to concerns raised by participants. Monitoring will involve daily observation of measures collected by the fitness tracker and the wireless scale, as well as continuous supervision of forum interactions and posts. Additionally, a protocol is in place to monitor for participant misbehaviour and direct participants-in-need to appropriate sources of help. PMID:28706104

Exploratory community sensing in social networks

NASA Astrophysics Data System (ADS)

Khrabrov, Alexy; Stocco, Gabriel; Cybenko, George

2010-04-01

Social networks generally provide an implementation of some kind of groups or communities which users can voluntarily join. Twitter does not have this functionality, and there is no notion of a formal group or community. We propose a method for identification of communities and assignment of semantic meaning to the discussion topics of the resulting communities. Using this analysis method and a sample of roughly a month's worth of Tweets from Twitter's "gardenhose" feed, we demonstrate the discovery of meaningful user communities on Twitter. We examine Twitter data streaming in real time and treat it as a sensor. Twitter is a social network which pioneered microblogging with the messages fitting an SMS, and a variety of clients, browsers, smart phones and PDAs are used for status updates by individuals, businesses, media outlets and even devices all over the world. Often an aggregate trend of such statuses may represent an important development in the world, which has been demonstrated with the Iran and Moldova elections and the anniversary of the Tiananmen in China. We propose using Twitter as a sensor, tracking individuals and communities of interest, and characterizing individual roles and dynamics of their communications. We developed a novel algorithm of community identification in social networks based on direct communication, as opposed to linking. We show ways to find communities of interest and then browse their neighborhoods by either similarity or diversity of individuals and groups adjacent to the one of interest. We use frequent collocations and statistically improbable phrases to summarize the focus of the community, giving a quick overview of its main topics. Our methods provide insight into the largest social sensor network in the world and constitute a platform for social sensing.

Online social networking amongst teens: friend or foe?

PubMed

O'Dea, Bridianne; Campbell, Andrew

2011-01-01

The impact of Internet communication on adolescent social development is of considerable importance to health professionals, parents and teachers. Online social networking and instant messaging programs are popular utilities amongst a generation of techno-savvy youth. Although these utilities provide varied methods of communication, their social benefits are still in question. This study examined the relationship between online social interaction, perceived social support, self-esteem and psychological distress amongst teens. A total of 400 participants (M(age) = 14.31 years) completed an online survey consisting of parametric and non-parametric measures. No significant relationship was found between online interaction and social support. Time spent interacting online was negatively correlated with self-esteem and psychological distress. While previous research has focused on young adults, this study examines the impact of online social networking on emerging teens. It highlights the need for continued caution in the acceptance of these utilities.

An incremental community detection method for social tagging systems using locality-sensitive hashing.

PubMed

Wu, Zhenyu; Zou, Ming

2014-10-01

An increasing number of users interact, collaborate, and share information through social networks. Unprecedented growth in social networks is generating a significant amount of unstructured social data. From such data, distilling communities where users have common interests and tracking variations of users' interests over time are important research tracks in fields such as opinion mining, trend prediction, and personalized services. However, these tasks are extremely difficult considering the highly dynamic characteristics of the data. Existing community detection methods are time consuming, making it difficult to process data in real time. In this paper, dynamic unstructured data is modeled as a stream. Tag assignments stream clustering (TASC), an incremental scalable community detection method, is proposed based on locality-sensitive hashing. Both tags and latent interactions among users are incorporated in the method. In our experiments, the social dynamic behaviors of users are first analyzed. The proposed TASC method is then compared with state-of-the-art clustering methods such as StreamKmeans and incremental k-clique; results indicate that TASC can detect communities more efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model

PubMed Central

2013-01-01

Background High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. Methods/Design A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants’ online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Discussion Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. Trial registration ClinicalTrials.gov NCT01142804 PMID:23945138

Social Networking Sites: An Adjunctive Treatment Modality for Psychological Problems

PubMed Central

Menon, Indu S.; Sharma, Manoj Kumar; Chandra, Prabha S.; Thennarasu, K.

2014-01-01

Background: Social networking is seen as a way to enhance social support and feeling of well-being. The present work explores the potentials of social networking sites as an adjunctive treatment modality for initiating treatment contact as well as for managing psychological problems. Materials and Methods: Interview schedule, Facebook intensity questionnaire were administered on 28 subjects with a combination of 18 males and 10 females. They were taken from the in-patient and out-patient psychiatry setting of the hospital. Results: Facebook was the most popular sites and used to seek emotional support on the basis of the frequent updates of emotional content that users put in their profile; reconciliations, escape from the problems or to manage the loneliness; getting information about illness and its treatment and interaction with experts and also manifested as problematic use. Conclusions: It has implications for developing social networking based adjunctive treatment modality for psychological problems. PMID:25035548

The role of social networks in the development of overweight and obesity among adults: a scoping review.

PubMed

Powell, Katie; Wilcox, John; Clonan, Angie; Bissell, Paul; Preston, Louise; Peacock, Marian; Holdsworth, Michelle

2015-09-30

Although it is increasingly acknowledged that social networks are important to our understanding ofoverweight and obesity, there is limited understanding about the processes by which such networks shapetheir progression. This paper reports the findings of a scoping review of the literature that sought to identify the key processes through which social networks are understood to influence the development of overweight and obesity. A scoping review was conducted. Forty five papers were included in the final review, the findings of which were synthesised to provide an overview of the main processes through which networks have been understood to influence the development of overweight and obesity. Included papers addressed a wide range of research questions framed around six types of networks: a paired network (one's spouse or intimate partner); friends and family (including work colleagues and people within social clubs); ephemeral networks in shared public spaces (such as fellow shoppers in a supermarket or diners in a restaurant); people living within the same geographical region; peers (including co-workers, fellow students, fellow participants in a weight loss programme); and cultural groups (often related toethnicity). As individuals are embedded in many of these different types of social networks at any one time, the pathways of influence from social networks to the development of patterns of overweight and obesity are likely to be complex and interrelated. Included papers addressed a diverse set of issues: body weight trends over time; body size norms or preferences; weight loss and management; physical activity patterns; and dietary patterns. Three inter-related processes were identified: social contagion (whereby the network in which people are embedded influences their weight or weight influencing behaviours), social capital (whereby sense of belonging and social support influence weight or weight influencing behaviours), and social selection (whereby a person's network might develop according to his or her weight). The findings have important implications for understanding about methods to target the spread of obesity, indicating that much greater attention needs to be paid to the social context in which people make decisions about their weight and weight influencing behaviours.

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Bibliometrics for Social Validation.

PubMed

Hicks, Daniel J

2016-01-01

This paper introduces a bibliometric, citation network-based method for assessing the social validation of novel research, and applies this method to the development of high-throughput toxicology research at the US Environmental Protection Agency. Social validation refers to the acceptance of novel research methods by a relevant scientific community; it is formally independent of the technical validation of methods, and is frequently studied in history, philosophy, and social studies of science using qualitative methods. The quantitative methods introduced here find that high-throughput toxicology methods are spread throughout a large and well-connected research community, which suggests high social validation. Further assessment of social validation involving mixed qualitative and quantitative methods are discussed in the conclusion.

Bibliometrics for Social Validation

PubMed Central

2016-01-01

This paper introduces a bibliometric, citation network-based method for assessing the social validation of novel research, and applies this method to the development of high-throughput toxicology research at the US Environmental Protection Agency. Social validation refers to the acceptance of novel research methods by a relevant scientific community; it is formally independent of the technical validation of methods, and is frequently studied in history, philosophy, and social studies of science using qualitative methods. The quantitative methods introduced here find that high-throughput toxicology methods are spread throughout a large and well-connected research community, which suggests high social validation. Further assessment of social validation involving mixed qualitative and quantitative methods are discussed in the conclusion. PMID:28005974

The Peer Social Networks of Young Children with Down Syndrome in Classroom Programmes

ERIC Educational Resources Information Center

Guralnick, Michael J.; Connor, Robert T.; Johnson, L. Clark

2011-01-01

Background: The nature and characteristics of the peer social networks of young children with Down syndrome (DS) in classroom settings were examined within a developmental framework. Method: Comparisons were made with younger typically developing children matched on mental age and typically developing children matched on chronological age.…

Collaboration Levels in Asynchronous Discussion Forums: A Social Network Analysis Approach

ERIC Educational Resources Information Center

Luhrs, Cecilia; McAnally-Salas, Lewis

2016-01-01

Computer Supported Collaborative Learning literature relates high levels of collaboration to enhanced learning outcomes. However, an agreement on what is considered a high level of collaboration is unclear, especially if a qualitative approach is taken. This study describes how methods of Social Network Analysis were used to design a collaboration…

Shaping Social Activity by Incentivizing Users

PubMed Central

Farajtabar, Mehrdad; Du, Nan; Rodriguez, Manuel Gomez; Valera, Isabel; Zha, Hongyuan; Song, Le

2015-01-01

Events in an online social network can be categorized roughly into endogenous events, where users just respond to the actions of their neighbors within the network, or exogenous events, where users take actions due to drives external to the network. How much external drive should be provided to each user, such that the network activity can be steered towards a target state? In this paper, we model social events using multivariate Hawkes processes, which can capture both endogenous and exogenous event intensities, and derive a time dependent linear relation between the intensity of exogenous events and the overall network activity. Exploiting this connection, we develop a convex optimization framework for determining the required level of external drive in order for the network to reach a desired activity level. We experimented with event data gathered from Twitter, and show that our method can steer the activity of the network more accurately than alternatives. PMID:26005312

Multimedia Information Networks in Social Media

NASA Astrophysics Data System (ADS)

Cao, Liangliang; Qi, Guojun; Tsai, Shen-Fu; Tsai, Min-Hsuan; Pozo, Andrey Del; Huang, Thomas S.; Zhang, Xuemei; Lim, Suk Hwan

The popularity of personal digital cameras and online photo/video sharing community has lead to an explosion of multimedia information. Unlike traditional multimedia data, many new multimedia datasets are organized in a structural way, incorporating rich information such as semantic ontology, social interaction, community media, geographical maps, in addition to the multimedia contents by themselves. Studies of such structured multimedia data have resulted in a new research area, which is referred to as Multimedia Information Networks. Multimedia information networks are closely related to social networks, but especially focus on understanding the topics and semantics of the multimedia files in the context of network structure. This chapter reviews different categories of recent systems related to multimedia information networks, summarizes the popular inference methods used in recent works, and discusses the applications related to multimedia information networks. We also discuss a wide range of topics including public datasets, related industrial systems, and potential future research directions in this field.

A snapshot of how Latino heterosexual men promote sexual health within their social networks: Process evaluation findings from an efficacious community-level intervention

PubMed Central

Rhodes, Scott D.; Daniel, Jason; Alonzo, Jorge; Vissman, Aaron T.; Duck, Stacy; Downs, Mario; Gilbert, Paul A.

2014-01-01

Background HoMBReS was a community-level social network intervention designed to increase sexual health among Latino heterosexual men who were members of a multi-county soccer league. Methods We used process data collected each month during 18 months of intervention implementation from each of 15 trained Latino male lay health advisors (known as Navegantes) to explore the activities that Navegantes conducted to increase condom and HIV testing among their social network members. Results The Navegantes reported conducting 2,364 activities, for a mean of 8.8 activities per Navegante per month. The most common activity was condom distribution. Most activities were conducted with men; about 2% were conducted with women. Among activities conducted with men, half were conducted with soccer teammates and half with non-teammates. Conclusions Latino men’s social networks can be leveraged to promote sexual health within the community. Innovative methods that reach large numbers of community members are needed given the lack of prevention resources for populations disproportionately impacted by HIV and STDs. PMID:23206201

Discovering Central Practitioners in a Medical Discussion Forum Using Semantic Web Analytics.

PubMed

Rajabi, Enayat; Abidi, Syed Sibte Raza

2017-01-01

The aim of this paper is to investigate semantic web based methods to enrich and transform a medical discussion forum in order to perform semantics-driven social network analysis. We use the centrality measures as well as semantic similarity metrics to identify the most influential practitioners within a discussion forum. The centrality results of our approach are in line with centrality measures produced by traditional SNA methods, thus validating the applicability of semantic web based methods for SNA, particularly for analyzing social networks for specialized discussion forums.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

PubMed

So, Nina; Franks, Becca; Lim, Sean; Curley, James P

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

PubMed Central

So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels. PMID:26226265

A review of influenza detection and prediction through social networking sites.

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

The relationship between social desirability bias and self-reports of health, substance use, and social network factors among urban substance users in Baltimore, Maryland.

PubMed

Latkin, Carl A; Edwards, Catie; Davey-Rothwell, Melissa A; Tobin, Karin E

2017-10-01

Social desirability response bias may lead to inaccurate self-reports and erroneous study conclusions. The present study examined the relationship between social desirability response bias and self-reports of mental health, substance use, and social network factors among a community sample of inner-city substance users. The study was conducted in a sample of 591 opiate and cocaine users in Baltimore, Maryland from 2009 to 2013. Modified items from the Marlowe-Crowne Social Desirability Scale were included in the survey, which was conducted face-to-face and using Audio Computer Self Administering Interview (ACASI) methods. There were highly statistically significant differences in levels of social desirability response bias by levels of depressive symptoms, drug use stigma, physical health status, recent opiate and cocaine use, Alcohol Use Disorders Identification Test (AUDIT) scores, and size of social networks. There were no associations between health service utilization measures and social desirability bias. In multiple logistic regression models, even after including the Center for Epidemiologic Studies Depression Scale (CES-D) as a measure of depressive symptomology, social desirability bias was associated with recent drug use and drug user stigma. Social desirability bias was not associated with enrollment in prior research studies. These findings suggest that social desirability bias is associated with key health measures and that the associations are not primarily due to depressive symptoms. Methods are needed to reduce social desirability bias. Such methods may include the wording and prefacing of questions, clearly defining the role of "study participant," and assessing and addressing motivations for socially desirable responses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of the Social Network-Based Intervention “Powerful Together with Diabetes” Using Intervention Mapping

PubMed Central

Vissenberg, Charlotte; Nierkens, Vera; Uitewaal, Paul J. M.; Middelkoop, Barend J. C.; Nijpels, Giel; Stronks, Karien

2017-01-01

This article describes the development of the social network-based intervention Powerful Together with Diabetes which aims to improve diabetes self-management (DSM) among patients with type 2 diabetes living in socioeconomically deprived neighborhoods by stimulating social support for DSM and diminishing social influences hindering DSM (e.g., peer pressure and social norms). The intervention was specifically developed for patients with Dutch, Turkish, Moroccan, and Surinamese backgrounds. The intervention was developed according to Intervention Mapping. This article describes the first four steps of Intervention Mapping: (1) the needs assessment; (2) development of performance and change objectives; (3) selection of theory-based methods and strategies; and (4) the translation of these into an organized program. These four steps resulted in Powerful Together with Diabetes, a 10-month group-based intervention consisting of 24 meetings, 6 meetings for significant others, and 2 meetings for participants and their spouses. The IM method resulted in a tailored approach with a specific focus on the social networks of its participants. This article concludes that the IM method helped our planning team to tailor the intervention to the needs of our target population and facilitated our evaluation design. However, in hindsight, the intervention could have been improved by investing more in participatory planning and community involvement. PMID:29326916

Development of the Social Network-Based Intervention "Powerful Together with Diabetes" Using Intervention Mapping.

PubMed

Vissenberg, Charlotte; Nierkens, Vera; Uitewaal, Paul J M; Middelkoop, Barend J C; Nijpels, Giel; Stronks, Karien

2017-01-01

This article describes the development of the social network-based intervention Powerful Together with Diabetes which aims to improve diabetes self-management (DSM) among patients with type 2 diabetes living in socioeconomically deprived neighborhoods by stimulating social support for DSM and diminishing social influences hindering DSM (e.g., peer pressure and social norms). The intervention was specifically developed for patients with Dutch, Turkish, Moroccan, and Surinamese backgrounds. The intervention was developed according to Intervention Mapping. This article describes the first four steps of Intervention Mapping: (1) the needs assessment; (2) development of performance and change objectives; (3) selection of theory-based methods and strategies; and (4) the translation of these into an organized program. These four steps resulted in Powerful Together with Diabetes , a 10-month group-based intervention consisting of 24 meetings, 6 meetings for significant others, and 2 meetings for participants and their spouses. The IM method resulted in a tailored approach with a specific focus on the social networks of its participants. This article concludes that the IM method helped our planning team to tailor the intervention to the needs of our target population and facilitated our evaluation design. However, in hindsight, the intervention could have been improved by investing more in participatory planning and community involvement.

Large Scale Data Analysis and Knowledge Extraction in Communication Data

DTIC Science & Technology

2017-03-31

this purpose, we developed a novel method the " Correlation Density Ran!C’ which finds probability density distribution of related frequent event on all...which is called " Correlation Density Rank", is developed to derive the community tree from the network. As in the real world, where a network is...Community Structure in Dynamic Social Networks using the Correlation Density Rank," 2014 ASE BigData/SocialCom/Cybersecurity Conference, Stanford

Exploring the potential of expatriate social networks to reduce HIV and STI transmission: a protocol for a qualitative study

PubMed Central

Crawford, Gemma; Bowser, Nicole Jasmine; Brown, Graham Ernest; Maycock, Bruce Richard

2013-01-01

Introduction HIV diagnoses acquired among Australian men working or travelling overseas including  Southeast Asia are increasing. This change within transmission dynamics means traditional approaches to prevention need to be considered in new contexts. The significance and role of social networks in mediating sexual risk behaviours may be influential. Greater understanding of expatriate and traveller behaviour is required to understand how local relationships are formed, how individuals enter and are socialised into networks, and how these networks may affect sexual intentions and behaviours. This paper describes the development of a qualitative protocol to investigate how social networks of Australian expatriates and long-term travellers might support interventions to reduce transmission of HIV and sexually transmitted infections. Methods and analysis To explore the interactions of male expatriates and long-term travellers within and between their environments, symbolic interactionism will be the theoretical framework used. Grounded theory methods provide the ability to explain social processes through the development of explanatory theory. The primary data source will be interviews conducted in several rounds in both Australia and Southeast Asia. Purposive and theoretical sampling will be used to access participants whose data can provide depth and individual meaning. Ethics and dissemination The role of expatriate and long-term traveller networks and their potential to impact health are uncertain. This study seeks to gain a deeper understanding of the Australian expatriate culture, behavioural contexts and experiences within social networks in  Southeast Asia. This research will provide tangible recommendations for policy and practice as the findings will be disseminated to health professionals and other stakeholders, academics and the community via local research and evaluation networks, conference presentations and online forums. The Curtin University Human Research Ethics Committee has granted approval for this research. PMID:23444449

Using Social Networking to Understand Social Networks: Analysis of a Mobile Phone Closed User Group Used by a Ghanaian Health Team

PubMed Central

Akosah, Eric; Ohemeng-Dapaah, Seth; Sakyi Baah, Joseph; Kanter, Andrew S

2013-01-01

Background The network structure of an organization influences how well or poorly an organization communicates and manages its resources. In the Millennium Villages Project site in Bonsaaso, Ghana, a mobile phone closed user group has been introduced for use by the Bonsaaso Millennium Villages Project Health Team and other key individuals. No assessment on the benefits or barriers of the use of the closed user group had been carried out. Objective The purpose of this research was to make the case for the use of social network analysis methods to be applied in health systems research—specifically related to mobile health. Methods This study used mobile phone voice records of, conducted interviews with, and reviewed call journals kept by a mobile phone closed user group consisting of the Bonsaaso Millennium Villages Project Health Team. Social network analysis methodology complemented by a qualitative component was used. Monthly voice data of the closed user group from Airtel Bharti Ghana were analyzed using UCINET and visual depictions of the network were created using NetDraw. Interviews and call journals kept by informants were analyzed using NVivo. Results The methodology was successful in helping identify effective organizational structure. Members of the Health Management Team were the more central players in the network, rather than the Community Health Nurses (who might have been expected to be central). Conclusions Social network analysis methodology can be used to determine the most productive structure for an organization or team, identify gaps in communication, identify key actors with greatest influence, and more. In conclusion, this methodology can be a useful analytical tool, especially in the context of mobile health, health services, and operational and managerial research. PMID:23552721

The role of social networks in the governance of health systems: the case of eye care systems in Ghana.

PubMed

Blanchet, Karl; James, Philip

2013-03-01

Efforts have been increasingly invested to improve local health systems' capacities in developing countries. We describe the application of innovative methods based on a social network analysis approach. The findings presented refer to a study carried out between July 2008 and January 2010 in the Brong Ahafo region of Ghana. Social network analysis methods were applied in five different districts using the software package Ucinet to calculate the various properties of the social network of eye care providers. The study focused on the managerial decisions made by Ghanaian district hospital managers about the governance of the health system. The study showed that the health system in the Brong Ahafo region experienced significant changes specifically after a key shock, the departure of an international organization. Several other actors at different levels of the network disappeared, the positions of nurses and hospital managers changed, creating new relationships and power balances that resulted in a change in the general structure of the network. The system shifted from a centralized and dense hierarchical network towards an enclaved network composed of five sub-networks. The new structure was less able to respond to shocks, circulate information and knowledge across scales and implement multi-scale solutions than that which it replaced. Although the network became less resilient, it responded better to the management needs of the hospital managers who now had better access to information, even if this information was partial. The change of the network over time also showed the influence of the international organization on generating links and creating connections between actors from different levels. The findings of the study reveal the importance of creating international health connections between actors working in different spatial scales of the health system.

Medical Mistrust among Social Network Members May Contribute to Antiretroviral Treatment Nonadherence in African Americans Living with HIV

PubMed Central

Bogart, Laura M.; Wagner, Glenn J.; Green, Harold D.; Mutchler, Matt G.; Klein, David J.; McDavitt, Bryce; Lawrence, Sean J.; Hilliard, Charles L.

2016-01-01

Rationale African Americans living with HIV are less likely to adhere to antiretroviral treatment (ART) compared to other racial/ethnic groups. Medical mistrust is thought to be a factor in this disparity. Objective We examined (1) whether exposure to HIV conspiracy beliefs, a specific type of HIV-related mistrust (about the origins and treatment of HIV) in social networks is associated with ART nonadherence among African Americans living with HIV; and (2) the characteristics of individuals who discuss HIV-related mistrust in the social networks of African Americans living with HIV. Methods At baseline and 6- and 12-months post-baseline, 175 African Americans living with HIV on ART completed egocentric social network assessments, from which we assessed the structure and composition of their personal networks (the social context immediately surrounding them). HIV-related mistrust was operationalized with an indicator of whether any social network member had expressed HIV conspiracy beliefs to the participant. Daily medication adherence was monitored electronically. Results At baseline, 63% of participants agreed with at least one conspiracy belief, and 55% reported hearing at least one social network member (“alter”) express conspiracy beliefs. In a multivariate linear repeated measures regression, expression of conspiracy beliefs by similar others in the network (in terms of age, gender, HIV status, sexual orientation, and race/ethnicity) was associated with ART nonadherence (i.e., percentage of prescribed doses taken). In a multivariate logistic regression, expression of conspiracy beliefs was more likely among social network members who were HIV-positive, who knew the participants’ serostatus, and with whom participants interacted frequently, and less likely among more well-connected social network members. Conclusion HIV-related mistrust in the network may be most influential when expressed by similar others who may be HIV-positive themselves. PMID:27046475

Recovering time-varying networks of dependencies in social and biological studies.

PubMed

Ahmed, Amr; Xing, Eric P

2009-07-21

A plausible representation of the relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network that is topologically rewiring and semantically evolving over time. Although there is a rich literature in modeling static or temporally invariant networks, little has been done toward recovering the network structure when the networks are not observable in a dynamic context. In this article, we present a machine learning method called TESLA, which builds on a temporally smoothed l(1)-regularized logistic regression formalism that can be cast as a standard convex-optimization problem and solved efficiently by using generic solvers scalable to large networks. We report promising results on recovering simulated time-varying networks and on reverse engineering the latent sequence of temporally rewiring political and academic social networks from longitudinal data, and the evolving gene networks over >4,000 genes during the life cycle of Drosophila melanogaster from a microarray time course at a resolution limited only by sample frequency.

Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2016-01-01

Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.

Are Maternal Social Networks and Perceptions of Trust Associated with Suspected Autism Spectrum Disorder in Offspring? A Population-Based Study in Japan

PubMed Central

Fujiwara, Takeo; Kawachi, Ichiro

2014-01-01

Objective To investigate the associations of maternal social networks and perceptions of trust with the prevalence of suspected autism spectrum disorders in 18-month-old offspring in Japan. Methods Questionnaires included measurements of maternal social networks (number of relatives or friends they could call upon for assistance), maternal perceptions of trust, mutual assistance (i.e. individual measures of “cognitive social capital”), and social participation (i.e. individual measures of “structural social capital”) as well as the Modified Checklist for Autism in Toddlers to detect suspected autism spectrum disorder (ASD). These tools were mailed to all families with 18-month-old toddlers in Chiba, a city near Tokyo (N = 6061; response rate: 64%). The association between social capital or social network indicators and suspected ASD were analyzed, adjusted for covariates by logistic regression analysis. Results Low maternal social trust was found to be significantly positively associated with suspected ASD in toddlers compared with high maternal social trust (adjusted odds ratio [OR]: 1.82, 95% confidence interval [CI]: 1.38 to 2.40); mutual aid was also significantly positively related (low vs. high: OR, 1.82, 95% CI: 1.38 to 2.40). However, maternal community participation showed U-shape association with suspected ASD of offspring. Maternal social network showed consistent inverse associations with suspected ASD of offspring, regardless of the type of social connection (e.g., relatives, neighbors, or friends living outside of their neighborhood). Conclusions Mothers' cognitive social capital and social networks, but not structural social capital, might be associated with suspected ASD in offspring. PMID:24983630

Positive Impact of Social Media Use on Depression in Cancer Patients

PubMed

Farpour, Hamid Reza; Habibi, Leila; Owji, Seyed Hossein

2017-11-26

Objective: The focus of attention was the prevalence of depression among cancer patients using social networks. An attempt was made to determine if social media could help cancer patients overcome their stress and depression, causes of serious emotional and mental problems for them and their families. Methods: To ascertain the prevalence of depression among cancer patients with reference to use of social networks, 316 cancer patients in the Association of Cancer Patients and cancer-related centers in Tehran at 2015 were evaluated. Depression was measured using the Beck Depression Inventory. Data were analyzed by the Chi-square test with SPSS software. Results: Using the Beck criteria, 61% (N=192) of patients were depressed. Interestingly, a significant difference was observed between depression in users and non-users of social networks (p=0.001), 33.9% and 66.1% being affected, respectively. Conclusion: These results verified a high incidence of depression in cancer patients, but a beneficial effect of social network use. Therefore access to social networks should be promoted for prevention and amelioration of depression. Moreover, it is recommended that particular attention be paid to the patient sex and educational level in designing counseling and psychological skill training programs. Creative Commons Attribution License

Nonlinearity in Social Service Evaluation: A Primer on Agent-Based Modeling

ERIC Educational Resources Information Center

Israel, Nathaniel; Wolf-Branigin, Michael

2011-01-01

Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable evaluators and researchers to simulate complex…

Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management.

PubMed

Kreakie, B J; Hychka, K C; Belaire, J A; Minor, E; Walker, H A

2016-02-01

Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution's web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google's "relatedness" operator that identifies pages "similar" to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago (n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined.

Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management

NASA Astrophysics Data System (ADS)

Kreakie, B. J.; Hychka, K. C.; Belaire, J. A.; Minor, E.; Walker, H. A.

2016-02-01

Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution's web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google's "relatedness" operator that identifies pages "similar" to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago ( n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined.

Selection for territory acquisition is modulated by social network structure in a wild songbird

PubMed Central

Farine, D R; Sheldon, B C

2015-01-01

The social environment may be a key mediator of selection that operates on animals. In many cases, individuals may experience selection not only as a function of their phenotype, but also as a function of the interaction between their phenotype and the phenotypes of the conspecifics they associate with. For example, when animals settle after dispersal, individuals may benefit from arriving early, but, in many cases, these benefits will be affected by the arrival times of other individuals in their local environment. We integrated a recently described method for calculating assortativity on weighted networks, which is the correlation between an individual's phenotype and that of its associates, into an existing framework for measuring the magnitude of social selection operating on phenotypes. We applied this approach to large-scale data on social network structure and the timing of arrival into the breeding area over three years. We found that late-arriving individuals had a reduced probability of breeding. However, the probability of breeding was also influenced by individuals’ social networks. Associating with late-arriving conspecifics increased the probability of successfully acquiring a breeding territory. Hence, social selection could offset the effects of nonsocial selection. Given parallel theoretical developments of the importance of local network structure on population processes, and increasing data being collected on social networks in free-living populations, the integration of these concepts could yield significant insights into social evolution. PMID:25611344

Social network diagnostics: a tool for monitoring group interventions

PubMed Central

2013-01-01

Background Many behavioral interventions designed to improve health outcomes are delivered in group settings. To date, however, group interventions have not been evaluated to determine if the groups generate interaction among members and how changes in group interaction may affect program outcomes at the individual or group level. Methods This article presents a model and practical tool for monitoring how social ties and social structure are changing within the group during program implementation. The approach is based on social network analysis and has two phases: collecting network measurements at strategic intervention points to determine if group dynamics are evolving in ways anticipated by the intervention, and providing the results back to the group leader to guide implementation next steps. This process aims to initially increase network connectivity and ultimately accelerate the diffusion of desirable behaviors through the new network. This article presents the Social Network Diagnostic Tool and, as proof of concept, pilot data collected during the formative phase of a childhood obesity intervention. Results The number of reported advice partners and discussion partners increased during program implementation. Density, the number of ties among people in the network expressed as a percentage of all possible ties, increased from 0.082 to 0.182 (p < 0.05) in the advice network, and from 0.027 to 0.055 (p > 0.05) in the discussion network. Conclusions The observed two-fold increase in network density represents a significant shift in advice partners over the intervention period. Using the Social Network Tool to empirically guide program activities of an obesity intervention was feasible. PMID:24083343

Using Social Network Analysis as a Method to Assess and Strengthen Participation in Health Promotion Programs in Vulnerable Areas.

PubMed

Hindhede, Anette Lykke; Aagaard-Hansen, Jens

2017-03-01

This article provides an example of the application of social network analysis method to assess community participation thereby strengthening planning and implementation of health promotion programming. Community health promotion often takes the form of services that reach out to or are located within communities. The concept of community reflects the idea that people's behavior and well-being are influenced by interaction with others, and here, health promotion requires participation and local leadership to facilitate transmission and uptake of interventions for the overall community to achieve social change. However, considerable uncertainty exists over exact levels of participation in these interventions. The article draws on a mixed methods research within a community development project in a vulnerable neighborhood of a town in Denmark. It presents a detailed analysis of the way in which social network analysis can be used as a tool to display participation and nonparticipation in community development and health promotion activities, to help identify capacities and assets, mobilize resources, and finally to evaluate the achievements. The article concludes that identification of interpersonal ties among people who know one another well as well as more tenuous relationships in networks can be used by community development workers to foster greater cohesion and cooperation within an area.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data.

PubMed

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam's scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data

PubMed Central

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. PMID:28928958

Predicting the global spread range via small subnetworks

NASA Astrophysics Data System (ADS)

Sun, Jiachen; Dong, Junyou; Ma, Xiao; Feng, Ling; Hu, Yanqing

2017-04-01

Modern online social network platforms are replacing traditional media due to their effectiveness in both spreading information and communicating opinions. One of the key problems in these online platforms is to predict the global spread range of any given information. Due to its gigantic size as well as time-varying dynamics, an online social network's global structure, however, is usually inaccessible to most researchers. Thus, it raises the very important issue of how to use solely small subnetworks to predict the global influence. In this paper, based on percolation theory, we show that the global spread range can be predicted well from only two small subnetworks. We test our methods in an artificial network and three empirical online social networks, such as the full Sina Weibo network with 99546027 nodes.

Impact of weak social ties and networks on poor sleep quality: A case study of Iranian employees.

PubMed

Masoudnia, Ebrahim

2015-12-01

The poor sleep quality is one of the major risk factors of somatic, psychiatric and social disorders and conditions as well as the major predictors of quality of employees' performance. The previous studies in Iran had neglected the impacts of social factors including social networks and ties on adults sleep quality. Thus, the aim of the current research was to determine the relationship between social networks and adult employees' sleep quality. This study was conducted with a correlational and descriptive design. Data were collected from 360 participants (183 males and 177 females) who were employed in Yazd public organizations in June and July of 2014. These samples were selected based on random sampling method. In addition, the measuring tools were the Pittsburgh Sleep Quality Index (PSQI) and Social Relations Inventory (SRI). Based on the results, the prevalence rate of sleep disorder among Iranian adult employees was 63.1% (total PSQI>5). And, after controlling for socio-demographic variables, there was significant difference between individuals with strong and poor social network and ties in terms of overall sleep quality (p<.01), subjective sleep quality (p<.01), habitual sleep efficiency (p<.05), and daytime dysfunction (p<.01). The results also revealed that the employees with strong social network and ties had better overall sleep quality, had the most habitual sleep efficiency, and less daytime dysfunction than employees with poor social network and ties. It can be implied that the weak social network and ties serve as a risk factor for sleep disorders or poor sleep quality for adult employees. Therefore, the social and behavioral interventions seem essential to improve the adult's quality sleep. Copyright © 2015 Elsevier B.V. All rights reserved.

Social Networks in Improvement of Health Care

PubMed Central

Masic, Izet; Sivic, Suad; Toromanovic, Selim; Borojevic, Tea; Pandza, Haris

2012-01-01

Social network is a social structure made of individuals or organizations associated with one or more types of interdependence (friendship, common interests, work, knowledge, prestige, etc.) which are the “nodes” of the network. Networks can be organized to exchange information, knowledge or financial assistance under the various interest groups in universities, workplaces and associations of citizens. Today the most popular and widely used networks are based on application of the Internet as the main ICT. Depending on the method of connection, their field of activity and expertise of those who participate in certain networks, the network can be classified into the following groups: a) Social Networks with personal physical connectivity (the citizens’ associations, transplant networks, etc.), b) Global social internet network (Facebook, Twitter, Skype), c) specific health internet social network (forums, Health Care Forums, Healthcare Industry Forum), d) The health community internet network of non professionals (DailyStrength, CaringBridge, CarePages, MyFamilyHealth), e) Scientific social internet network (BiomedExperts, ResearchGate, iMedExchange), f) Social internet network which supported professionals (HealthBoards, Spas and Hope Association of Disabled and diabetic Enurgi), g) Scientific medical internet network databases in the system of scientific and technical information (CC, Pubmed/Medline, Excerpta Medica/EMBASE, ISI Web Knowledge, EBSCO, Index Copernicus, Social Science Index, etc.). The information in the network are exchanged in real time and in a way that has until recently been impossible in real life of people in the community. Networks allow tens of thousands of specific groups of people performing a series of social, professional and educational activities in the place of living and housing, place of work or other locations where individuals are. Network provides access to information related to education, health, nutrition, drugs, procedures, etc., which gives a special emphasis on public health aspects of information, especially in the field of medicine and health care. The authors of this paper discuss the role and practical importance of social networks in improving the health and solving of health problems without the physical entrance into the health care system. Social networks have their advantages and disadvantages, benefits and costs, especially when it comes to information which within the network set unprofessional people from unreliable sources, without an adequate selection. The ethical aspect of the norms in this segment is still not adequately regulated, so any sanctions for the unauthorized and malicious use of social networks in private and other purposes in order to obtain personal gain at the expense of individuals or groups (sick or healthy, owners of certain businesses and companies, health organizations and pharmaceutical manufacturers, etc.), for which there is still no global or European codes and standards of conduct. Cyber crime is now one of the mostly present types of crime in modern times, as evidenced by numerous scandals that are happening both globally and locally. PMID:23922516

Design and methods of a social network isolation study for reducing respiratory infection transmission: The eX-FLU cluster randomized trial.

PubMed

Aiello, Allison E; Simanek, Amanda M; Eisenberg, Marisa C; Walsh, Alison R; Davis, Brian; Volz, Erik; Cheng, Caroline; Rainey, Jeanette J; Uzicanin, Amra; Gao, Hongjiang; Osgood, Nathaniel; Knowles, Dylan; Stanley, Kevin; Tarter, Kara; Monto, Arnold S

2016-06-01

Social networks are increasingly recognized as important points of intervention, yet relatively few intervention studies of respiratory infection transmission have utilized a network design. Here we describe the design, methods, and social network structure of a randomized intervention for isolating respiratory infection cases in a university setting over a 10-week period. 590 students in six residence halls enrolled in the eX-FLU study during a chain-referral recruitment process from September 2012-January 2013. Of these, 262 joined as "seed" participants, who nominated their social contacts to join the study, of which 328 "nominees" enrolled. Participants were cluster-randomized by 117 residence halls. Participants were asked to respond to weekly surveys on health behaviors, social interactions, and influenza-like illness (ILI) symptoms. Participants were randomized to either a 3-Day dorm room isolation intervention or a control group (no isolation) upon illness onset. ILI cases reported on their isolation behavior during illness and provided throat and nasal swab specimens at onset, day-three, and day-six of illness. A subsample of individuals (N=103) participated in a sub-study using a novel smartphone application, iEpi, which collected sensor and contextually-dependent survey data on social interactions. Within the social network, participants were significantly positively assortative by intervention group, enrollment type, residence hall, iEpi participation, age, gender, race, and alcohol use (all P<0.002). We identified a feasible study design for testing the impact of isolation from social networks in a university setting. These data provide an unparalleled opportunity to address questions about isolation and infection transmission, as well as insights into social networks and behaviors among college-aged students. Several important lessons were learned over the course of this project, including feasible isolation durations, the need for extensive organizational efforts, as well as the need for specialized programmers and server space for managing survey and smartphone data. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Loneliness, Social Networks, and Health: A Cross-Sectional Study in Three Countries

PubMed Central

Rico-Uribe, Laura Alejandra; Caballero, Francisco Félix; Olaya, Beatriz; Tobiasz-Adamczyk, Beata; Koskinen, Seppo; Leonardi, Matilde; Haro, Josep Maria; Chatterji, Somnath

2016-01-01

Objective It is widely recognized that social networks and loneliness have effects on health. The present study assesses the differential association that the components of the social network and the subjective perception of loneliness have with health, and analyzes whether this association is different across different countries. Methods A total of 10 800 adults were interviewed in Finland, Poland and Spain. Loneliness was assessed by means of the 3-item UCLA Loneliness Scale. Individuals’ social networks were measured by asking about the number of members in the network, how often they had contacts with these members, and whether they had a close relationship. The differential association of loneliness and the components of the social network with health was assessed by means of hierarchical linear regression models, controlling for relevant covariates. Results In all three countries, loneliness was the variable most strongly correlated with health after controlling for depression, age, and other covariates. Loneliness contributed more strongly to health than any component of the social network. The relationship between loneliness and health was stronger in Finland (|β| = 0.25) than in Poland (|β| = 0.16) and Spain (|β| = 0.18). Frequency of contact was the only component of the social network that was moderately correlated with health. Conclusions Loneliness has a stronger association with health than the components of the social network. This association is similar in three different European countries with different socio-economic and health characteristics and welfare systems. The importance of evaluating and screening feelings of loneliness in individuals with health problems should be taken into account. Further studies are needed in order to be able to confirm the associations found in the present study and infer causality. PMID:26761205

Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

PubMed Central

Wiggins, Benjamin L.; Goodreau, Steven M.

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. PMID:26086650

Analysis of Online Social Networks to Understand Information Sharing Behaviors Through Social Cognitive Theory.

PubMed

Yoon, Hong-Jun; Tourassi, Georgia

2014-05-01

Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples' behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of "leaders" on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of "followers", people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

Social traits, social networks and evolutionary biology.

PubMed

Fisher, D N; McAdam, A G

2017-12-01

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users

PubMed Central

Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

2016-01-01

Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one’s avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one’s avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection. PMID:27415603

Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users.

PubMed

Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

2016-09-01

Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one's avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one's avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection.

Social-ecological network analysis of scale mismatches in estuary watershed restoration.

PubMed

Sayles, Jesse S; Baggio, Jacopo A

2017-03-07

Resource management boundaries seldom align with environmental systems, which can lead to social and ecological problems. Mapping and analyzing how resource management organizations in different areas collaborate can provide vital information to help overcome such misalignment. Few quantitative approaches exist, however, to analyze social collaborations alongside environmental patterns, especially among local and regional organizations (i.e., in multilevel governance settings). This paper develops and applies such an approach using social-ecological network analysis (SENA), which considers relationships among and between social and ecological units. The framework and methods are shown using an estuary restoration case from Puget Sound, United States. Collaboration patterns and quality are analyzed among local and regional organizations working in hydrologically connected areas. These patterns are correlated with restoration practitioners' assessments of the productivity of their collaborations to inform network theories for natural resource governance. The SENA is also combined with existing ecological data to jointly consider social and ecological restoration concerns. Results show potentially problematic areas in nearshore environments, where collaboration networks measured by density (percentage of possible network connections) and productivity are weakest. Many areas also have high centralization (a few nodes hold the network together), making network cohesion dependent on key organizations. Although centralization and productivity are inversely related, no clear relationship between density and productivity is observed. This research can help practitioners to identify where governance capacity needs strengthening and jointly consider social and ecological concerns. It advances SENA by developing a multilevel approach to assess social-ecological (or social-environmental) misalignments, also known as scale mismatches.

Social implications of children's smartphone addiction: The role of support networks and social engagement.

PubMed

Ihm, Jennifer

2018-06-01

Background and aims Most studies have regarded smartphone addiction as a condition stemming from individuals' psychological issues, so research has rarely examined it in relation to a lack of social resources and its social impacts. However, this study reinterprets smartphone addiction as a social problem stemming from a lack of offline social networks and resulting in a decline of social engagement. Methods This study drew on a survey of 2,000 children in Korea consisting of 991 males and 1,009 females with an average age of 12 years old. Using the STATA 14 structural equation modeling program, this study examined the relationships between children's lack of social networks, smartphone addiction, and social engagement. Results Social network variables, such as formal organizational membership, quality of relationship with parents, size of the peer group, and peer support, decrease smartphone addiction. Simply having good relationships and reciprocal feelings with peers do not have any influence on the smartphone addiction. The more the children become addicted to smartphones, the less they participate in social engagement. Discussion and conclusions This study provides a new understanding of smartphone addiction by focusing on its social aspects, augmenting prior studies that have addressed psychological factors. Findings suggest that children's lack of social networks may inhibit comfortable social interactions and feelings of support in the offline environment, which can heighten their desire to escape to smartphones. These children, unlike non-addicts, may not take advantage of the media to enrich their social lives and increase their level of social engagement.

Social Networks-Based Adaptive Pairing Strategy for Cooperative Learning

ERIC Educational Resources Information Center

Chuang, Po-Jen; Chiang, Ming-Chao; Yang, Chu-Sing; Tsai, Chun-Wei

2012-01-01

In this paper, we propose a grouping strategy to enhance the learning and testing results of students, called Pairing Strategy (PS). The proposed method stems from the need of interactivity and the desire of cooperation in cooperative learning. Based on the social networks of students, PS provides members of the groups to learn from or mimic…

Food Insecurity Is Associated with Acculturation and Social Networks in Puerto Rican Households

ERIC Educational Resources Information Center

Dhokarh, Rajanigandha; Himmelgreen, David A.; Peng, Yu-Kuei; Segura-Perez, Sofia; Hromi-Fiedler, Amber; Perez-Escamilla, Rafael

2011-01-01

Objective: To examine whether acculturation and social networks influence household food insecurity in an inner-city Puerto Rican community. Methods: A survey was administered to 200 low-income female Puerto Rican caregivers with at least 1 child 12-72 months old living in Hartford, CT. Food insecurity was measured with the Radimer/Cornell Hunger…

The Shifting Spaces of Teacher Relationships: Complementary Methods in Examinations of Teachers' Digital Practices

ERIC Educational Resources Information Center

Homan, Elizabeth C.

2014-01-01

Today's teachers are faced with a number of options when it comes to sharing knowledge about their professions. In the digital age, teachers use social media, online professional networks, email listservs, and blogging connections to share knowledge and resources. Here, I describe how one teacher engages with social media to develop networks that…

An Examination of Native and Immigrant Students' Social Networking Using the College Search and Selection Process

ERIC Educational Resources Information Center

Neimeyer, Bruce Carlton

2009-01-01

This dissertation explores the use of formal and informal networks through cyber- and traditional communication methods in the college search and selection process by native and immigrant students to examine various postulates and propositions of social capital theory. In addition, the analysis of cybernetworks used by disadvantaged, college bound…

The Structure of Informal Social Networks of Persons with Profound Intellectual and Multiple Disabilities

ERIC Educational Resources Information Center

Kamstra, A.; van der Putten, A. A. J.; Vlaskamp, C.

2015-01-01

Background: Persons with less severe disabilities are able to express their needs and show initiatives in social contacts, persons with profound intellectual and multiple disabilities (PIMD), however, depend on others for this. This study analysed the structure of informal networks of persons with PIMD. Materials and Methods: Data concerning the…

Female Arab Students' Perceptions of Social Networks as an English Language Learning Environment

ERIC Educational Resources Information Center

Ellili-Cherif, Maha

2017-01-01

The purpose of this research was to investigate female Arab college students' use of and perceptions about social networking sites (SNSs) as an English language learning environment. A mixed methods approach was adopted for data collection and analysis. First, a questionnaire was used to explore the extent to which participants (n = 182) were…

The Contribution of Social Networks to the Health and Self-Management of Patients with Long-Term Conditions: A Longitudinal Study

PubMed Central

Reeves, David; Blickem, Christian; Vassilev, Ivaylo; Brooks, Helen; Kennedy, Anne; Richardson, Gerry; Rogers, Anne

2014-01-01

Evidence for the effectiveness of patient education programmes in changing individual self-management behaviour is equivocal. More distal elements of personal social relationships and the availability of social capital at the community level may be key to the mobilisation of resources needed for long-term condition self-management to be effective. Aim To determine how the social networks of people with long-term conditions (diabetes and heart disease) are associated with health-related outcomes and changes in outcomes over time. Methods Patients with chronic heart disease (CHD) or diabetes (n = 300) randomly selected from the disease registers of 19 GP practices in the North West of England. Data on personal social networks collected using a postal questionnaire, alongside face-to-face interviewing. Follow-up at 12 months via postal questionnaire using a self-report grid for network members identified at baseline. Analysis Multiple regression analysis of relationships between health status, self-management and health-economics outcomes, and characteristics of patients' social networks. Results Findings indicated that: (1) social involvement with a wider variety of people and groups supports personal self-management and physical and mental well-being; (2) support work undertaken by personal networks expands in accordance with health needs helping people to cope with their condition; (3) network support substitutes for formal care and can produce substantial saving in traditional health service utilisation costs. Health service costs were significantly (p<0.01) reduced for patients receiving greater levels of illness work through their networks. Conclusions Support for self-management which achieves desirable policy outcomes should be construed less as an individualised set of actions and behaviour and more as a social network phenomenon. This study shows the need for a greater focus on harnessing and sustaining the capacity of networks and the importance of social involvement with community groups and resources for producing a more desirable and cost-effective way of supporting long term illness management. PMID:24887107

Sense-making for intelligence analysis on social media data

NASA Astrophysics Data System (ADS)

Pritzkau, Albert

2016-05-01

Social networks, in particular online social networks as a subset, enable the analysis of social relationships which are represented by interaction, collaboration, or other sorts of influence between people. Any set of people and their internal social relationships can be modelled as a general social graph. These relationships are formed by exchanging emails, making phone calls, or carrying out a range of other activities that build up the network. This paper presents an overview of current approaches to utilizing social media as a ubiquitous sensor network in the context of national and global security. Exploitation of social media is usually an interdisciplinary endeavour, in which the relevant technologies and methods are identified and linked in order ultimately demonstrate selected applications. Effective and efficient intelligence is usually accomplished in a combined human and computer effort. Indeed, the intelligence process heavily depends on combining a human's flexibility, creativity, and cognitive ability with the bandwidth and processing power of today's computers. To improve the usability and accuracy of the intelligence analysis we will have to rely on data-processing tools at the level of natural language. Especially the collection and transformation of unstructured data into actionable, structured data requires scalable computational algorithms ranging from Artificial Intelligence, via Machine Learning, to Natural Language Processing (NLP). To support intelligence analysis on social media data, social media analytics is concerned with developing and evaluating computational tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data. Analytics methods are employed to extract of significant patterns that might not be obvious. As a result, different data representations rendering distinct aspects of content and interactions serve as a means to adapt the focus of the intelligence analysis to specific information requests.

Modular and hierarchical structure of social contact networks

NASA Astrophysics Data System (ADS)

Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2013-10-01

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

The mediating role of social capital in the association between neighbourhood income inequality and body mass index.

PubMed

Mackenbach, Joreintje D; Lakerveld, Jeroen; van Oostveen, Yavanna; Compernolle, Sofie; De Bourdeaudhuij, Ilse; Bárdos, Helga; Rutter, Harry; Glonti, Ketevan; Oppert, Jean-Michel; Charreire, Helene; Brug, Johannes; Nijpels, Giel

2017-04-01

Neighbourhood income inequality may contribute to differences in body weight. We explored whether neighbourhood social capital mediated the association of neighbourhood income inequality with individual body mass index (BMI). A total of 4126 adult participants from 48 neighbourhoods in France, Hungary, the Netherlands and the UK provided information on their levels of income, perceptions of neighbourhood social capital and BMI. Factor analysis of the 13-item social capital scale revealed two social capital constructs: social networks and social cohesion. Neighbourhood income inequality was defined as the ratio of the amount of income earned by the top 20% and the bottom 20% in a given neighbourhood. Two single mediation analyses-using multilevel linear regression analyses-with neighbourhood social networks and neighbourhood social cohesion as possible mediators-were conducted using MacKinnon's product-of-coefficients method, adjusted for age, gender, education and absolute household income. Higher neighbourhood income inequality was associated with elevated levels of BMI and lower levels of neighbourhood social networks and neighbourhood social cohesion. High levels of neighbourhood social networks were associated with lower BMI. Results stratified by country demonstrate that social networks fully explained the association between income inequality and BMI in France and the Netherlands. Social cohesion was only a significant mediating variable for Dutch participants. The results suggest that in some European urban regions, neighbourhood social capital plays a large role in the association between neighbourhood income inequality and individual BMI. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units

PubMed Central

2011-01-01

Background The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. Methods We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Results Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Conclusions Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction. PMID:21631936

"I like talking to people on the computer": Outcomes of a home-based intervention to develop social media skills in youth with disabilities living in rural communities.

PubMed

Raghavendra, Parimala; Hutchinson, Claire; Grace, Emma; Wood, Denise; Newman, Lareen

2018-05-01

To investigate the effectiveness of a home-based social media use intervention to enhance the social networks of rural youth with disabilities. Participants were nine youth (mean age = 17.0 years) with disabilities from two rural Australian communities. The intervention consisted of providing appropriate assistive technology and social media training on individualised goals. Using mixed methods, quantitative (a single group pre-post) and qualitative (interviews with participants and their carers) measures were used to examine outcomes of training, individual experiences of the intervention, and changes to online social networks. Participants increased their performance and satisfaction with performance on social media problem areas post-intervention; paired t-tests showed statistical significance at p < .001. There was also a significant increase in the number of online communication partners; Wilcoxon Signed Ranks showed statistical significance at p < .05. The interviews highlighted increased social participation, independence and improvements to literacy. Ongoing parental concerns regarding cyber safety and inappropriate online content were noted. The findings suggest that social media training is a feasible method for increasing social networks among rural-based youth with disabilities. To sustain ongoing benefits, parents need knowledge and training in integrating assistive technology and social media. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Network Method of Measuring Affiliation-Based Peer Influence: Assessing the Influences of Teammates' Smoking on Adolescent Smoking

ERIC Educational Resources Information Center

Fujimoto, Kayo; Unger, Jennifer B.; Valente, Thomas W.

2012-01-01

Using a network analytic framework, this study introduces a new method to measure peer influence based on adolescents' affiliations or 2-mode social network data. Exposure based on affiliations is referred to as the "affiliation exposure model." This study demonstrates the methodology using data on young adolescent smoking being influenced by…

Network Interventions on Physical Activity in an Afterschool Program: An Agent-Based Social Network Study

PubMed Central

Zhang, Jun; Shoham, David A.; Tesdahl, Eric

2015-01-01

Objectives. We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children’s physical activity. We tested 3 intervention strategies. Results. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children’s physical activity. PMID:25689202

Video Games, Internet and Social Networks: A Study among French School students

PubMed

Dany, Lionel; Moreau, Laure; Guillet, Clémentine; Franchina, Carmelo

2016-11-25

Aim : Screen-based media use is gradually becoming a public health issue, especially among young people.Method : A local descriptive observational study was conducted in 11 colleges of the Bouches-du-Rhône department. All middle high school students were asked to fill in a questionnaire comprising questions about their demographic characteristics, their screen-based media use (Internet, video games, social networks), any problematic use (video games and social networks), self-esteem and quality of life.Results : A total of 950 college students (mean age : 12.96 years) participated in the research. The results show a high level and a very diverse screen-based media use. Boys more frequently played video games and girls go more frequently used social networks. The levels of problematic use were relatively low for all middle high school students. The level of problematic video game use was significantly higher in boys, and the level of problematic social network use was higher in girls.Conclusion : Differences in the use of video games or social networks raise the general issue of gender differences in society. This study indicates the need for more specific preventive interventions for screen-based media use. The addictive “nature” of certain practices needs to be studied in more detail.

Interactive social contagions and co-infections on complex networks

NASA Astrophysics Data System (ADS)

Liu, Quan-Hui; Zhong, Lin-Feng; Wang, Wei; Zhou, Tao; Eugene Stanley, H.

2018-01-01

What we are learning about the ubiquitous interactions among multiple social contagion processes on complex networks challenges existing theoretical methods. We propose an interactive social behavior spreading model, in which two behaviors sequentially spread on a complex network, one following the other. Adopting the first behavior has either a synergistic or an inhibiting effect on the spread of the second behavior. We find that the inhibiting effect of the first behavior can cause the continuous phase transition of the second behavior spreading to become discontinuous. This discontinuous phase transition of the second behavior can also become a continuous one when the effect of adopting the first behavior becomes synergistic. This synergy allows the second behavior to be more easily adopted and enlarges the co-existence region of both behaviors. We establish an edge-based compartmental method, and our theoretical predictions match well with the simulation results. Our findings provide helpful insights into better understanding the spread of interactive social behavior in human society.

A prospective examination of online social network dynamics and smoking cessation

PubMed Central

Zhao, Kang; Papandonatos, George D.; Erar, Bahar; Wang, Xi; Amato, Michael S.; Cha, Sarah; Cohn, Amy M.; Pearson, Jennifer L.

2017-01-01

Introduction Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence. Method Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics. Results Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05). Conclusions This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors. PMID:28832621

Interspecific social networks promote information transmission in wild songbirds.

PubMed

Farine, Damien R; Aplin, Lucy M; Sheldon, Ben C; Hoppitt, William

2015-03-22

Understanding the functional links between social structure and population processes is a central aim of evolutionary ecology. Multiple types of interactions can be represented by networks drawn for the same population, such as kinship, dominance or affiliative networks, but the relative importance of alternative networks in modulating population processes may not be clear. We illustrate this problem, and a solution, by developing a framework for testing the importance of different types of association in facilitating the transmission of information. We apply this framework to experimental data from wild songbirds that form mixed-species flocks, recording the arrival (patch discovery) of individuals to novel foraging sites. We tested whether intraspecific and interspecific social networks predicted the spread of information about novel food sites, and found that both contributed to transmission. The likelihood of acquiring information per unit of connection to knowledgeable individuals increased 22-fold for conspecifics, and 12-fold for heterospecifics. We also found that species varied in how much information they produced, suggesting that some species play a keystone role in winter foraging flocks. More generally, these analyses demonstrate that this method provides a powerful approach, using social networks to quantify the relative transmission rates across different social relationships.

Social power, conflict policing, and the role of subordination signals in rhesus macaque society

PubMed Central

Beisner, Brianne A.; Hannibal, Darcy L.; Finn, Kelly R.; Fushing, Hsieh; McCowan, Brenda

2017-01-01

Objectives Policing is a conflict-limiting mechanism observed in many primate species. It is thought to require a skewed distribution of social power for some individuals to have sufficiently high social power to stop others’ fights, yet social power has not been examined in most species with policing behavior. We examined networks of subordination signals as a source of social power that permits policing behavior in rhesus macaques. Materials and Methods For each of seven captive groups of rhesus macaques, we (a) examined the structure of subordination signal networks and used GLMs to examine the relationship between (b) pairwise dominance certainty and subordination network pathways and (c) policing frequency and social power (group-level convergence in subordination signaling pathways). Results Networks of subordination signals had perfect linear transitivity, and pairs connected by both direct and indirect pathways of signals had more certain dominance relationships than pairs with no such network connection. Social power calculated using both direct and indirect network pathways showed a heavy-tailed distribution and positively predicted conflict policing. Conclusions Our results empirically substantiate that subordination signaling is associated with greater dominance relationship certainty and further show that pairs who signal rarely (or not at all) may use information from others’ signaling interactions to infer or reaffirm the relative certainty of their own relationships. We argue that the network of formal dominance relationships is central to societal stability because it is important for relationship stability and also supports the additional stabilizing mechanism of policing. PMID:26801956

Do highly cited clinicians get more citations when being present at social networking sites?

PubMed Central

Ramezani-Pakpour-Langeroudi, Fatemeh; Okhovati, Maryam; Talebian, Ali

2018-01-01

BACKGROUND AND AIMS: The advent of social networking sites has facilitated the dissemination of scientific research. This article aims to investigate the presence of Iranian highly cited clinicians in social networking sites. MATERIALS AND METHODS: This is a scientometrics study. Essential Science Indicator (ESI) was searched for Iranian highly cited papers in clinical medicine during November–December 2015. Then, the authors of the papers were checked and a list of authors was obtained. In the second phase, the authors’ names were searched in the selected social networking sites (ResearchGate [RG], Academia, Mendeley, LinkedIn). The total citations and h-index in Scopus were also gathered. RESULTS: Fifty-five highly cited papers were retrieved. A total of 107 authors participated in writing these papers. RG was the most popular (64.5%) and LinkedIn and Academia were in 2nd and 3rd places. None of the authors of highly cited papers were subscribed to Mendeley. A positive direct relationship was observed between visibility at social networking sites with citation and h-index rate. A significant relationship was observed between the RG score, citations, reads indicators in RG, and citation numbers and there was a significant relationship between the number of document indicator in Academia and the citation numbers. CONCLUSION: It seems putting the papers in social networking sites can influence the citation rate. We recommend all scientists to be present at social networking sites to have better chance of visibility and also citation. PMID:29629379

Social networks and patterns of health risk behaviours over two decades: A multi-cohort study.

PubMed

Kauppi, Maarit; Elovainio, Marko; Stenholm, Sari; Virtanen, Marianna; Aalto, Ville; Koskenvuo, Markku; Kivimäki, Mika; Vahtera, Jussi

2017-08-01

To determine the associations between social network size and subsequent long-term health behaviour patterns, as indicated by alcohol use, smoking, and physical activity. Repeat data from up to six surveys over a 15- or 20-year follow-up were drawn from the Finnish Public Sector study (Raisio-Turku cohort, n=986; Hospital cohort, n=7307), and the Health and Social Support study (n=20,115). Social network size was determined at baseline, and health risk behaviours were assessed using repeated data from baseline and follow-up. We pooled cohort-specific results from repeated-measures log-binomial regression with the generalized estimating equations (GEE) method using fixed-effects meta-analysis. Participants with up to 10 members in their social network at baseline had an unhealthy risk factor profile throughout the follow-up. The pooled relative risks adjusted for age, gender, survey year, chronic conditions and education were 1.15 for heavy alcohol use (95% CI: 1.06-1.24), 1.19 for smoking (95% CI: 1.12-1.27), and 1.25 for low physical activity (95% CI: 1.21-1.29), as compared with those with >20 members in their social network. These associations appeared to be similar in subgroups stratified according to gender, age and education. Social network size predicted persistent behaviour-related health risk patterns up to at least two decades. Copyright © 2017 Elsevier Inc. All rights reserved.

The Influence of Social Network Characteristics on Peer Clustering in Smoking: A Two-Wave Panel Study of 19- and 23-Year-Old Swedes

PubMed Central

Rostila, Mikael; Edling, Christofer; Rydgren, Jens

2016-01-01

Objectives The present study examines how the composition of social networks and perceived relationship content influence peer clustering in smoking, and how the association changes during the transition from late adolescence to early adulthood. Methods The analysis was based on a Swedish two-wave survey sample comprising ego-centric network data. Respondents were 19 years old in the initial wave, and 23 when the follow-up sample was conducted. 17,227 ego-alter dyads were included in the analyses, which corresponds to an average response rate of 48.7 percent. Random effects logistic regression models were performed to calculate gender-specific average marginal effects of social network characteristics on smoking. Results The association of egos’ and alters’ smoking behavior was confirmed and found to be stronger when correlated in the female sample. For females, the associations decreased between age 19 and 23. Interactions between network characteristics and peer clustering in smoking showed that intense social interactions with smokers increase egos’ smoking probability. The influence of network structures on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. Conclusions The study confirmed peer clustering in smoking and revealed that females’ smoking behavior in particular is determined by social interactions. Female smokers’ propensity to interact with other smokers was found to be associated with the quality of peer relationships, frequent social interactions, and network density. The influence of social networks on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. PMID:27727314

Relation between social network and psychological distress among middle-aged adults in Japan: Evidence from a national longitudinal survey.

PubMed

Fu, Rong; Noguchi, Harkuo; Tachikawa, Hirokazu; Aiba, Miyuki; Nakamine, Shin; Kawamura, Akira; Takahashi, Hideto; Tamiya, Nanako

2017-02-01

It is widely documented that psychological distress is negatively associated with social networks involvement. However, despite the theoretical postulations that social networks are crucial for alleviating psychological distress, no study has yet empirically confirmed the causality of this relationship. Thus, we used the random-effects generalized least squares method to investigate the effect of one- and two-year lagged values for involvement in social networks on psychological distress. Nine years of longitudinal data were extracted from a nationally representative survey in Japan ("The Longitudinal Survey of Middle-aged and Older Persons"). We utilized the Kessler 6 (K6) score to measure psychological distress among 15,242 respondents aged 50-59 years in the baseline year (2005), and stratified participants into three layers of social networks: inner (well-established friendship ties and participating in hobby activates), intermediary (neighborly ties), and outer (involvement in community activities). We found highly significant and negative associations between all three layers and K6 scores, with the strongest association being for the inner layer. We further observed that one-year lagged involvement in the inner and intermediary layers led to significantly lower K6 scores. However, the protective influences of social networks generally diminished over time. In addition, the protective influences of social network involvement on psychological distress were stronger for women than for men. Furthermore, involvement in social networks was especially important for improving mental health among people with psychological distress. These findings would be important for policymaking to prevent mental health deterioration among middle-aged adults in Japan. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls

PubMed Central

Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

2016-01-01

Background Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls’ perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Methods Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Results Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered “uncool”. Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. Conclusion This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications. PMID:26934191

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

PubMed Central

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

A Typology to Explain Changing Social Networks Post Stroke.

PubMed

Northcott, Sarah; Hirani, Shashivadan P; Hilari, Katerina

2018-05-08

Social network typologies have been used to classify the general population but have not previously been applied to the stroke population. This study investigated whether social network types remain stable following a stroke, and if not, why some people shift network type. We used a mixed methods design. Participants were recruited from two acute stroke units. They completed the Stroke Social Network Scale (SSNS) two weeks and six months post stroke and in-depth interviews 8-15 months following the stroke. Qualitative data was analysed using Framework Analysis; k-means cluster analysis was applied to the six-month data set. Eighty-seven participants were recruited, 71 were followed up at six months, and 29 completed in-depth interviews. It was possible to classify all 29 participants into one of the following network types both prestroke and post stroke: diverse; friends-based; family-based; restricted-supported; restricted-unsupported. The main shift that took place post stroke was participants moving out of a diverse network into a family-based one. The friends-based network type was relatively stable. Two network types became more populated post stroke: restricted-unsupported and family-based. Triangulatory evidence was provided by k-means cluster analysis, which produced a cluster solution (for n = 71) with comparable characteristics to the network types derived from qualitative analysis. Following a stroke, a person's social network is vulnerable to change. Explanatory factors for shifting network type included the physical and also psychological impact of having a stroke, as well as the tendency to lose contact with friends rather than family.

Point-Process Models of Social Network Interactions: Parameter Estimation and Missing Data Recovery

DTIC Science & Technology

2014-08-01

treating them as zero will have a de minimis impact on the results, but avoiding computing them (and computing with them) saves tremendous time. Set a... test the methods on simulated time series on artificial social networks, including some toy networks and some meant to resemble IkeNet. We conclude...the section by discussing the results in detail. In each of our tests we begin with a complete data set, whether it is real (IkeNet) or simulated. Then

Detecting Emotional Contagion in Massive Social Networks

PubMed Central

Coviello, Lorenzo; Sohn, Yunkyu; Kramer, Adam D. I.; Marlow, Cameron; Franceschetti, Massimo; Christakis, Nicholas A.; Fowler, James H.

2014-01-01

Happiness and other emotions spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a novel method for measuring the contagion of emotional expression. With data from millions of Facebook users, we show that rainfall directly influences the emotional content of their status messages, and it also affects the status messages of friends in other cities who are not experiencing rainfall. For every one person affected directly, rainfall alters the emotional expression of about one to two other people, suggesting that online social networks may magnify the intensity of global emotional synchrony. PMID:24621792

Inferring animal social networks and leadership: applications for passive monitoring arrays.

PubMed

Jacoby, David M P; Papastamatiou, Yannis P; Freeman, Robin

2016-11-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. © 2016 The Authors.

Inferring animal social networks and leadership: applications for passive monitoring arrays

PubMed Central

Papastamatiou, Yannis P.; Freeman, Robin

2016-01-01

Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics. In doing so, we provide the first evidence of long-term, spatially extensive social processes in wild sharks. To achieve these results, we interrogate simulated and real tracking data with the explicit purpose of drawing attention to the key considerations in the use and interpretation of inference methods and their impact on resultant social structure. We provide a modified translation of the GMMEvents method for R, including new analyses quantifying the directionality and duration of social events with the aim of encouraging the careful use of these methods more widely in less tractable social animal systems but where passive telemetry is already widespread. PMID:27881803

When Advocacy Obscures Accuracy Online: Digital Pandemics of Public Health Misinformation Through an Antifluoride Case Study

PubMed Central

Getman, Rebekah; Saraf, Avinash; Zhang, Lily H.; Kalenderian, Elsbeth

2015-01-01

Objectives. In an antifluoridation case study, we explored digital pandemics and the social spread of scientifically inaccurate health information across the Web, and we considered the potential health effects. Methods. Using the social networking site Facebook and the open source applications Netvizz and Gephi, we analyzed the connectedness of antifluoride networks as a measure of social influence, the social diffusion of information based on conversations about a sample scientific publication as a measure of spread, and the engagement and sentiment about the publication as a measure of attitudes and behaviors. Results. Our study sample was significantly more connected than was the social networking site overall (P < .001). Social diffusion was evident; users were forced to navigate multiple pages or never reached the sample publication being discussed 60% and 12% of the time, respectively. Users had a 1 in 2 chance of encountering negative and nonempirical content about fluoride unrelated to the sample publication. Conclusions. Network sociology may be as influential as the information content and scientific validity of a particular health topic discussed using social media. Public health must employ social strategies for improved communication management. PMID:25602893

Clinic Versus Online Social Network–Delivered Lifestyle Interventions: Protocol for the Get Social Noninferiority Randomized Controlled Trial

PubMed Central

Wang, Monica L; Waring, Molly E; Jake-Schoffman, Danielle E; Oleski, Jessica L; Michaels, Zachary; Goetz, Jared M; Lemon, Stephenie C; Ma, Yunsheng

2017-01-01

Background Online social networks may be a promising modality to deliver lifestyle interventions by reducing cost and burden. Although online social networks have been integrated as one component of multimodality lifestyle interventions, no randomized trials to date have compared a lifestyle intervention delivered entirely via online social network with a traditional clinic-delivered intervention. Objective This paper describes the design and methods of a noninferiority randomized controlled trial, testing (1) whether a lifestyle intervention delivered entirely through an online social network would produce weight loss that would not be appreciably worse than that induced by a traditional clinic-based lifestyle intervention among overweight and obese adults and (2) whether the former would do so at a lower cost. Methods Adults with body mass index (BMI) between 27 and 45 kg/m2 (N=328) will be recruited from the communities in central Massachusetts. These overweight or obese adults will be randomized to two conditions: a lifestyle intervention delivered entirely via the online social network Twitter (Get Social condition) and an in-person group-based lifestyle intervention (Traditional condition) among overweight and obese adults. Measures will be obtained at baseline, 6 months, and 12 months after randomization. The primary noninferiority outcome is percentage weight loss at 12 months. Secondary noninferiority outcomes include dietary intake and moderate intensity physical activity at 12 months. Our secondary aim is to compare the conditions on cost. Exploratory outcomes include treatment retention, acceptability, and burden. Finally, we will explore predictors of weight loss in the online social network condition. Results The final wave of data collection is expected to conclude in June 2019. Data analysis will take place in the months following and is expected to be complete in September 2019. Conclusions Findings will extend the literature by revealing whether delivering a lifestyle intervention via an online social network is an effective alternative to the traditional modality of clinic visits, given the former might be more scalable and feasible to implement in settings that cannot support clinic-based models. Trial Registration ClinicalTrials.gov NCT02646618; https://clinicaltrials.gov/ct2/show/NCT02646618 (Archived by WebCite at http://www.webcitation.org/6v20waTFW) PMID:29229591

Association of School Social Networks' Influence and Mass Media Factors with Cigarette Smoking among Asthmatic Students

ERIC Educational Resources Information Center

Kanamori, Mariano; Beck, Kenneth H.; Carter-Pokras, Olivia

2015-01-01

Background: Around 10% of adolescent students under 18 years have current asthma. Asthmatic adolescents smoke as much or more than non-asthmatic adolescents. We explored the association between exposure to mass media and social networks' influence with asthmatic student smoking, and variations of these exposures by sex. Methods: This study…

Mentoring in the Context of Latino Youth's Broader Village during Their Transition from High School

ERIC Educational Resources Information Center

Sanchez, Bernadette; Esparza, Patricia; Berardi, Luciano; Pryce, Julia

2011-01-01

The aims of this study were to examine the mentoring and social network experiences of Latino youth during the high school transition. A mixed-methods approach was used to examine participants' natural mentoring relationships before and after the transition along with the broader social networks of youth. A total of 32 Latino participants…

The Use of Social Networking among Senior Secondary School Students in Abuja Municipal Area of Federal Capital Territory, Nigeria

ERIC Educational Resources Information Center

Ali, F. A. Farah; Aliyu, Umar Yanda

2015-01-01

The present study examined the use of social networking among senior secondary school students in Abuja Municipal Area Council of FCT. The study employed quantitative method for data collection involving questionnaire administration. Fifteen questions with Likert model and ten yes/no responses in a questionnaire were personally administered to 400…

Naturally-Emerging Technology-Based Leadership Roles in Three Independent Schools: A Social Network-Based Case Study Using Fuzzy Set Qualitative Comparative Analysis

ERIC Educational Resources Information Center

Velastegui, Pamela J.

2013-01-01

This hypothesis-generating case study investigates the naturally emerging roles of technology brokers and technology leaders in three independent schools in New York involving 92 school educators. A multiple and mixed method design utilizing Social Network Analysis (SNA) and fuzzy set Qualitative Comparative Analysis (FSQCA) involved gathering…

Defining Appropriate Professional Behavior for Faculty and University Students on Social Networking Websites

ERIC Educational Resources Information Center

Malesky, L. Alvin; Peters, Chris

2012-01-01

The vast majority of university students have profiles on social networking sites (e.g., Myspace, Facebook) (Salaway et al. 2008). However, it is yet to be determined what role this rapidly evolving method of communication will play in an academic setting. Data for the current study was collected from 459 university students and 159 university…

Social care networks and older LGBT adults: challenges for the future.

PubMed

Brennan-Ing, Mark; Seidel, Liz; Larson, Britta; Karpiak, Stephen E

2014-01-01

Research on service needs among older adults rarely addresses the special circumstances of lesbian, gay, bisexual, and transgender (LGBT) individuals, such as their reliance on friend-centered social networks or the experience of discrimination from service providers. Limited data suggests that older LGBT adults underutilize health and social services that are important in maintaining independence and quality of life. This study explored the social care networks of this population using a mixed-methods approach. Data were obtained from 210 LGBT older adults. The average age was 60 years, and 71% were men, 24% were women, and 5% were transgender or intersex. One-third was Black, and 62% were Caucasian. Quantitative assessments found high levels of morbidity and friend-centered support networks. Need for and use of services was frequently reported. Content analysis revealed unmet needs for basic supports, including housing, economic supports, and help with entitlements. Limited opportunities for socialization were strongly expressed, particularly among older lesbians. Implications for senior programs and policies are discussed.

Seasonal Influenza Vaccination amongst Medical Students: A Social Network Analysis Based on a Cross-Sectional Study

PubMed Central

Edge, Rhiannon; Heath, Joseph; Rowlingson, Barry; Keegan, Thomas J.; Isba, Rachel

2015-01-01

Introduction The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics. Methods We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network. Results Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics. Conclusions This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers. PMID:26452223

An Empirical Typology of Social Networks and Its Association With Physical and Mental Health: A Study With Older Korean Immigrants

PubMed Central

Jang, Yuri; Lee, Beom S.; Ko, Jung Eun; Haley, William E.; Chiriboga, David A.

2015-01-01

Objectives. In the context of social convoy theory, the purposes of the study were (a) to identify an empirical typology of the social networks evident in older Korean immigrants and (b) to examine its association with self-rated health and depressive symptoms. Method. The sample consisted of 1,092 community-dwelling older Korean immigrants in Florida and New York. Latent class analyses were conducted to identify the optimal social network typology based on 8 indicators of interpersonal relationships and activities. Bivariate and multivariate analyses were conducted to examine how the identified social network typology was associated with self-rating of health and depressive symptoms. Results. Results from the latent class analysis identified 6 clusters as being most optimal, and they were named diverse, unmarried/diverse, married/coresidence, family focused, unmarried/restricted, and restricted. Memberships in the clusters of diverse and married/coresidence were significantly associated with more favorable ratings of health and lower levels of depressive symptoms. Discussion. Notably, no distinct network solely composed of friends was identified in the present sample of older immigrants; this may reflect the disruptions in social convoys caused by immigration. The findings of this study promote our understanding of the unique patterns of social connectedness in older immigrants. PMID:23887929

What Motivates Young Adults to Talk About Physical Activity on Social Network Sites?

PubMed Central

Campo, Shelly; Yang, Jingzhen; Eckler, Petya; Snetselaar, Linda; Janz, Kathleen; Leary, Emily

2017-01-01

Background Electronic word-of-mouth on social network sites has been used successfully in marketing. In social marketing, electronic word-of-mouth about products as health behaviors has the potential to be more effective and reach more young adults than health education through traditional mass media. However, little is known about what motivates people to actively initiate electronic word-of-mouth about health behaviors on their personal pages or profiles on social network sites, thus potentially reaching all their contacts on those sites. Objective This study filled the gap by applying a marketing theoretical model to explore the factors associated with electronic word-of-mouth on social network sites about leisure-time physical activity. Methods A Web survey link was sent to undergraduate students at one of the Midwestern universities and 439 of them completed the survey. Results The average age of the 439 participants was 19 years (SD=1 year, range: 18-24). Results suggested that emotional engagement with leisure-time physical activity (ie, affective involvement in leisure-time physical activity) predicted providing relevant opinions or information on social network sites. Social network site users who perceived stronger ties with all their contacts were more likely to provide and seek leisure-time physical activity opinions and information. People who provided leisure-time physical activity opinions and information were more likely to seek opinions and information, and people who forwarded information about leisure-time physical activity were more likely to chat about it. Conclusions This study shed light on the application of the electronic word-of-mouth theoretical framework in promoting health behaviors. The findings can also guide the development of future social marketing interventions using social network sites to promote leisure-time physical activity. PMID:28642215

The Significance of Kinship for Medical Education: Reflections on the Use of a Bespoke Social Network to Support Learners’ Professional Identities

PubMed Central

2016-01-01

Background Social media can support and sustain communities much better than previous generations of learning technologies, where institutional barriers undermined any initiatives for embedding formal and informal learning. Some of the many types of social media have already had an impact on student learning, based on empirical evidence. One of these, social networking, has the potential to support communication in formal and informal spaces. Objective In this paper we report on the evaluation of an institutional social network—King's Social Harmonisation Project (KINSHIP)—established to foster an improved sense of community, enhance communication, and serve as a space to model digital professionalism for students at King’s College London, United Kingdom. Methods Our evaluation focused on a study that examined students’ needs and perceptions with regard to the provision of a cross-university platform. Data were collected from students, including those in the field of health and social care, in order to recommend a practical way forward to address current needs in this area. Results The findings indicate that the majority of the respondents were positive about using a social networking platform to develop their professional voice and profiles. Results suggest that timely promotion of the platform, emphasis on interface and learning design, and a clear identity are required in order to gain acceptance as the institutional social networking site. Conclusions Empirical findings in this study project an advantage of an institutional social network such a KINSHIP over other social networks (eg, Facebook) because access is limited to staff and students and the site is mainly being used for academic purposes. PMID:27731848

Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

NASA Astrophysics Data System (ADS)

Li, Ming-Xia; Palchykov, Vasyl; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

2014-08-01

Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.

Temporal and social contexts of heroin-using populations. An illustration of the snowball sampling technique.

PubMed

Kaplan, C D; Korf, D; Sterk, C

1987-09-01

Snowball sampling is a method that has been used in the social sciences to study sensitive topics, rare traits, personal networks, and social relationships. The method involves the selection of samples utilizing "insider" knowledge and referral chains among subjects who possess common traits that are of research interest. It is especially useful in generating samples for which clinical sampling frames may be difficult to obtain or are biased in some way. In this paper, snowball samples of heroin users in two Dutch cities have been analyzed for the purpose of providing descriptions and limited inferences about the temporal and social contexts of their lifestyles. Two distinct heroin-using populations have been discovered who are distinguished by their life cycle stage. Significant contextual explanations have been found involving the passage from adolescent peer group to criminal occupation, the functioning of network "knots" and "outcroppings," and the frequency of social contact. It is suggested that the snowball sampling method may have utility in studying the temporal and social contexts of other populations of clinical interest.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

Harnessing Online Peer Education (HOPE): integrating C-POL and social media to train peer leaders in HIV prevention.

PubMed

Jaganath, Devan; Gill, Harkiran K; Cohen, Adam Carl; Young, Sean D

2012-01-01

Novel methods, such as Internet-based interventions, are needed to combat the spread of HIV. While past initiatives have used the Internet to promote HIV prevention, the growing popularity, decreasing digital divide, and multi-functionality of social networking sites, such as Facebook, make this an ideal time to develop innovative ways to use online social networking sites to scale HIV prevention interventions among high-risk groups. The UCLA Harnessing Online Peer Education study is a longitudinal experimental study to evaluate the feasibility, acceptability, and preliminary effectiveness of using social media for peer-led HIV prevention, specifically among African American and Latino Men who have Sex with Men (MSM). No curriculum currently exists to train peer leaders in delivering culturally aware HIV prevention messages using social media. Training was created that adapted the Community Popular Opinion Leader (C-POL) model, for use on social networking sites. Peer leaders are recruited who represent the target population and have experience with both social media and community outreach. The curriculum contains the following elements: discussion and role playing exercises to integrate basic knowledge of HIV/AIDS, awareness of sociocultural HIV/AIDS issues in the age of technology, and communication methods for training peer leaders in effective, interactive social media-based HIV prevention. Ethical issues related to Facebook and health interventions are integrated throughout the sessions. Training outcomes have been developed for long-term assessment of retention and efficacy. This is the first C-POL curriculum that has been adapted for use on social networking websites. Although this curriculum has been used to target African-American and Latino MSM, it has been created to allow generalization to other high-risk groups.

Harnessing Online Peer Education (HOPE): Integrating C-POL and Social Media to Train Peer Leaders in HIV Prevention

PubMed Central

Jaganath, Devan; Gill, Harkiran K.; Cohen, Adam Carl; Young, Sean D.

2011-01-01

Novel methods, such as Internet-based interventions, are needed to combat the spread of HIV. While past initiatives have used the Internet to promote HIV prevention, the growing popularity, decreasing digital divide, and multi-functionality of social networking sites, such as Facebook, make this an ideal time to develop innovative ways to use online social networking sites to scale HIV prevention interventions among high-risk groups. The UCLA HOPE [Harnessing Online Peer Education] study is a longitudinal experimental study to evaluate the feasibility, acceptability, and preliminary effectiveness of using social media for peer-led HIV prevention, specifically among African American and Latino Men who have Sex with Men (MSM). No curriculum currently exists to train peer leaders in delivering culturally aware HIV prevention messages using social media. Training was created that adapted the Community Popular Opinion Leader (C-POL) model, for use on social networking sites. Peer leaders are recruited who represent the target population and have experience with both social media and community outreach. The curriculum contains the following elements: discussion and role playing exercises to integrate basic knowledge of HIV/AIDS, awareness of sociocultural HIV/AIDS issues in the age of technology, and communication methods for training peer leaders in effective, interactive social media-based HIV prevention. Ethical issues related to Facebook and health interventions are integrated throughout the sessions. Training outcomes have been developed for long-term assessment of retention and efficacy. This is the first C-POL curriculum that has been adapted for use on social networking websites. Although this curriculum has been used to target African American and Latino MSM, it has been created to allow generalization to other high-risk groups. PMID:22149081

Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

PubMed

Frantz, Terrill L

2012-01-01

This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities. Copyright © 2012 S. Karger AG, Basel.

Bidirectional influence: A longitudinal analysis of size of drug network and depression among inner-city residents in Baltimore, Maryland

PubMed Central

Yang, Jingyan; Latkin, Carl A.; Davey-Rothwell, Melissa

2015-01-01

BACKGROUND The prevalence of depression among drug users is high. It has been recognized that drug use behaviors can be influenced and spread through social networks. OBJECTIVES We investigated the directional relationship between social network factors and depressive symptoms among a sample of inner-city residents in Baltimore, MD. METHODS We performed a longitudinal study of four-wave data collected from a network-based HIV/STI prevention intervention for women and network members, consisting of both men and women. Our primary outcome and exposure were depression using CESD scale and social network characteristics, respectively. Linear mixed model with clustering adjustment was used to account for both repeated measurement and network design. RESULTS Of the 746 participants, those who had high levels of depression tended to be female, less educated, homeless, smokers, and did not have a main partner. In the univariate longitudinal model, larger size of drug network was significantly associated with depression (OR=1.38, p<0.001). This relationship held after controlling for age, gender, homeless in the past six months, college education, having a main partner, cigarette smoking, perceived health, and social support network (aOR=1.19, p=0.001). In the univariate mixed model using depression to predict size of drug network, the data suggested that depression was associated with larger size of drug network (coef.=1.23, p<0.001) and the same relation held in multivariate model (adjusted coef.=1.08, p=0.001). CONCLUSIONS The results suggest that larger size of drug network is a risk factor for depression, and vice versa. Further intervention strategies to reduce depression should address social networks factors. PMID:26584046

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness

PubMed Central

Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-01-01

Background Social network technologies have become part of health education and wider health promotion—either by design or happenstance. Social support, peer pressure, and information sharing in online communities may affect health behaviors. If there are positive and sustained effects, then social network technologies could increase the effectiveness and efficiency of many public health campaigns. Social media alone, however, may be insufficient to promote health. Furthermore, there may be unintended and potentially harmful consequences of inaccurate or misleading health information. Given these uncertainties, there is a need to understand and synthesize the evidence base for the use of online social networking as part of health promoting interventions to inform future research and practice. Objective Our aim was to review the research on the integration of expert-led health promotion interventions with online social networking in order to determine the extent to which the complementary benefits of each are understood and used. We asked, in particular, (1) How is effectiveness being measured and what are the specific problems in effecting health behavior change?, and (2) To what extent is the designated role of social networking grounded in theory? Methods The narrative synthesis approach to literature review was used to analyze the existing evidence. We searched the indexed scientific literature using keywords associated with health promotion and social networking. The papers included were only those making substantial study of both social networking and health promotion—either reporting the results of the intervention or detailing evidence-based plans. General papers about social networking and health were not included. Results The search identified 162 potentially relevant documents after review of titles and abstracts. Of these, 42 satisfied the inclusion criteria after full-text review. Six studies described randomized controlled trials (RCTs) evaluating the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a “social networking condition” in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. Conclusions More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks. PMID:26068087

An exploration of the Facebook social networks of smokers and non-smokers

PubMed Central

2017-01-01

Background Social networks influence health behavior, including tobacco use and cessation. To date, little is known about whether and how the networks of online smokers and non-smokers may differ, or the potential implications of such differences with regards to intervention efforts. Understanding how social networks vary by smoking status could inform public health efforts to accelerate cessation or slow the adoption of tobacco use. Objectives These secondary analyses explore the structure of ego networks of both smokers and non-smokers collected as part of a randomized control trial conducted within Facebook. Methods During the trial, a total of 14,010 individuals installed a Facebook smoking cessation app: 9,042 smokers who were randomized in the trial, an additional 2,881 smokers who did not meet full eligibility criteria, and 2,087 non-smokers. The ego network for all individuals was constructed out to second-degree connections. Four kinds of networks were constructed: friendship, family, photo, and group networks. From these networks we measured edges, isolates, density, mean betweenness, transitivity, and mean closeness. We also measured diameter, clustering, and modularity without ego and isolates. Logistic regressions were performed with smoking status as the response and network metrics as the primary independent variables and demographics and Facebook utilization metrics as covariates. Results The four networks had different characteristics, indicated by different multicollinearity issues and by logistic regression output. Among Friendship networks, the odds of smoking were higher in networks with lower betweenness (p = 0.00), lower transitivity (p = 0.00), and larger diameter (p = 0.00). Among Family networks, the odds of smoking were higher in networks with more vertices (p = .01), less transitivity (p = .04), and fewer isolates (p = .01). Among Photo networks, none of the network metrics were predictive of smoking status. Among Group networks, the odds of smoking were higher when diameter was smaller (p = .04). Together, these findings suggested that compared to non-smokers, smokers in this sample had less connected, more dispersed Facebook Friendship networks; larger but more fractured Family networks with fewer isolates; more compact Group networks; and Photo networks that were similar in network structure to those of non-smokers. Conclusions This study illustrates the importance of examining structural differences in online social networks as a critical component for network-based interventions and lays the foundation for future research that examines the ways that social networks differ based on individual health behavior. Interventions that seek to target the behavior of individuals in the context of their social environment would be well served to understand social network structures of participants. PMID:29095958

How citation distortions create unfounded authority: analysis of a citation network

PubMed Central

2009-01-01

Objective To understand belief in a specific scientific claim by studying the pattern of citations among papers stating it. Design A complete citation network was constructed from all PubMed indexed English literature papers addressing the belief that β amyloid, a protein accumulated in the brain in Alzheimer’s disease, is produced by and injures skeletal muscle of patients with inclusion body myositis. Social network theory and graph theory were used to analyse this network. Main outcome measures Citation bias, amplification, and invention, and their effects on determining authority. Results The network contained 242 papers and 675 citations addressing the belief, with 220 553 citation paths supporting it. Unfounded authority was established by citation bias against papers that refuted or weakened the belief; amplification, the marked expansion of the belief system by papers presenting no data addressing it; and forms of invention such as the conversion of hypothesis into fact through citation alone. Extension of this network into text within grants funded by the National Institutes of Health and obtained through the Freedom of Information Act showed the same phenomena present and sometimes used to justify requests for funding. Conclusion Citation is both an impartial scholarly method and a powerful form of social communication. Through distortions in its social use that include bias, amplification, and invention, citation can be used to generate information cascades resulting in unfounded authority of claims. Construction and analysis of a claim specific citation network may clarify the nature of a published belief system and expose distorted methods of social citation. PMID:19622839

Analysis of Online Social Networks to Understand Information Sharing Behaviors Through Social Cognitive Theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Hong-Jun; Tourassi, Georgia

Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of leaders on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of followers , people who never discussed the topicsmore » before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.« less

The Social Context Network Model in Psychiatric and Neurological Diseases.

PubMed

Baez, Sandra; García, Adolfo M; Ibanez, Agustín

2017-01-01

The role of contextual modulations has been extensively studied in basic sensory and cognitive processes. However, little is known about their impact on social cognition, let alone their disruption in disorders compromising such a domain. In this chapter, we flesh out the social context network model (SCNM), a neuroscientific proposal devised to address the issue. In SCNM terms, social context effects rely on a fronto-temporo-insular network in charge of (a) updating context cues to make predictions, (b) consolidating context-target associative learning, and (c) coordinating internal and external milieus. First, we characterize various social cognition domains as context-dependent phenomena. Then, we review behavioral and neural evidence of social context impairments in behavioral variant frontotemporal dementia (bvFTD) and autism spectrum disorder (ASD), highlighting their relation with key SCNM hubs. Next, we show that other psychiatric and neurological conditions involve context-processing impairments following damage to the brain regions included in the model. Finally, we call for an ecological approach to social cognition assessment, moving beyond widespread abstract and decontextualized methods.

Performance of Social Network Sensors during Hurricane Sandy

PubMed Central

Kryvasheyeu, Yury; Chen, Haohui; Moro, Esteban; Van Hentenryck, Pascal; Cebrian, Manuel

2015-01-01

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the “friendship paradox”, is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users’ network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple “sentiment sensing” technique that can detect and locate disasters. PMID:25692690

Assembling the puzzle for promoting physical activity in Brazil: a social network analysis.

PubMed

Brownson, Ross C; Parra, Diana C; Dauti, Marsela; Harris, Jenine K; Hallal, Pedro C; Hoehner, Christine; Malta, Deborah Carvalho; Reis, Rodrigo S; Ramos, Luiz Roberto; Ribeiro, Isabela C; Soares, Jesus; Pratt, Michael

2010-07-01

Physical inactivity is a significant public health problem in Brazil that may be addressed by partnerships and networks. In conjunction with Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America), the aim of this study was to conduct a social network analysis of physical activity in Brazil. An online survey was completed by 28 of 35 organizations contacted from December 2008 through March 2009. Network analytic methods examined measures of collaboration, importance, leadership, and attributes of the respondent and organization. Leadership nominations for organizations studied ranged from 0 to 23. Positive predictors of collaboration included: south region, GUIA membership, years working in physical activity, and research, education, and promotion/practice areas of physical activity. The most frequently reported barrier to collaboration was bureaucracy. Social network analysis identified factors that are likely to improve collaboration among organizations in Brazil.

Performance of social network sensors during Hurricane Sandy.

PubMed

Kryvasheyeu, Yury; Chen, Haohui; Moro, Esteban; Van Hentenryck, Pascal; Cebrian, Manuel

2015-01-01

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the "friendship paradox", is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users' network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple "sentiment sensing" technique that can detect and locate disasters.

[Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

PubMed

Yoshihara, Chika; Shimizu, Shinji

2005-10-01

The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

[Characteristics of social supportive network serving the older female sex workers in Qingdao].

PubMed

Xu, Y Q; Li, Y F; Jiang, Z X; Zhang, X J; Yuan, X; Zhang, N; Li, X F; Jiang, B F

2016-02-01

To overview the status of social support on older female sex workers (OFSWs) in Qingdao and to better understand the characteristics of this egocentric social support networks. Ucinet 6 software was used to analyze the characteristics of egocentric social networks which involving 400 OFSWs who were recruited by respondent-driven sampling (RDS) method in Qingdao during March 2014 to June. Structural equation model (SEM) was used for data analysis, fitted test and estimation. A total of 400 OFSWs of Qingdao nominated 1 617 social supportive members, and the average size of egocentric social networks of OFSWs was (4.0 ± 1.5). Among all the alter egos (social support network members of the egos), 613 were female sex workers fellows, accounted for the most important part of all the social ties (37.91%). Characteristics of small size and non-relative relationships were seen more obviously among OFSWs with non-local registration and the ratings of emotional support (4.42±2.38) was significantly lower than the tangible support (5.73 ± 1.69) (P<0.05). Result of the SEM showed that homogeneity, joint strength and the network structure were significantly related to the ratings of average support. The total standard effects of which were 0.110, 0.925 and -0.069 respectively. It seemed that homogeneity can affect the degree of support, both directly and indirectly. OFSWs in Qingdao tended to ask for social support from friends who were also female sex workers. Stronger the joint strength between egos and alters, greater the homogeneity between the two was seen. Tighter relations among the alter egos, higher degree of average social support of the egos were acquired.

Building Social Networks for Health Promotion: Shout-out Health, New Jersey, 2011

PubMed Central

Jones, Veronica M.; Storm, Deborah S.; Parrott, J. Scott; O’Brien, Kathy Ahearn

2013-01-01

Background Building social networks for health promotion in high-poverty areas may reduce health disparities. Community involvement provides a mechanism to reach at-risk people with culturally tailored health information. Shout-out Health was a feasibility project to provide opportunity and support for women at risk for or living with human immunodeficiency virus infection to carry out health promotion within their informal social networks. Community Context The Shout-out Health project was designed by an academic–community agency team. During 3 months, health promotion topics were chosen, developed, and delivered to community members within informal social networks by participants living in Paterson and Jersey City, New Jersey. Methods We recruited women from our community agency partner’s clients; 57 women participated in in-person or online meetings facilitated by our team. The participants identified and developed the health topics, and we discussed each topic and checked it for message accuracy before the participants provided health promotion within their informal social networks. The primary outcome for evaluating feasibility included the women’s feedback about their experiences and the number of times they provided health promotion in the community. Other data collection included participant questionnaires and community-recipient evaluations. Outcome More than half of the participants reported substantial life challenges, such as unemployment and housing problems, yet with technical support and a modest stipend, women in both groups successfully provided health promotion to 5,861 people within their informal social networks. Interpretation Shout-out Health was feasible and has implications for building social networks to disseminate health information and reduce health disparities in communities. PMID:23987253

Influence Operations: Redefining the Indirect Approach

DTIC Science & Technology

2011-06-01

companies with JI teachers and preachers to disseminate messages: But the most successful distribution may be by word of mouth . As soon as a book is...unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words ) Across today’s spectrum of contemporary warfare, the human terrain is routinely...indoctrination, and electronic social networks (eSocial networks). Hezbollah and Al Qaeda continue to exemplify these methods. From Indonesia to

Perceptions and Use of Social Networking Sites in the United States and Ecuador: A Mixed-Methods Approach

ERIC Educational Resources Information Center

Pumper, Megan A.; Yaeger, Jeffery P.; Moreno, Megan A.

2013-01-01

Social networking sites are globally popular. In the United States, these types of sites are perceived positively by users and used at high rates, which has likely yielded personal health behavior displays such as substance abuse and depression. Due to possible cultural influence present on these sites, it remains unknown if SNS could be utilized…

Satisfaction with support versus size of network: Differential effects of social support on psychological distress in parents of pediatric cancer patients

PubMed Central

Harper, Felicity W. K.; Peterson, Amy M.; Albrecht, Terrance L.; Taub, Jeffrey W.; Phipps, Sean; Penner, Louis A.

2016-01-01

Objective This study examined the direct and the buffering effects of social support on longer-term global psychological distress among parents coping with pediatric cancer. In both sets of analyses we examined whether these effects depended on the dimension of social support provided (i.e., satisfaction with support versus size of support network). Method Participants were 102 parents of pediatric cancer patients. At study entry, parents reported their trait anxiety, depression, and two dimensions of their social support network (satisfaction with support and size of support network). Parents subsequently reported their psychological distress in 3- and 9-month follow-up assessments. Results Parents’ satisfaction with support had a direct effect on longer-term psychological distress; satisfaction was negatively associated with distress at both follow-ups. In contrast, size of support network buffered (moderated) the impact of trait anxiety and depression on later distress. Parents with smaller support networks and higher levels of trait anxiety and depression at baseline had higher levels of psychological distress at both follow-ups; for parents with larger support networks, there was no relationship. Conclusion Social support can attenuate psychological distress in parents coping with pediatric cancer; however, the nature of the effect depends on the dimension of support. Whereas, interventions that focus on increasing satisfaction with social support may benefit all parents, at-risk parents will likely benefit from interventions that ensure they have an adequate number of support resources. PMID:27092714

Language Networks as Complex Systems

ERIC Educational Resources Information Center

Lee, Max Kueiming; Ou, Sheue-Jen

2008-01-01

Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

PubMed Central

Kondo, Katsunori; Yamamoto, Tatsuo; Saito, Masashige; Ito, Kanade; Suzuki, Kayo; Osaka, Ken; Kawachi, Ichiro

2016-01-01

Background We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors. Methods Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10–19, 1–9, and 0). Results Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04–1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02–1.08)). Conclusion Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss. PMID:27459102

Post-stroke social networks, depressive symptoms, and disability in Tanzania: A prospective study.

PubMed

Saadi, Altaf; Okeng'o, Kigocha; Biseko, Maijo R; Shayo, Agness F; Mmbando, Theoflo N; Grundy, Sara J; Xu, Ai; Parker, Robert A; Wibecan, Leah; Iyer, Geetha; Onesmo, Peter M; Kapina, Boniphace N; Regenhardt, Robert W; Mateen, Farrah J

2018-01-01

Background Evidence suggests that social networks improve functional recovery after stroke, but this work has not been extended to low- and middle-income countries (LMICs). Post-stroke depression interferes with functional outcome but is understudied in LMICs. Aims To determine the relationships between social networks, disability, and depressive symptoms in patients surviving 90-days post-stroke in Dar es Salaam, Tanzania. Methods Participants ≥ 18 years, admitted ≤ 14 days of stroke onset, were enrolled. Disability was measured using the modified Rankin Scale, social networks by the Berkman-Syme social network index, and depressive symptoms by the Patient Health Questionnaire-9 (PHQ-9) by telephone interview at 90 days. A Kruskal-Wallis test or Spearman's correlation coefficient was used to assess the associations between social networks, depressive symptoms, and disability. Results Of 176 participants, 43% (n = 75) died, with an additional 11% (n = 20) lost to follow-up by 90 days. Among 81 survivors, 94% (n = 76, 57% male, average age 54 years) had complete information on all scales (mean and median follow-up time of 101 and 88 days). Thirty percent (n = 23, 41.9%, 95% confidence interval 20.2) had at least mild depressive symptoms (PHQ-9 ≥ 5 points). Nearly two-thirds (n = 46, 61%) reported ≥ 3 close friends. A higher social network index score was associated with fewer depressive symptoms (p < 0.0001) and showed a trend towards significance with lower disability (p = 0.061). Higher depressive symptom burden was correlated with higher disability (r = 0.52, p < 0.0001). Conclusion Post-stroke social isolation is associated with more depressive symptoms in Tanzania. Understanding social networks and the associated mechanisms of recovery in stroke is especially relevant in the context of limited resources.

Social management of laboratory rhesus macaques housed in large groups using a network approach: A review.

PubMed

McCowan, Brenda; Beisner, Brianne; Hannibal, Darcy

2017-12-07

Biomedical facilities across the nation and worldwide aim to develop cost-effective methods for the reproductive management of macaque breeding groups, typically by housing macaques in large, multi-male multi-female social groups that provide monkey subjects for research as well as appropriate socialization for their psychological well-being. One of the most difficult problems in managing socially housed macaques is their propensity for deleterious aggression. From a management perspective, deleterious aggression (as opposed to less intense aggression that serves to regulate social relationships) is undoubtedly the most problematic behavior observed in group-housed macaques, which can readily escalate to the degree that it causes social instability, increases serious physical trauma leading to group dissolution, and reduces psychological well-being. Thus for both welfare and other management reasons, aggression among rhesus macaques at primate centers and facilities needs to be addressed with a more proactive approach.Management strategies need to be instituted that maximize social housing while also reducing problematic social aggression due to instability using efficacious methods for detection and prevention in the most cost effective manner. Herein we review a new proactive approach using social network analysis to assess and predict deleterious aggression in macaque groups. We discovered three major pathways leading to instability, such as unusually high rates and severity of trauma and social relocations.These pathways are linked either directly or indirectly to network structure in rhesus macaque societies. We define these pathways according to the key intrinsic and extrinsic variables (e.g., demographic, genetic or social factors) that influence network and behavioral measures of stability (see Fig. 1). They are: (1) presence of natal males, (2) matrilineal genetic fragmentation, and (3) the power structure and conflict policing behavior supported by this power structure. We discuss how these three major pathways leading to greater understanding and predictability of deleterious aggression in macaque social groups. Copyright © 2017. Published by Elsevier B.V.

An Examination of Research Collaboration in Psychometrics Utilizing Social Network Analysis Methods

ERIC Educational Resources Information Center

DiCrecchio, Nicole C.

2016-01-01

Co-authorship networks have been studied in many fields as a way to understand collaboration patterns. However, a comprehensive exploration of the psychometrics field has not been conducted. Also, few studies on co-author networks have included longitudinal analyses as well as data on the characteristics of authors in the network. Including both…

Go Ask Alice: Uncovering the Role of a University Partner in an Informal Science Curriculum Support Network

ERIC Educational Resources Information Center

Baker-Doyle, Kira J.

2013-01-01

This article describes a study from the Linking Instructors Networks of Knowledge in Science Education project, which aims to examine the informal science curriculum support networks of teachers in a school-university curriculum reform partnership. We used social network analysis and qualitative methods to reveal characteristics of the informal…

Human communication dynamics in digital footsteps: a study of the agreement between self-reported ties and email networks.

PubMed

Wuchty, Stefan; Uzzi, Brian

2011-01-01

Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's "social network" of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions.

Social network analysis identified central outcomes for core outcome sets using systematic reviews of HIV/AIDS.

PubMed

Saldanha, Ian J; Li, Tianjing; Yang, Cui; Ugarte-Gil, Cesar; Rutherford, George W; Dickersin, Kay

2016-02-01

Methods to develop core outcome sets, the minimum outcomes that should be measured in research in a topic area, vary. We applied social network analysis methods to understand outcome co-occurrence patterns in human immunodeficiency virus (HIV)/AIDS systematic reviews and identify outcomes central to the network of outcomes in HIV/AIDS. We examined all Cochrane reviews of HIV/AIDS as of June 2013. We defined a tie as two outcomes (nodes) co-occurring in ≥2 reviews. To identify central outcomes, we used normalized node betweenness centrality (nNBC) (the extent to which connections between other outcomes in a network rely on that outcome as an intermediary). We conducted a subgroup analysis by HIV/AIDS intervention type (i.e., clinical management, biomedical prevention, behavioral prevention, and health services). The 140 included reviews examined 1,140 outcomes, 294 of which were unique. The most central outcome overall was all-cause mortality (nNBC = 23.9). The most central and most frequent outcomes differed overall and within subgroups. For example, "adverse events (specified)" was among the most central but not among the most frequent outcomes, overall. Social network analysis methods are a novel application to identify central outcomes, which provides additional information potentially useful for developing core outcome sets. Copyright © 2016 Elsevier Inc. All rights reserved.

Association of tuberculosis with multimorbidity and social networks

PubMed Central

Valenzuela-Jiménez, Hiram; Manrique-Hernández, Edgar Fabian; Idrovo, Alvaro Javier

2017-01-01

ABSTRACT The combination of tuberculosis with other diseases can affect tuberculosis treatment within populations. In the present study, social network analysis of data retrieved from the Mexican National Epidemiological Surveillance System was used in order to explore associations between the number of contacts and multimorbidity. The node degree was calculated for each individual with tuberculosis and included information from 242 contacts without tuberculosis. Multimorbidity was identified in 49.89% of individuals. The node degrees were highest for individuals with tuberculosis + HIV infection (p < 0.04) and lowest for those with tuberculosis + pulmonary edema (p < 0.07). Social network analysis should be used as a standard method for monitoring tuberculosis and tuberculosis-related syndemics. PMID:28125153

Rumor spreading in online social networks by considering the bipolar social reinforcement

NASA Astrophysics Data System (ADS)

Ma, Jing; Li, Dandan; Tian, Zihao

2016-04-01

Considering the bipolar social reinforcement which includes positive and negative effects, in this paper we explore the rumor spreading dynamics in online social networks. By means of the generation function and cavity method developed from statistical physics of disordered system, the rumor spreading threshold can be theoretically drawn. Simulation results indicate that decreasing the positive reinforcement factor or increasing the negative reinforcement factor can suppress the rumor spreading effectively. By analyzing the topological properties of the real world social network, we find that the nodes with lower degree usually have smaller weight. However, the nodes with lower degree may have larger k-shell. In order to curb rumor spreading, some control strategies that are based on the nodes' degree, k-shell and weight are presented. By comparison, we show that controlling those nodes that have larger degree or weight are two effective strategies to prevent the rumor spreading.

Sexual risk and HIV prevention behaviours among African-American and Latino MSM social networking users.

PubMed

Young, Sean D; Szekeres, Greg; Coates, Thomas

2013-08-01

This study explores the feasibility of recruiting minority men who have sex with men Facebook users for human immunodeficiency virus (HIV) prevention studies and notes demographic and sexual risk behaviours. Facebook-registered men who have sex with men (MSM; N = 118) were recruited using online and offline methods. Participants validated Facebook-user status through using a Facebook Connect (computer science) application. Participants were primarily Latino (60.2%) and African-American (28.0%), with 33.1% using social media to find sex partners. Black MSM social networking users reported engaging in a lower frequency (coefficient = -0.48, p < 0.05) of unprotected receptive anal intercourse compared to Latino MSM. Results suggest that minority social media users can be recruited for HIV studies and that sexual risk behavioural differences exist among minority social networking users. Findings highlight the importance of incorporating technologies into population-focused HIV interventions.

Optimal information dissemination strategy to promote preventive behaviors in multilayer epidemic networks.

PubMed

Shakeri, Heman; Sahneh, Faryad Darabi; Scoglio, Caterina; Poggi-Corradini, Pietro; Preciado, Victor M

2015-06-01

Launching a prevention campaign to contain the spread of infection requires substantial financial investments; therefore, a trade-off exists between suppressing the epidemic and containing costs. Information exchange among individuals can occur as physical contacts (e.g., word of mouth, gatherings), which provide inherent possibilities of disease transmission, and non-physical contacts (e.g., email, social networks), through which information can be transmitted but the infection cannot be transmitted. Contact network (CN) incorporates physical contacts, and the information dissemination network (IDN) represents non-physical contacts, thereby generating a multilayer network structure. Inherent differences between these two layers cause alerting through CN to be more effective but more expensive than IDN. The constraint for an epidemic to die out derived from a nonlinear Perron-Frobenius problem that was transformed into a semi-definite matrix inequality and served as a constraint for a convex optimization problem. This method guarantees a dying-out epidemic by choosing the best nodes for adopting preventive behaviors with minimum monetary resources. Various numerical simulations with network models and a real-world social network validate our method.

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras.

PubMed

Shakya, Holly B; Stafford, Derek; Hughes, D Alex; Keegan, Thomas; Negron, Rennie; Broome, Jai; McKnight, Mark; Nicoll, Liza; Nelson, Jennifer; Iriarte, Emma; Ordonez, Maria; Airoldi, Edo; Fowler, James H; Christakis, Nicholas A

2017-03-13

Despite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change. We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions. The Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a 'toolkit' for practitioners to use in network-based intervention efforts, including public release of our network mapping software. NCT02694679; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

PubMed

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction: Metabolic networks (72.3%), Parasite-Host networks (93.3%), CoCoMac brain cortex co-activation network (89.6%), NW Spain fasciolosis spreading network (97.2%), Spanish financial law network (89.9%) and World trade network for Intelligent & Active Food Packaging (92.8%). In order to seek these models, we studied an average of 55,388 pairs of nodes in each model and a total of 332,326 pairs of nodes in all models. Finally, this method was used to solve a more complicated problem. A model was developed to score the connectivity quality in the Drug-Target network of US FDA approved drugs. In this last model the θ(k) values were calculated for three types of molecular networks representing different levels of organization: drug molecular graphs (atom-atom bonds), protein residue networks (amino acid interactions), and drug-target network (compound-protein binding). The overall accuracy of this model was 76.3%. This work opens a new door to the computational reevaluation of network connectivity quality (collation) for complex systems in molecular, biomedical, technological, and legal-social sciences as well as in world trade and industry. Copyright © 2011 Elsevier Ltd. All rights reserved.

Use of a mobile social networking intervention for weight management: a mixed-methods study protocol.

PubMed

Laranjo, Liliana; Lau, Annie Y S; Martin, Paige; Tong, Huong Ly; Coiera, Enrico

2017-07-12

Obesity and physical inactivity are major societal challenges and significant contributors to the global burden of disease and healthcare costs. Information and communication technologies are increasingly being used in interventions to promote behaviour change in diet and physical activity. In particular, social networking platforms seem promising for the delivery of weight control interventions.We intend to pilot test an intervention involving the use of a social networking mobile application and tracking devices ( Fitbit Flex 2 and Fitbit Aria scale) to promote the social comparison of weight and physical activity, in order to evaluate whether mechanisms of social influence lead to changes in those outcomes over the course of the study. Mixed-methods study involving semi-structured interviews and a pre-post quasi-experimental pilot with one arm, where healthy participants in different body mass index (BMI) categories, aged between 19 and 35 years old, will be subjected to a social networking intervention over a 6-month period. The primary outcome is the average difference in weight before and after the intervention. Secondary outcomes include BMI, number of steps per day, engagement with the intervention, social support and system usability. Semi-structured interviews will assess participants' expectations and perceptions regarding the intervention. Ethics approval was granted by Macquarie University's Human Research Ethics Committee for Medical Sciences on 3 November 2016 (ethics reference number 5201600716).The social network will be moderated by a researcher with clinical expertise, who will monitor and respond to concerns raised by participants. Monitoring will involve daily observation of measures collected by the fitness tracker and the wireless scale, as well as continuous supervision of forum interactions and posts. Additionally, a protocol is in place to monitor for participant misbehaviour and direct participants-in-need to appropriate sources of help. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Rapid innovation diffusion in social networks.

PubMed

Kreindler, Gabriel E; Young, H Peyton

2014-07-22

Social and technological innovations often spread through social networks as people respond to what their neighbors are doing. Previous research has identified specific network structures, such as local clustering, that promote rapid diffusion. Here we derive bounds that are independent of network structure and size, such that diffusion is fast whenever the payoff gain from the innovation is sufficiently high and the agents' responses are sufficiently noisy. We also provide a simple method for computing an upper bound on the expected time it takes for the innovation to become established in any finite network. For example, if agents choose log-linear responses to what their neighbors are doing, it takes on average less than 80 revision periods for the innovation to diffuse widely in any network, provided that the error rate is at least 5% and the payoff gain (relative to the status quo) is at least 150%. Qualitatively similar results hold for other smoothed best-response functions and populations that experience heterogeneous payoff shocks.

Rapid innovation diffusion in social networks

PubMed Central

Kreindler, Gabriel E.; Young, H. Peyton

2014-01-01

Social and technological innovations often spread through social networks as people respond to what their neighbors are doing. Previous research has identified specific network structures, such as local clustering, that promote rapid diffusion. Here we derive bounds that are independent of network structure and size, such that diffusion is fast whenever the payoff gain from the innovation is sufficiently high and the agents’ responses are sufficiently noisy. We also provide a simple method for computing an upper bound on the expected time it takes for the innovation to become established in any finite network. For example, if agents choose log-linear responses to what their neighbors are doing, it takes on average less than 80 revision periods for the innovation to diffuse widely in any network, provided that the error rate is at least 5% and the payoff gain (relative to the status quo) is at least 150%. Qualitatively similar results hold for other smoothed best-response functions and populations that experience heterogeneous payoff shocks. PMID:25024191

Collective learning for the emergence of social norms in networked multiagent systems.

PubMed

Yu, Chao; Zhang, Minjie; Ren, Fenghui

2014-12-01

Social norms such as social rules and conventions play a pivotal role in sustaining system order by regulating and controlling individual behaviors toward a global consensus in large-scale distributed systems. Systematic studies of efficient mechanisms that can facilitate the emergence of social norms enable us to build and design robust distributed systems, such as electronic institutions and norm-governed sensor networks. This paper studies the emergence of social norms via learning from repeated local interactions in networked multiagent systems. A collective learning framework, which imitates the opinion aggregation process in human decision making, is proposed to study the impact of agent local collective behaviors on the emergence of social norms in a number of different situations. In the framework, each agent interacts repeatedly with all of its neighbors. At each step, an agent first takes a best-response action toward each of its neighbors and then combines all of these actions into a final action using ensemble learning methods. Extensive experiments are carried out to evaluate the framework with respect to different network topologies, learning strategies, numbers of actions, influences of nonlearning agents, and so on. Experimental results reveal some significant insights into the manipulation and control of norm emergence in networked multiagent systems achieved through local collective behaviors.

Role of Social Media in Diabetes Management in the Middle East Region: Systematic Review

PubMed Central

2018-01-01

Background Diabetes is a major health care burden in the Middle East region. Social networking tools can contribute to the management of diabetes with improved educational and care outcomes using these popular tools in the region. Objective The objective of this review was to evaluate the impact of social networking interventions on the improvement of diabetes management and health outcomes in patients with diabetes in the Middle East. Methods Peer-reviewed articles from PubMed (1990-2017) and Google Scholar (1990-2017) were identified using various combinations of predefined terms and search criteria. The main inclusion criterion consisted of the use of social networking apps on mobile phones as the primary intervention. Outcomes were grouped according to study design, type of diabetes, category of technological intervention, location, and sample size. Results This review included 5 articles evaluating the use of social media tools in the management of diabetes in the Middle East. In most studies, the acceptance rate for the use of social networking to optimize the management of diabetes was relatively high. Diabetes-specific management tools such as the Saudi Arabia Networking for Aiding Diabetes and Diabetes Intelligent Management System for Iraq systems helped collect patient information and lower hemoglobin A1c (HbA1c) levels, respectively. Conclusions The reviewed studies demonstrated the potential of social networking tools being adopted in regions in the Middle East to improve the management of diabetes. Future studies consisting of larger sample sizes spanning multiple regions would provide further insight into the use of social media for improving patient outcomes. PMID:29439941

Reinterpretaion of the friendship paradox

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

The friendship paradox (FP) is a sociological phenomenon stating that most people have fewer friends than their friends do. It is to say that in a social network, the number of friends that most individuals have is smaller than the average number of friends of friends. This has been verified by Feld. We call this interpreting method mean value version. But is it the best choice to portray the paradox? In this paper, we propose a probability method to reinterpret this paradox, and we illustrate that the explanation using our method is more persuasive. An individual satisfies the FP if his (her) randomly chosen friend has more friends than him (her) with probability not less than 1/2. Comparing the ratios of nodes satisfying the FP in networks, rp, we can see that the probability version is stronger than the mean value version in real networks both online and offline. We also show some results about the effects of several parameters on rp in random network models. Most importantly, rp is a quadratic polynomial of the power law exponent γ in Price model, and rp is higher when the average clustering coefficient is between 0.4 and 0.5 in Petter-Beom (PB) model. The introduction of the probability method to FP can shed light on understanding the network structure in complex networks especially in social networks.

Fitting ERGMs on big networks.

PubMed

An, Weihua

2016-09-01

The exponential random graph model (ERGM) has become a valuable tool for modeling social networks. In particular, ERGM provides great flexibility to account for both covariates effects on tie formations and endogenous network formation processes. However, there are both conceptual and computational issues for fitting ERGMs on big networks. This paper describes a framework and a series of methods (based on existent algorithms) to address these issues. It also outlines the advantages and disadvantages of the methods and the conditions to which they are most applicable. Selected methods are illustrated through examples. Copyright © 2016 Elsevier Inc. All rights reserved.

Community structure in networks

NASA Astrophysics Data System (ADS)

Newman, Mark

2004-03-01

Many networked systems, including physical, biological, social, and technological networks, appear to contain ``communities'' -- groups of nodes within which connections are dense, but between which they are sparser. The ability to find such communities in an automated fashion could be of considerable use. Communities in a web graph for instance might correspond to sets of web sites dealing with related topics, while communities in a biochemical network or an electronic circuit might correspond to functional units of some kind. We present a number of new methods for community discovery, including methods based on ``betweenness'' measures and methods based on modularity optimization. We also give examples of applications of these methods to both computer-generated and real-world network data, and show how our techniques can be used to shed light on the sometimes dauntingly complex structure of networked systems.

Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

Characteristics of Socially Successful Elementary School-Aged Children with Autism

PubMed Central

Locke, Jill; Williams, Justin; Shih, Wendy; Kasari, Connie

2016-01-01

Background The extant literature demonstrates that children with autism spectrum disorder (ASD) often have difficulty interacting and socially connecting with typically developing classmates. However, some children with ASD have social outcomes that are consistent with their typically developing counterparts. Little is known about this subgroup of children with ASD. This study examined the stable (unlikely to change) and malleable (changeable) characteristics of socially successful children with ASD. Methods This study used baseline data from three intervention studies performed in public schools in the Southwestern United States. A total of 148 elementary-aged children with ASD in 130 classrooms in 47 public schools participated. Measures of playground peer engagement and social network salience (inclusion in informal peer groups) were obtained. Results The results demonstrated that a number of malleable factors significantly predicted playground peer engagement (class size, autism symptom severity, peer connections) and social network salience (autism symptom severity, peer connections, received friendships). In addition, age was the only stable factor that significantly predicted social network salience. Interestingly, two malleable (i.e., peer connections and received friendships) and no stable factors (i.e., age, IQ, sex) predicted overall social success (e.g., high playground peer engagement and social network salience) in children with ASD. Conclusions School-based interventions should address malleable factors such as the number of peer connections and received friendships that predict the best social outcomes for children with ASD. PMID:27620949

Information seeking for making evidence-informed decisions: a social network analysis on the staff of a public health department in Canada

PubMed Central

2012-01-01

Background Social network analysis is an approach to study the interactions and exchange of resources among people. It can help understanding the underlying structural and behavioral complexities that influence the process of capacity building towards evidence-informed decision making. A social network analysis was conducted to understand if and how the staff of a public health department in Ontario turn to peers to get help incorporating research evidence into practice. Methods The staff were invited to respond to an online questionnaire inquiring about information seeking behavior, identification of colleague expertise, and friendship status. Three networks were developed based on the 170 participants. Overall shape, key indices, the most central people and brokers, and their characteristics were identified. Results The network analysis showed a low density and localized information-seeking network. Inter-personal connections were mainly clustered by organizational divisions; and people tended to limit information-seeking connections to a handful of peers in their division. However, recognition of expertise and friendship networks showed more cross-divisional connections. Members of the office of the Medical Officer of Health were located at the heart of the department, bridging across divisions. A small group of professional consultants and middle managers were the most-central staff in the network, also connecting their divisions to the center of the information-seeking network. In each division, there were some locally central staff, mainly practitioners, who connected their neighboring peers; but they were not necessarily connected to other experts or managers. Conclusions The methods of social network analysis were useful in providing a systems approach to understand how knowledge might flow in an organization. The findings of this study can be used to identify early adopters of knowledge translation interventions, forming Communities of Practice, and potential internal knowledge brokers. PMID:22591757

Developing community networks to deliver HIV prevention interventions.

PubMed Central

Guenther-Grey, C; Noroian, D; Fonseka, J; Higgins, D

1996-01-01

Outreach has a long history in health and social service programs as an important method for reaching at-risk persons within their communities. One method of "outreach" is based on the recruitment of networks of community members (or "networkers") to deliver HIV prevention messages and materials in the context of their social networks and everyday lives. This paper documents the experiences of the AIDS Community Demonstration Projects in recruiting networkers to deliver HIV prevention interventions to high-risk populations, including injecting drug users not in treatment; female sex partners of injecting drug users; female sex traders; men who have sex with men but do not self-identify as gay; and youth in high-risk situations. The authors interviewed project staff and reviewed project records of the implementation of community networks in five cities. Across cities, the projects successfully recruited persons into one or more community networks to distribute small media materials, condoms, and bleach kits, and encourage risk-reduction behaviors among community members. Networkers' continuing participation was enlisted through a variety of monetary and nonmonetary incentives. While continuous recruitment of networkers was necessary due to attrition, most interventions reported maintaining a core group of networkers. In addition, the projects appeared to serve as a starting point for some networkers to become more active in other community events and issues. PMID:8862156

A trust-based recommendation method using network diffusion processes

NASA Astrophysics Data System (ADS)

Chen, Ling-Jiao; Gao, Jian

2018-09-01

A variety of rating-based recommendation methods have been extensively studied including the well-known collaborative filtering approaches and some network diffusion-based methods, however, social trust relations are not sufficiently considered when making recommendations. In this paper, we contribute to the literature by proposing a trust-based recommendation method, named CosRA+T, after integrating the information of trust relations into the resource-redistribution process. Specifically, a tunable parameter is used to scale the resources received by trusted users before the redistribution back to the objects. Interestingly, we find an optimal scaling parameter for the proposed CosRA+T method to achieve its best recommendation accuracy, and the optimal value seems to be universal under several evaluation metrics across different datasets. Moreover, results of extensive experiments on the two real-world rating datasets with trust relations, Epinions and FriendFeed, suggest that CosRA+T has a remarkable improvement in overall accuracy, diversity and novelty. Our work takes a step towards designing better recommendation algorithms by employing multiple resources of social network information.

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth.

PubMed

Andina-Diaz, Elena; Ovalle-Perandones, Mª Antonia; Ramos-Vidal, Ignacio; Camacho-Morell, Francisca; Siles-Gonzalez, Jose; Marques-Sanchez, Pilar

2018-04-24

Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health.

A cloud-based forensics tracking scheme for online social network clients.

PubMed

Lin, Feng-Yu; Huang, Chien-Cheng; Chang, Pei-Ying

2015-10-01

In recent years, with significant changes in the communication modes, most users are diverted to cloud-based applications, especially online social networks (OSNs), which applications are mostly hosted on the outside and available to criminals, enabling them to impede criminal investigations and intelligence gathering. In the virtual world, how the Law Enforcement Agency (LEA) identifies the "actual" identity of criminal suspects, and their geolocation in social networks, is a major challenge to current digital investigation. In view of this, this paper proposes a scheme, based on the concepts of IP location and network forensics, which aims to develop forensics tracking on OSNs. According to our empirical analysis, the proposed mechanism can instantly trace the "physical location" of a targeted service resource identifier (SRI), when the target client is using online social network applications (Facebook, Twitter, etc.), and can analyze the probable target client "identity" associatively. To the best of our knowledge, this is the first individualized location method and architecture developed and evaluated in OSNs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results

PubMed Central

Anil Kumar, V.S.; Marathe, Madhav V.; Ravi, S.S.; Rosenkrantz, Daniel J.

2014-01-01

We consider the problem of inhibiting undesirable contagions (e.g. rumors, spread of mob behavior) in social networks. Much of the work in this context has been carried out under the 1-threshold model, where diffusion occurs when a node has just one neighbor with the contagion. We study the problem of inhibiting more complex contagions in social networks where nodes may have thresholds larger than 1. The goal is to minimize the propagation of the contagion by removing a small number of nodes (called critical nodes) from the network. We study several versions of this problem and prove that, in general, they cannot even be efficiently approximated to within any factor ρ ≥ 1, unless P = NP. We develop efficient and practical heuristics for these problems and carry out an experimental study of their performance on three well known social networks, namely epinions, wikipedia and slashdot. Our results show that these heuristics perform significantly better than five other known methods. We also establish an efficiently computable upper bound on the number of nodes to which a contagion can spread and evaluate this bound on many real and synthetic networks. PMID:25750583

Gender differences in the association of perceived social support and social network with self-rated health status among older adults: a population-based study in Brazil

PubMed Central

2013-01-01

Background Older adults are more likely to live alone, because they may have been predeceased by their spouse and friends. Social interaction could also be reduced in this age group due by limited mobility caused by chronic conditions. Therefore, aging is frequently accompanied by reduced social support, which might affect health status. Little is known about the role of gender in the relationship between social support and health in older adults. Hence, the present study tests the hypothesis that gender differences exist in the relationship between perceived social support, social network, and self-rated health (SRH) among older adults. Methods A cross-sectional study using two-stage probabilistic sampling recruited 3,649 individuals aged 60 years and above. Data were collected during the national influenza vaccination campaign in Rio de Janeiro, Brazil, in 2006. Individual interviews collected information on SRH, perceived social support, social network, and other covariates. Multivariate logistic regression analyses using nested models were conducted separately for males and females. Independent variables were organised into six blocks: (1) perceived social support and social network, (2) age group, (3) socioeconomic characteristics, (4) health-related behaviours, (5) use of health care services, (6) functional status measures and somatic health problems. Results Older men who did not participate in group activities were more likely to report poor SRH compared to those who did, (OR = 1.63; 95% CI = 1.16–2.30). Low perceived social support predicted the probability of poor SRH in women (OR = 1.64; 95% CI = 1.16–2.34). Poor SRH was associated with low age, low income, not working, poor functional capacity, and depression in both men and women. More somatic health problems were associated with poor SRH in women. Conclusions The association between social interactions and SRH varies between genders. Low social network involvement is associated with poor SRH in older men, whereas low perceived social support is associated with poor SRH in older women. The hypothesis that the relationship of perceived social support and social networks to SRH differs according to gender has been confirmed. PMID:24229389

Sexual network analysis of a gonorrhoea outbreak

PubMed Central

De, P; Singh, A; Wong, T; Yacoub, W; Jolly, A

2004-01-01

Objectives: Sexual partnerships can be viewed as networks in order to study disease transmission. We examined the transmission of Neisseria gonorrhoeae in a localised outbreak in Alberta, Canada, using measures of network centrality to determine the association between risk of infection of network members and their position within the sexual network. We also compared risk in smaller disconnected components with a large network centred on a social venue. Methods: During the investigation of the outbreak, epidemiological data were collected on gonorrhoea cases and their sexual contacts from STI surveillance records. In addition to traditional contact tracing information, subjects were interviewed about social venues they attended in the past year where casual sexual partnering may have occurred. Sexual networks were constructed by linking together named partners. Univariate comparisons of individual network member characteristics and algebraic measures of network centrality were completed. Results: The sexual networks consisted of 182 individuals, of whom 107 were index cases with laboratory confirmed gonorrhoea and 75 partners of index cases. People who had significantly higher information centrality within each of their local networks were found to have patronised a popular motel bar in the main town in the region (p = 0.05). When the social interaction through the bar was considered, a large network of 89 individuals was constructed that joined all eight of the largest local networks. Moreover, several networks from different communities were linked by individuals who served as bridge populations as a result of their sexual partnering. Conclusion: Asking clients about particular social venues emphasised the importance of location in disease transmission. Network measures of centrality, particularly information centrality, allowed the identification of key individuals through whom infection could be channelled into local networks. Such individuals would be ideal targets for increased interventions. PMID:15295126

The social network of international health aid.

PubMed

Han, Lu; Koenig-Archibugi, Mathias; Opsahl, Tore

2018-06-01

International development assistance for health generates an emergent social network in which policy makers in recipient countries are connected to numerous bilateral and multilateral aid agencies and to other aid recipients. Ties in this global network are channels for the transmission of knowledge, norms and influence in addition to material resources, and policy makers in centrally situated governments receive information faster and are exposed to a more diverse range of sources and perspectives. Since diversity of perspectives improves problem-solving capacity, the structural position of aid-receiving governments in the health aid network can affect the health outcomes that those governments are able to attain. We apply a recently developed Social Network Analysis measure to health aid data for 1990-2010 to investigate the relationship between country centrality in the health aid network and improvements in child health. A generalized method of moments (GMM) analysis indicates that, controlling for the volume of health aid and other factors, higher centrality in the health aid network is associated with better child survival rates in a sample of 110 low and middle income countries. Copyright © 2018 Elsevier Ltd. All rights reserved.

Descriptive and Injunctive Network Norms Associated with Non Medical Use of Prescription Drugs among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2016-01-01

Background Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. Methods 1,046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Results Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Conclusions Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths’ perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. PMID:27563741

Social network approaches to leadership: an integrative conceptual review.

PubMed

Carter, Dorothy R; DeChurch, Leslie A; Braun, Michael T; Contractor, Noshir S

2015-05-01

Contemporary definitions of leadership advance a view of the phenomenon as relational, situated in specific social contexts, involving patterned emergent processes, and encompassing both formal and informal influence. Paralleling these views is a growing interest in leveraging social network approaches to study leadership. Social network approaches provide a set of theories and methods with which to articulate and investigate, with greater precision and rigor, the wide variety of relational perspectives implied by contemporary leadership theories. Our goal is to advance this domain through an integrative conceptual review. We begin by answering the question of why-Why adopt a network approach to study leadership? Then, we offer a framework for organizing prior research. Our review reveals 3 areas of research, which we term: (a) leadership in networks, (b) leadership as networks, and (c) leadership in and as networks. By clarifying the conceptual underpinnings, key findings, and themes within each area, this review serves as a foundation for future inquiry that capitalizes on, and programmatically builds upon, the insights of prior work. Our final contribution is to advance an agenda for future research that harnesses the confluent ideas at the intersection of leadership in and as networks. Leadership in and as networks represents a paradigm shift in leadership research-from an emphasis on the static traits and behaviors of formal leaders whose actions are contingent upon situational constraints, toward an emphasis on the complex and patterned relational processes that interact with the embedding social context to jointly constitute leadership emergence and effectiveness. (c) 2015 APA, all rights reserved.

Mapping the online communication patterns of political conversations

NASA Astrophysics Data System (ADS)

Borondo, J.; Morales, A. J.; Benito, R. M.; Losada, J. C.

2014-11-01

The structure of the social networks in which individuals are embedded influences their political choices and therefore their voting behavior. Nowadays, social media represent a new channel for individuals to communicate, what together with the availability of the data, makes it possible to analyze the online social network resulting from political conversations. Here, by taking advantage of the recently developed techniques to analyze complex systems, we map the communication patterns resulting from Spanish political conversations. We identify the different existing communities, building networks of communities, and finding that users cluster themselves in politically homogeneous networks. We found that while most of the collective attention was monopolized by politicians, traditional media accounts were still the preferred sources from which to propagate information. Finally, we propose methods to analyze the use of different languages, finding a clear trend from sympathizers of several political parties to overuse or infra-use each language. We conclude that, on the light of a social media analysis perspective, the political conversation is constrained by both ideology and language.

[Health system sustainability from a network perspective: a proposal to optimize healthy habits and social support].

PubMed

Marqués Sánchez, Pilar; Fernández Peña, Rosario; Cabrera León, Andrés; Muñoz Doyague, María F; Llopis Cañameras, Jaime; Arias Ramos, Natalia

2013-01-01

The search of new health management formulas focused to give wide services is one of the priorities of our present health policies. Those formulas examine the optimization of the links between the main actors involved in public health, ie, users, professionals, local socio-political and corporate agents. This paper is aimed to introduce the Social Network Analysis as a method for analyzing, measuring and interpreting those connections. The knowledge of people's relationships (what is called social networks) in the field of public health is becoming increasingly important at an international level. In fact, countries such as UK, Netherlands, Italy, Australia and U.S. are looking formulas to apply this knowledge to their health departments. With this work we show the utility of the ARS on topics related to sustainability of the health system, particularly those related with health habits and social support, topics included in the 2020 health strategies that underline the importance of the collaborative aspects in networks.

Self-presentation 2.0: narcissism and self-esteem on Facebook.

PubMed

Mehdizadeh, Soraya

2010-08-01

Online social networking sites have revealed an entirely new method of self-presentation. This cyber social tool provides a new site of analysis to examine personality and identity. The current study examines how narcissism and self-esteem are manifested on the social networking Web site Facebook.com . Self-esteem and narcissistic personality self-reports were collected from 100 Facebook users at York University. Participant Web pages were also coded based on self-promotional content features. Correlation analyses revealed that individuals higher in narcissism and lower in self-esteem were related to greater online activity as well as some self-promotional content. Gender differences were found to influence the type of self-promotional content presented by individual Facebook users. Implications and future research directions of narcissism and self-esteem on social networking Web sites are discussed.

Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members.

PubMed

Pollet, Thomas V; Roberts, Sam G B; Dunbar, Robin I M

2011-04-01

The effect of Internet use on social relationships is still a matter of intense debate. This study examined the relationships between use of social media (instant messaging and social network sites), network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using social media was associated with a larger number of online social network "friends." However, time spent using social media was not associated with larger offline networks, or feeling emotionally closer to offline network members. Further, those that used social media, as compared to non-users of social media, did not have larger offline networks, and were not emotionally closer to offline network members. These results highlight the importance of considering potential time and cognitive constraints on offline social networks when examining the impact of social media use on social relationships.

A social model based on customers' profiles for analyzing the churning process in the mobile market of data plans

NASA Astrophysics Data System (ADS)

Postigo-Boix, Marcos; Melús-Moreno, José L.

2018-04-01

Mobile Network Operators (MNOs) present wireless services of the same kind in identical zones, clients select the service taking into account any element they consider relevant. Churning hits on the design of the network and the method to assign prices by MNOs, and of course their earnings. Therefore, MNOs try to reduce churn detecting potential churners before they leave the service. Our approach to churn prediction considers each customer individually. Previous research shows that members of the social circle of a subscriber may influence churn. Thus, many scenarios that describe social relations, and in which churning processes could be expected, set an emerging challenge with practical implications. This paper uses the Agent-Based Modeling (ABM) technique to model customers. The model's parameters include demographic and psychographic features as well as usage profiles according to their social behavior considering their customers' profiles. Our model modifies and extends an existing real social network generator algorithm that considers customer's profiles and homophily considerations to create connections. We show that using our approach, groups of customers with greater tendency to churn due to the influence of their social networks can be identified better.

Prediction of missing links and reconstruction of complex networks

NASA Astrophysics Data System (ADS)

Zhang, Cheng-Jun; Zeng, An

2016-04-01

Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.

Controlling nosocomial infection based on structure of hospital social networks.

PubMed

Ueno, Taro; Masuda, Naoki

2008-10-07

Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.

Pluralistic Inquiry for the History of Community Psychology

ERIC Educational Resources Information Center

Kelly, James G.; Chang, Janet

2008-01-01

The authors present the case not only for studying the history of community psychology but also of adopting a pluralistic approach to historical inquiry, using multiple methods and access to resources from other disciplines (e.g., historians of science and social historians). Examples of substantive topics and methods, including social network and…

Assessing Argumentative Representation with Bayesian Network Models in Debatable Social Issues

ERIC Educational Resources Information Center

Zhang, Zhidong; Lu, Jingyan

2014-01-01

This study seeks to obtain argumentation models, which represent argumentative processes and an assessment structure in secondary school debatable issues in the social sciences. The argumentation model was developed based on mixed methods, a combination of both theory-driven and data-driven methods. The coding system provided a combing point by…

Machine learning approaches to the social determinants of health in the health and retirement study.

PubMed

Seligman, Benjamin; Tuljapurkar, Shripad; Rehkopf, David

2018-04-01

Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length. Prediction, fit, and interpretability were compared across four machine learning methods: linear regression, penalized regressions, random forests, and neural networks. All models had poor out-of-sample prediction. Most machine learning models performed similarly to the simpler models. However, neural networks greatly outperformed the three other methods. Neural networks also had good fit to the data ( R 2 between 0.4-0.6, versus <0.3 for all others). Across machine learning models, nine variables were frequently selected or highly weighted as predictors: dental visits, current smoking, self-rated health, serial-seven subtractions, probability of receiving an inheritance, probability of leaving an inheritance of at least $10,000, number of children ever born, African-American race, and gender. Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider.

How Social Networks Influence Female Students' Choices to Major in Engineering

ERIC Educational Resources Information Center

Weinland, Kathryn Ann

2012-01-01

Scope and Method of Study: This study examined how social influence plays a part in female students' choices of college major, specifically engineering instead of science, technology, and math. Social influence may show itself through peers, family members, and teachers and may encompass resources under the umbrella of social capital. The…

Identifying Opinion Leaders to Promote Organ Donation on Social Media: Network Study

PubMed Central

Salmon, Charles T

2018-01-01

Background In the recent years, social networking sites (SNSs, also called social media) have been adopted in organ donation campaigns, and recruiting opinion leaders for such campaigns has been found effective in promoting behavioral changes. Objective The aim of this paper was to focus on the dissemination of organ donation tweets on Weibo, the Chinese equivalent of Twitter, and to examine the opinion leadership in the retweet network of popular organ donation messages using social network analysis. It also aimed to investigate how personal and social attributes contribute to a user’s opinion leadership on the topic of organ donation. Methods All messages about organ donation posted on Weibo from January 1, 2015 to December 31, 2015 were extracted using Python Web crawler. A retweet network with 505,047 nodes and 545,312 edges of the popular messages (n=206) was constructed and analyzed. The local and global opinion leaderships were measured using network metrics, and the roles of personal attributes, professional knowledge, and social positions in obtaining the opinion leadership were examined using general linear model. Results The findings revealed that personal attributes, professional knowledge, and social positions predicted individual’s local opinion leadership in the retweet network of popular organ donation messages. Alternatively, personal attributes and social positions, but not professional knowledge, were significantly associated with global opinion leadership. Conclusions The findings of this study indicate that health campaign designers may recruit peer leaders in SNS organ donation promotions to facilitate information sharing among the target audience. Users who are unverified, active, well connected, and experienced with information and communications technology (ICT) will accelerate the sharing of organ donation messages in the global environment. Medical professionals such as organ transplant surgeons who can wield a great amount of influence on their direct connections could also effectively participate in promoting organ donation on social media. PMID:29317384

Social network media exposure and adolescent eating pathology in Fiji

PubMed Central

Becker, Anne E.; Fay, Kristen E.; Agnew-Blais, Jessica; Khan, A. Nisha; Striegel-Moore, Ruth H.; Gilman, Stephen E.

2011-01-01

Background Mass media exposure has been associated with an increased risk of eating pathology. It is unknown whether indirect media exposure – such as the proliferation of media exposure in an individual’s social network – is also associated with eating disorders. Aims To test hypotheses that both individual (direct) and social network (indirect) mass media exposures were associated with eating pathology in Fiji. Method We assessed several kinds of mass media exposure, media influence, cultural orientation and eating pathology by self-report among adolescent female ethnic Fijians (n = 523). We fitted a series of multiple regression models of eating pathology, assessed by the Eating Disorder Examination Questionnaire (EDE–Q), in which mass media exposures, sociodemographic characteristics and body mass index were entered as predictors. Results Both direct and indirect mass media exposures were associated with eating pathology in unadjusted analyses, whereas in adjusted analyses only social network media exposure was associated with eating pathology. This result was similar when eating pathology was operationalised as either a continuous or a categorical dependent variable (e.g. odds ratio OR = 1.60, 95% CI 1.15–2.23 relating social network media exposure to upper-quartile EDE–Q scores). Subsequent analyses pointed to individual media influence as an important explanatory variable in this association. Conclusions Social network media exposure was associated with eating pathology in this Fijian study sample, independent of direct media exposure and other cultural exposures. Findings warrant further investigation of its health impact in other populations. PMID:21200076

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Social network targeting to maximise population behaviour change: a cluster randomised controlled trial.

PubMed

Kim, David A; Hwong, Alison R; Stafford, Derek; Hughes, D Alex; O'Malley, A James; Fowler, James H; Christakis, Nicholas A

2015-07-11

Information and behaviour can spread through interpersonal ties. By targeting influential individuals, health interventions that harness the distributive properties of social networks could be made more effective and efficient than those that do not. Our aim was to assess which targeting methods produce the greatest cascades or spillover effects and hence maximise population-level behaviour change. In this cluster randomised trial, participants were recruited from villages of the Department of Lempira, Honduras. We blocked villages on the basis of network size, socioeconomic status, and baseline rates of water purification, for delivery of two public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. We then randomised villages, separately for each intervention, to one of three targeting methods, introducing the interventions to 5% samples composed of either: randomly selected villagers (n=9 villages for each intervention); villagers with the most social ties (n=9); or nominated friends of random villagers (n=9; the last strategy exploiting the so-called friendship paradox of social networks). Participants and data collectors were not aware of the targeting methods. Primary endpoints were the proportions of available products redeemed by the entire population under each targeting method. This trial is registered with ClinicalTrials.gov, number NCT01672580. Between Aug 4, and Aug 14, 2012, 32 villages in rural Honduras (25-541 participants each; total study population of 5773) received public health interventions. For each intervention, nine villages (each with 1-20 initial target individuals) were randomised, using a blocked design, to each of the three targeting methods. In nomination-targeted villages, 951 (74·3%) of 1280 available multivitamin tickets were redeemed compared with 940 (66·2%) of 1420 in randomly targeted villages and 744 (61·0%) of 1220 in indegree-targeted villages. All pairwise differences in redemption rates were significant (p<0·01) after correction for multiple comparisons. Targeting nominated friends increased adoption of the nutritional intervention by 12·2% compared with random targeting (95% CI 6·9-17·9). Targeting the most highly connected individuals, by contrast, produced no greater adoption of either intervention, compared with random targeting. Introduction of a health intervention to the nominated friends of random individuals can enhance that intervention's diffusion by exploiting intrinsic properties of human social networks. This method has the additional advantage of scalability because it can be implemented without mapping the network. Deployment of certain types of health interventions via network targeting, without increasing the number of individuals targeted or the resources used, could enhance the adoption and efficiency of those interventions, thereby improving population health. National Institutes of Health, The Bill & Melinda Gates Foundation, Star Family Foundation, and the Canadian Institutes of Health Research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hacking Social Networks: Examining the Viability of Using Computer Network Attack Against Social Networks

DTIC Science & Technology

2007-03-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited. HACKING SOCIAL NETWORKS : EXAMINING THE...VIABILITY OF USING COMPUTER NETWORK ATTACK AGAINST SOCIAL NETWORKS by Russell G. Schuhart II March 2007 Thesis Advisor: David Tucker Second Reader...Master’s Thesis 4. TITLE AND SUBTITLE: Hacking Social Networks : Examining the Viability of Using Computer Network Attack Against Social Networks 6. AUTHOR

“Tertius gaudens”: germplasm exchange networks and agroecological knowledge among home gardeners in the Iberian Peninsula

PubMed Central

2013-01-01

Background The idea that knowledge flows through social networks is implicit in research on traditional knowledge, but researchers have paid scant attention to the role of social networks in shaping its distribution. We bridge those two bodies of research and investigate a) the structure of network of exchange of plant propagation material (germplasm) and b) the relation between a person’s centrality in such network and his/her agroecological knowledge. Methods We study 10 networks of germplasm exchange (n = 363) in mountain regions of the Iberian Peninsula. Data were collected through participant observation, semi-structured interviews, and a survey. Results The networks display some structural characteristics (i.e., decentralization, presence of external actors) that could enhance the flow of knowledge and germplasm but also some characteristics that do not favor such flow (i.e., low density and fragmentation). We also find that a measure that captures the number of contacts of an individual in the germplasm exchange network is associated with the person’s agroecological knowledge. Conclusion Our findings highlight the importance of social relations in the construction of traditional knowledge. PMID:23883296

CS_TOTR: A new vertex centrality method for directed signed networks based on status theory

NASA Astrophysics Data System (ADS)

Ma, Yue; Liu, Min; Zhang, Peng; Qi, Xingqin

Measuring the importance (or centrality) of vertices in a network is a significant topic in complex network analysis, which has significant applications in diverse domains, for example, disease control, spread of rumors, viral marketing and so on. Existing studies mainly focus on social networks with only positive (or friendship) relations, while signed networks with also negative (or enemy) relations are seldom studied. Various signed networks commonly exist in real world, e.g. a network indicating friendship/enmity, love/hate or trust/mistrust relationships. In this paper, we propose a new centrality method named CS_TOTR to give a ranking of vertices in directed signed networks. To design this new method, we use the “status theory” for signed networks, and also adopt the vertex ranking algorithm for a tournament and the topological sorting algorithm for a general directed graph. We apply this new centrality method on the famous Sampson Monastery dataset and obtain a convincing result which shows its validity.

Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

PubMed Central

Lee, Sandra Soo-Jin; Vernez, Simone L.; Ormond, K.E.; Granovetter, Mark

2013-01-01

Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities. PMID:25562728

[Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

PubMed

Díaz Córdova, Diego

2016-01-01

The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

Analyzing Social Media and Learning through Content and Social Network Analysis: A Faceted Methodological Approach

ERIC Educational Resources Information Center

Gruzd, Anatoliy; Paulin, Drew; Haythornthwaite, Caroline

2016-01-01

In just a short period, social media have altered many aspects of our daily lives, from how we form and maintain social relationships to how we discover, access, and share information online. Now social media are also affecting how we teach and learn. In this paper, we discuss methods that can help researchers and educators evaluate and understand…

Use of Social Media in Radiology Education.

PubMed

Ranginwala, Saad; Towbin, Alexander J

2018-01-01

Social media has become the dominant method of mass digital communication over the past decade. Public figures and corporations have learned how to use this new approach to deliver their messages directly to their followers. Recently, medical educators have begun to use social media as a means to deliver educational content directly to learners. The purpose of this article is to describe the benefits of using social media for medical education. Because each social media platform has different platform-specific constraints, several different popular social media networks are discussed. For each network, the authors discuss the basics of the platform and its benefits and disadvantages for users and provide examples of how they have used each platform to target a unique audience. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Modeling virtual organizations with Latent Dirichlet Allocation: a case for natural language processing.

PubMed

Gross, Alexander; Murthy, Dhiraj

2014-10-01

This paper explores a variety of methods for applying the Latent Dirichlet Allocation (LDA) automated topic modeling algorithm to the modeling of the structure and behavior of virtual organizations found within modern social media and social networking environments. As the field of Big Data reveals, an increase in the scale of social data available presents new challenges which are not tackled by merely scaling up hardware and software. Rather, they necessitate new methods and, indeed, new areas of expertise. Natural language processing provides one such method. This paper applies LDA to the study of scientific virtual organizations whose members employ social technologies. Because of the vast data footprint in these virtual platforms, we found that natural language processing was needed to 'unlock' and render visible latent, previously unseen conversational connections across large textual corpora (spanning profiles, discussion threads, forums, and other social media incarnations). We introduce variants of LDA and ultimately make the argument that natural language processing is a critical interdisciplinary methodology to make better sense of social 'Big Data' and we were able to successfully model nested discussion topics from forums and blog posts using LDA. Importantly, we found that LDA can move us beyond the state-of-the-art in conventional Social Network Analysis techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

How social networks influence female students' choices to major in engineering

NASA Astrophysics Data System (ADS)

Weinland, Kathryn Ann

Scope and Method of Study: This study examined how social influence plays a part in female students' choices of college major, specifically engineering instead of science, technology, and math. Social influence may show itself through peers, family members, and teachers and may encompass resources under the umbrella of social capital. The purpose of this study was to examine how female students' social networks, through the lens of social capital, influence her major choice of whether or not to study engineering. The variables of peer influence, parental influence, teacher/counselor influence, perception of engineering, and academic background were addressed in a 52 question, Likert scale survey. This survey has been modified from an instrument previously used by Reyer (2007) at Bradley University. Data collection was completed using the Dillman (2009) tailored design model. Responses were grouped into four main scales of the dependent variables of social influence, encouragement, perceptions of engineering and career motivation. A factor analysis was completed on the four factors as a whole, and individual questions were not be analyzed. Findings and Conclusions: This study addressed the differences in social network support for female freshmen majoring in engineering versus female freshmen majoring in science, technology, or math. Social network support, when working together from all angles of peers, teachers, parents, and teachers/counselors, transforms itself into a new force that is more powerful than the summation of the individual parts. Math and science preparation also contributed to female freshmen choosing to major in engineering instead of choosing to major in science, technology, or math. The STEM pipeline is still weak and ways in which to reinforce it should be examined. Social network support is crucial for female freshmen who are majoring in science, technology, engineering, and math.

Proactive recruitment of cancer patients’ social networks into a smoking cessation trial

PubMed Central

Bastian, Lori A.; Fish, Laura J.; Peterson, Bercedis L.; Biddle, Andrea K.; Garst, Jennifer; Lyna, Pauline; Molner, Stephanie; Bepler, Gerold; Kelley, Mike; Keefe, Francis J.; McBride, Colleen M.

2011-01-01

Background This report describes the characteristics associated with successful enrollment of smokers in the social networks (i.e., family and close friends) of patients with lung cancer into a smoking cessation intervention. Methods Lung cancer patients from four clinical sites were asked to complete a survey enumerating their family members and close friends who smoke, and provide permission to contact these potential participants. Family members and close friends identified as smokers were interviewed and offered participation in a smoking cessation intervention. Repeated measures logistic regression model examined characteristics associated with enrollment. Results A total of 1,062 eligible lung cancer patients were identified and 516 patients consented and completed the survey. These patients identified 1,325 potentially eligible family and close friends. Of these, 496 consented and enrolled in the smoking cessation program. Network enrollment was highest among patients who were white and had late-stage disease. Social network members enrolled were most likely to be female, a birth family, immediate family, or close friend, and live in close geographic proximity to the patient. Conclusions Proactive recruitment of smokers in the social networks of lung cancer patients is challenging. In this study, the majority of family members and friends declined to participate. Enlisting immediate female family members and friends, who live close to the patient as agents to proactively recruit other network members into smoking cessation trials could be used to extend reach of cessation interventions to patients’ social networks. Moreover, further consideration should be given to the appropriate timing of approaching network smokers to consider cessation. PMID:21382509

The Structure and Characteristics of #PhDChat, an Emergent Online Social Network

ERIC Educational Resources Information Center

Ford, Kasey C.; Veletsianos, George; Resta, Paul

2014-01-01

#PhDChat is an online network of individuals that has its roots to a group of UK doctoral students who began using Twitter in 2010 to hold discussions. Since then, the network around #PhDchat has evolved and grown. In this study, we examine this network using a mixed methods analysis of the tweets that were labeled with the hashtag over a…

Tracing information flow on a global scale using Internet chain-letter data

PubMed Central

Liben-Nowell, David; Kleinberg, Jon

2008-01-01

Although information, news, and opinions continuously circulate in the worldwide social network, the actual mechanics of how any single piece of information spreads on a global scale have been a mystery. Here, we trace such information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. We find that rather than fanning out widely, reaching many people in very few steps according to “small-world” principles, the progress of these chain letters proceeds in a narrow but very deep tree-like pattern, continuing for several hundred steps. This suggests a new and more complex picture for the spread of information through a social network. We describe a probabilistic model based on network clustering and asynchronous response times that produces trees with this characteristic structure on social-network data. PMID:18353985

A networking approach to reduce academic and social isolation for junior doctors working in rural hospitals in India.

PubMed

Vyas, R; Zachariah, A; Swamidasan, I; Doris, P; Harris, I

2012-07-01

Graduates from Christian Medical College (CMC) Vellore face many challenges while doing their service obligation in smaller hospitals, including academic and social isolation. To overcome these challenges, CMC aspired through its Fellowship in Secondary Hospital Medicine (FSHM), a 1-year blended on-site and distance-learning program, to provide academic and social support through networking for junior doctors working in rural areas. The purpose of this paper is to report the evaluation of the networking components of the FSHM program, with a focus on whether it succeeded in providing academic and social support for these junior doctors. A mixed method evaluation was done using written surveys for students and faculty and telephone interviews for students. Evidence for validity was gathered for the written survey. Criteria for validity were also applied for the qualitative data analysis. The major strengths of networking with faculty and peers identified were that it provided social support,, academic support through discussion about patient management problems and a variety of cases seen in the hospital, guidance on projects and reminders about deadlines. Recommendations for improvement included use of videoconferencing and Yahoo Groups. It is useful to incorporate networking into distance-learning educational programs for providing support to junior doctors working in rural hospitals.

Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives

PubMed Central

2016-01-01

Background Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. Objective We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members’ conversations. Methods Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. Results We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. Conclusions (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck’s cognitive theory of depression; (2) the social structure of the MDD group is much stickier than those of other social media groups, indicating the tendency of mutual communications and efficient spread of information in the MDD group; and (3) the linguistic patterns of MDD members are associated with their topological positions in the social network. PMID:26966078

Information filtering via biased random walk on coupled social network.

PubMed

Nie, Da-Cheng; Zhang, Zi-Ke; Dong, Qiang; Sun, Chongjing; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.

Information Filtering via Biased Random Walk on Coupled Social Network

PubMed Central

Dong, Qiang; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods. PMID:25147867

Parsing Social Network Survey Data from Hidden Populations Using Stochastic Context-Free Grammars

PubMed Central

Poon, Art F. Y.; Brouwer, Kimberly C.; Strathdee, Steffanie A.; Firestone-Cruz, Michelle; Lozada, Remedios M.; Kosakovsky Pond, Sergei L.; Heckathorn, Douglas D.; Frost, Simon D. W.

2009-01-01

Background Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a ÔhiddenÕ population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. Methodology/Principal Findings Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. Conclusions SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics. PMID:19738904

Using narrative inquiry to listen to the voices of adolescent mothers in relation to their use of social networking sites (SNS).

PubMed

Nolan, Samantha; Hendricks, Joyce; Williamson, Moira; Ferguson, Sally

2018-03-01

This article presents a discussion highlighting the relevance and strengths of using narrative inquiry to explore experiences of social networking site (SNS) use by adolescent mothers. Narrative inquiry as a method reveals truths about holistic human experience. Knowledge gleaned from personal narratives informs nursing knowledge and clinical practice. This approach gives voice to adolescent mothers in relation to their experiences with SNS as a means of providing social support. Discussion paper. This paper draws and reflects on the author's experiences using narrative inquiry and is supported by literature and theory. The following databases were searched: CINAHL, Cochrane Library, Medline, Scopus, ERIC, ProQuest, PsychINFO, Web of Science and Health Collection (Informit). Key terms and Boolean search operators were used to broaden the search criteria. Search terms included: adolescent mother, teenage mother, "social networking sites", online, social media, Facebook, social support, social capital and information. Dates for the search were limited to January 1995-June 2017. Narrative research inherently values the individual "story" of experience. This approach facilitates rapport building and methodological flexibility with an often difficult to engage sample group, adolescents. Narrative inquiry reveals a deep level of insight into social networking site use by adolescent mothers. The flexibility afforded by use of a narrative approach allows for fluidity and reflexivity in the research process. © 2017 John Wiley & Sons Ltd.

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting missing links and identifying spurious links via likelihood analysis

NASA Astrophysics Data System (ADS)

Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

2016-03-01

Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network’s probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms.

Predicting missing links and identifying spurious links via likelihood analysis

PubMed Central

Pan, Liming; Zhou, Tao; Lü, Linyuan; Hu, Chin-Kun

2016-01-01

Real network data is often incomplete and noisy, where link prediction algorithms and spurious link identification algorithms can be applied. Thus far, it lacks a general method to transform network organizing mechanisms to link prediction algorithms. Here we use an algorithmic framework where a network’s probability is calculated according to a predefined structural Hamiltonian that takes into account the network organizing principles, and a non-observed link is scored by the conditional probability of adding the link to the observed network. Extensive numerical simulations show that the proposed algorithm has remarkably higher accuracy than the state-of-the-art methods in uncovering missing links and identifying spurious links in many complex biological and social networks. Such method also finds applications in exploring the underlying network evolutionary mechanisms. PMID:26961965

Discovering Network Structure Beyond Communities

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2011-11-01

To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest.

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

PubMed Central

Vadillo, Miguel A; Curcin, Vasa

2017-01-01

Background Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. Objective The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research. Methods We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals. Results The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis. Conclusions Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques. PMID:28663166

Electronic Cigarette Marketing Online: a Multi-Site, Multi-Product Comparison

PubMed Central

Sidhu, Anupreet K; Valente, Thomas W

2015-01-01

Background Electronic cigarette awareness and use has been increasing rapidly. E-cigarette brands have utilized social networking sites to promote their products, as the growth of the e-cigarette industry has paralleled that of Web 2.0. These online platforms are cost-effective and have unique technological features and user demographics that can be attractive for selective marketing. The popularity of multiple sites also poses a risk of exposure to social networks where e-cigarette brands might not have a presence. Objective To examine the marketing strategies of leading e-cigarette brands on multiple social networking sites, and to identify how affordances of the digital media are used to their advantage. Secondary analyses include determining if any brands are benefitting from site demographics, and exploring cross-site diffusion of marketing content through multi-site users. Methods We collected data from two e-cigarette brands from four social networking sites over approximately 2.5 years. Content analysis is used to search for themes, population targeting, marketing strategies, and cross-site spread of messages. Results Twitter appeared to be the most frequently used social networking site for interacting directly with product users. Facebook supported informational broadcasts, such as announcements regarding political legislation. E-cigarette brands also differed in their approaches to their users, from informal conversations to direct product marketing. Conclusions E-cigarette makers use different strategies to market their product and engage their users. There was no evidence of direct targeting of vulnerable populations, but the affordances of the different sites are exploited to best broadcast context-specific messages. We developed a viable method to study cross-site diffusion, although additional refinement is needed to account for how different types of digital media are used. PMID:27227129

Dynamics of Disagreement: Large-Scale Temporal Network Analysis Reveals Negative Interactions in Online Collaboration

NASA Astrophysics Data System (ADS)

Tsvetkova, Milena; García-Gavilanes, Ruth; Yasseri, Taha

2016-11-01

Disagreement and conflict are a fact of social life. However, negative interactions are rarely explicitly declared and recorded and this makes them hard for scientists to study. In an attempt to understand the structural and temporal features of negative interactions in the community, we use complex network methods to analyze patterns in the timing and configuration of reverts of article edits to Wikipedia. We investigate how often and how fast pairs of reverts occur compared to a null model in order to control for patterns that are natural to the content production or are due to the internal rules of Wikipedia. Our results suggest that Wikipedia editors systematically revert the same person, revert back their reverter, and come to defend a reverted editor. We further relate these interactions to the status of the involved editors. Even though the individual reverts might not necessarily be negative social interactions, our analysis points to the existence of certain patterns of negative social dynamics within the community of editors. Some of these patterns have not been previously explored and carry implications for the knowledge collection practice conducted on Wikipedia. Our method can be applied to other large-scale temporal collaboration networks to identify the existence of negative social interactions and other social processes.

Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users

PubMed Central

Baumgartner, Peter; Peiper, Nicholas

2017-01-01

Large shifts in medical, recreational, and illicit cannabis consumption in the United States have implications for personalizing treatment and prevention programs to a wide variety of populations. As such, considerable research has investigated clinical presentations of cannabis users in clinical and population-based samples. Studies leveraging big data, social media, and social network analysis have emerged as a promising mechanism to generate timely insights that can inform treatment and prevention research. This study extends a novel method called stochastic block modeling to derive communities of cannabis consumers as part of a complex social network on Twitter. A set of examples illustrate how this method can ascertain candidate samples of medical, recreational, and illicit cannabis users. Implications for research planning, intervention design, and public health surveillance are discussed. PMID:28615950

The Game of Contacts: Estimating the Social Visibility of Groups.

PubMed

Salganik, Matthew J; Mello, Maeve B; Abdo, Alexandre H; Bertoni, Neilane; Fazito, Dimitri; Bastos, Francisco I

2011-01-01

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations-illicit drug users, men who have sex with men, and sex workers-are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys.

Evaluation of a Social Network Intervention for People with Mild to Borderline Intellectual Disabilities.

PubMed

van Asselt-Goverts, A E; Embregts, P J C M; Hendriks, A H C

2018-03-01

Little is known about the effectiveness of interventions aimed at enhancing the social networks of people with intellectual disabilities. This study explores the results of such an intervention. How did the clients with mild to borderline intellectual disabilities and their support workers evaluate the intervention? What did they learn from it? Were there any changes in network characteristics, satisfaction and wishes in relation to networks, participation, loneliness, self-determination or self-esteem? The evaluation of the intervention was explored from several perspectives (i.e. five clients, their six support workers and three trainers), using mixed methods (i.e. interviews and questionnaires). The intervention was positively evaluated by both clients and support workers. Moreover, the analysis revealed the vulnerability of clients and their networks but also the benefits experienced from the intervention, such as decreased loneliness, enhanced social networks, increased awareness, competence, autonomy and increased participation. The indicative level of evidence for the effectiveness of this intervention justifies a larger series of case studies or a larger control trial study. © 2016 John Wiley & Sons Ltd.

'I could never do that before': effectiveness of a tailored Internet support intervention to increase the social participation of youth with disabilities.

PubMed

Raghavendra, P; Newman, L; Grace, E; Wood, D

2013-07-01

Youth use the Internet for a variety of purposes including social networking. Youth with disabilities are limited in their social networks and friendships with peers. The aim was to investigate the effectiveness of tailored one-on-one support strategies designed to facilitate social participation of youth with disabilities through the use of the Internet for social networking. Eighteen youth aged 10-18 years with cerebral palsy, physical disability or acquired brain injury received support, training and assistive technology at their home to learn to use the Internet for building social networks. The Canadian Occupational Performance Measure (COPM) and Goal Attainment Scale (GAS) were used to evaluate objective changes in performance and satisfaction. Interviews with the youth identified subjective changes they experienced through participation in the programme and to determine whether and how the intervention influenced their social participation. Youth showed an increase in performance and satisfaction with performance on identified goals concerning social networking on the COPM; Paired T-test showed that these differences were statistically significant at P < 0.001. GAS T-scores demonstrated successful outcomes (>50) for 78% of the youth. Interviews showed that youth were positive about the benefits of hands-on training at home leading to increased use of the Internet for social networking. The Internet could be a viable method to facilitate social participation for youth with disabilities. Youth identified the benefits of one-to-one support at home and training of the family compared with typical group training at school. Despite its success with this group of youth, the time and effort intensive nature of this approach may limit the viability of such programmes. Further longitudinal research should investigate whether Internet use is sustained post intervention, and to identify the factors that best support ongoing successful and safe use. © 2013 John Wiley & Sons Ltd.

Teaching an Interdisciplinary Graduate-Level Methods Course in an Openly-Networked Connected Learning Environment: A Glass Half-Full

ERIC Educational Resources Information Center

Secret, Mary; Bryant, Nita L.; Cummings, Cory R.

2017-01-01

Our paper describes the design and delivery of an online interdisciplinary social science research methods course (ISRM) for graduate students in sociology, education, social work, and public administration. Collaborative activities and learning took place in two types of computer-mediated learning environments: a closed Blackboard course…

Study protocol - Indigenous Australian social networks and the impact on smoking policy and programs in Australia: protocol for a mixed-method prospective study

PubMed Central

2013-01-01

Background Tobacco use is the most preventable cause of morbidity and mortality in Australia. Comprehensive tobacco control has reduced smoking rates in Australia from approximately 34 per cent in 1980 to 15 per cent in 2010. However, 46 per cent of Aboriginal and Torres Strait Islander people (Indigenous Australians) smoke on a daily basis, more than double the rate of non-Indigenous Australians. The evidence of effective tobacco control strategies for Indigenous Australians is relatively scarce. The aim of this study is to (i) explore the influences of smoking in Indigenous Australian people and to (ii) help inform and evaluate a multi-component tobacco control strategy. The study aims to answer the following questions: - do individuals' social networks influence smoking behaviours; - is there an association between various social and cultural factors and being a smoker or non-smoker; and - does a multi-component tobacco control program impact positively on tobacco behaviours, attitudes and beliefs in Indigenous Australians. Methods and design Our prospective study will use a mixed-method approach (qualitative and quantitative), including a pre- and post-test evaluation of a tobacco control initiative. The study will explore the social and cultural context underlying Indigenous Australian tobacco use and associated factors which influence smoking behaviour. Primary data will be collected via a panel survey, interviews and focus groups. Secondary data will include de-identified PBS items related to smoking and also data collected from the Quitlines call service. Network analysis will be used to assess whether social networks influence smoking behaviours. For the survey, baseline differences will be tested using chi2 statistics for the categorical and dichotomous variables and t-tests for the continuous variables, where appropriate. Grounded theory will be used to analyse the interviews and focus groups. Local Aboriginal community controlled organisations will partner in the study. Discussion Our study will explore the key factors, including the influence of social networks, that impact on tobacco use and the extent to which smoking behaviours transcend networks within the Indigenous Australian community in the ACT. This will add to the evidence-base, identifying influential factors to tobacco use and the effectiveness and influence of a multi-component tobacco control strategy. PMID:24060337

Learned Social Hopelessness: The Role of Explanatory Style in Predicting Social Support during Adolescence

ERIC Educational Resources Information Center

Ciarrochi, Joseph; Heaven, Patrick C. L.

2008-01-01

Background: Almost no research has examined the impact of explanatory style on social adjustment. We hypothesised that adolescents with a pessimistic style would be less likely to develop and maintain social support networks. Methods: Seven hundred and nineteen students (351 males and 366 females; 2 unknown; M[subscript AGE] = 12.28, SD = 0.49)…

Social network analysis of the genetic structure of Pacific islanders.

PubMed

Terrell, John Edward

2010-05-01

Social network analysis (SNA) is a body of theory and a set of relatively new computer-aided techniques used in the analysis and study of relational data. Recent studies of autosomal markers from over 40 human populations in the south-western Pacific have further documented the remarkable degree of genetic diversity in this part of the world. I report additional analysis using SNA methods contributing new controlled observations on the structuring of genetic diversity among these islanders. These SNA mappings are then compared with model-based network expectations derived from the geographic distances among the same populations. Previous studies found that genetic divergence among island Melanesian populations is organised by island, island size/topography, and position (coastal vs. inland), and that similarities observed correlate only weakly with an isolation-by-distance model. Using SNA methods, however, improves the resolution of among population comparison, and suggests that isolation by distance constrained by social networks together with position (coastal/inland) accounts for much of the population structuring observed. The multilocus data now available is also in accord with current thinking on the impact of major biogeographical transformations on prehistoric colonisation and post-settlement human interaction in Oceania.

User Vulnerability and its Reduction on a Social Networking Site

DTIC Science & Technology

2014-01-01

social networking sites bring about new...and explore other users’ profiles and friend networks. Social networking sites have reshaped business models [Vayner- chuk 2009], provided platform... social networking sites is to enable users to be more social, user privacy and security issues cannot be ignored. On one hand, most social networking sites

Finding Influential Users in Social Media Using Association Rule Learning

NASA Astrophysics Data System (ADS)

Erlandsson, Fredrik; Bródka, Piotr; Borg, Anton; Johnson, Henric

2016-04-01

Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user participation. Normally, the success of a social media site is dependent on the activity level of the participating users. For both online social networking sites and individual users, it is of interest to find out if a topic will be interesting or not. In this article, we propose association learning to detect relationships between users. In order to verify the findings, several experiments were executed based on social network analysis, in which the most influential users identified from association rule learning were compared to the results from Degree Centrality and Page Rank Centrality. The results clearly indicate that it is possible to identify the most influential users using association rule learning. In addition, the results also indicate a lower execution time compared to state-of-the-art methods.

Potential benefits and harms of a peer support social network service on the internet for people with depressive tendencies: qualitative content analysis and social network analysis.

PubMed

Takahashi, Yoshimitsu; Uchida, Chiyoko; Miyaki, Koichi; Sakai, Michi; Shimbo, Takuro; Nakayama, Takeo

2009-07-23

Internet peer support groups for depression are becoming popular and could be affected by an increasing number of social network services (SNSs). However, little is known about participant characteristics, social relationships in SNSs, and the reasons for usage. In addition, the effects of SNS participation on people with depression are rather unknown. The aim was to explore the potential benefits and harms of an SNS for depression based on a concurrent triangulation design of mixed methods strategy, including qualitative content analysis and social network analysis. A cross-sectional Internet survey of participants, which involved the collection of SNS log files and a questionnaire, was conducted in an SNS for people with self-reported depressive tendencies in Japan in 2007. Quantitative data, which included user demographics, depressive state, and assessment of the SNS (positive vs not positive), were statistically analyzed. Descriptive contents of responses to open-ended questions concerning advantages and disadvantages of SNS participation were analyzed using the inductive approach of qualitative content analysis. Contents were organized into codes, concepts, categories, and a storyline based on the grounded theory approach. Social relationships, derived from data of "friends," were analyzed using social network analysis, in which network measures and the extent of interpersonal association were calculated based on the social network theory. Each analysis and integration of results were performed through a concurrent triangulation design of mixed methods strategy. There were 105 participants. Median age was 36 years, and 51% (36/71) were male. There were 37 valid respondents; their number of friends and frequency of accessing the SNS were significantly higher than for invalid/nonrespondents (P = .008 and P = .003). Among respondents, 90% (28/31) were mildly, moderately, or severely depressed. Assessment of the SNS was performed by determining the access frequency of the SNS and the number of friends. Qualitative content analysis indicated that user-selectable peer support could be passive, active, and/or interactive based on anonymity or ease of use, and there was the potential harm of a downward depressive spiral triggered by aggravated psychological burden. Social network analysis revealed that users communicated one-on-one with each other or in small groups (five people or less). A downward depressive spiral was related to friends who were moderately or severely depressed and friends with negative assessment of the SNS. An SNS for people with depressive tendencies provides various opportunities to obtain support that meets users' needs. To avoid a downward depressive spiral, we recommend that participants do not use SNSs when they feel that the SNS is not user-selectable, when they get egocentric comments, when friends have a negative assessment of the SNS, or when they have additional psychological burden.

Having mentors and campus social networks moderates the impact of worries and video gaming on depressive symptoms: a moderated mediation analysis

PubMed Central

2014-01-01

Background Easy access to the internet has spawned a wealth of research to investigate the effects of its use on depression. However, one limitation of many previous studies is that they disregard the interactive mechanisms of risk and protective factors. The aim of the present study was to investigate a resilience model in the relationship between worry, daily internet video game playing, daily sleep duration, mentors, social networks and depression, using a moderated mediation analysis. Methods 6068 Korean undergraduate and graduate students participated in this study. The participants completed a web-based mental health screening questionnaire including the Beck Depression Inventory (BDI) and information about number of worries, number of mentors, number of campus social networks, daily sleep duration, daily amount of internet video game playing and daily amount of internet searching on computer or smartphone. A moderated mediation analysis was carried out using the PROCESS macro which allowed the inclusion of mediators and moderator in the same model. Results The results showed that the daily amount of internet video game playing and daily sleep duration partially mediated the association between the number of worries and the severity of depression. In addition, the mediating effect of the daily amount of internet video game playing was moderated by both the number of mentors and the number of campus social networks. Conclusions The current findings indicate that the negative impact of worry on depression through internet video game playing can be buffered when students seek to have a number of mentors and campus social networks. Interventions should therefore target individuals who have higher number of worries but seek only a few mentors or campus social networks. Social support via campus mentorship and social networks ameliorate the severity of depression in university students. PMID:24884864

Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

PubMed

Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L

2017-04-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

USGS Publications Warehouse

Haak, Danielle M.; Fath, Brian D.; Forbes, Valery E.; Martin, Dustin R.; Pope, Kevin L.

2017-01-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensisalters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Teen Alcohol Use and Social Networks: The Contributions of Friend Influence and Friendship Selection

PubMed Central

Cheadle, Jacob E; Walsemann, Katrina M; Goosby, Bridget J

2015-01-01

Background We evaluated the contributions of teen alcohol use to the formation and continuation of new and existing friendships while in turn estimating the influence of friend drinking on individuals’ regular use and heavy drinking. Method Longitudinal network analysis was used to assess the mutual influences between teen drinking and social networks among adolescents in two large Add Health schools where full network data was collected three times. Friendship processes were disaggregated into the formation of new friendships and the continuation of existing friendships in a joint model isolating friendship selection and friend influences. Results Friends have a modest influence on one another when selection is controlled. Selection is more complicated than prior studies suggest, and is only related to new friendships and not their duration in the largest school. Alcohol use predicts decreasing popularity in some cases, and popularity does not predict alcohol consumption. Conclusion Intervention efforts should continue pursuing strategies that mitigate negative peer influences. The development of socializing opportunities that facilitate relationship opportunities to select on healthy behaviors also appears promising. Future work preventing teen substance use should incorporate longitudinal network assessments to determine whether programs promote protective peer relationships in addition to how treatment effects diffuse through social networks. PMID:26692436

Purchasing Networks as Clues to Assessing Educational Psychology Textbooks

ERIC Educational Resources Information Center

Seifert, Kelvin

2008-01-01

Recently the analysis of social networks has proved successful for understanding many educational processes, and has led to dozens of papers on a variety of education-related topics and problems (Natriello, 2005; Watts, 2005), as well as to entire books explaining network research methods both to specialists and to wider audiences (e.g. Barbabasi,…

Social Media for Networking, Professional Development, and Patient Engagement.

PubMed

Markham, Merry Jennifer; Gentile, Danielle; Graham, David L

2017-01-01

Social media has become an established method of communication, and many physicians are finding these interactive tools and platforms to be useful for both personal and professional use. Risks of social media, or barriers to its use, include perceived lack of time, privacy concerns, and the risk of damage to one's reputation by unprofessional behavior. Of the social media platforms, Twitter has become favored by physicians and other health care professionals. Although one of the most obvious uses of social media is for rapid dissemination and receipt of information, oncologists are finding that social media is important for networking through blogs, Facebook, and Twitter. These platforms also have potential for providing opportunities for professional development, such as finding collaborators through networking, participation in Twitter journal clubs, and participating in online case-based tumor boards. Social media can also be used for patient engagement, such as through participation in tweet chats. There is emerging data that patient engagement through these platforms may lead to improvement in some health-related outcomes; however, data are sparse for oncology-specific outcomes. Efforts are underway to determine how to assess how social media engagement impacts health outcomes in oncology patients.

Network Exposure and Homicide Victimization in an African American Community

PubMed Central

Wildeman, Christopher

2014-01-01

Objectives. We estimated the association of an individual’s exposure to homicide in a social network and the risk of individual homicide victimization across a high-crime African American community. Methods. Combining 5 years of homicide and police records, we analyzed a network of 3718 high-risk individuals that was created by instances of co-offending. We used logistic regression to model the odds of being a gunshot homicide victim by individual characteristics, network position, and indirect exposure to homicide. Results. Forty-one percent of all gun homicides occurred within a network component containing less than 4% of the neighborhood’s population. Network-level indicators reduced the association between individual risk factors and homicide victimization and improved the overall prediction of individual victimization. Network exposure to homicide was strongly associated with victimization: the closer one is to a homicide victim, the greater the risk of victimization. Regression models show that exposure diminished with social distance: each social tie removed from a homicide victim decreased one’s odds of being a homicide victim by 57%. Conclusions. Risk of homicide in urban areas is even more highly concentrated than previously thought. We found that most of the risk of gun violence was concentrated in networks of identifiable individuals. Understanding these networks may improve prediction of individual homicide victimization within disadvantaged communities. PMID:24228655

SOCIAL SCIENCE EDUCATION CONSORTIUM. PUBLICATION 106, ANTHROPOLOGY.

ERIC Educational Resources Information Center

BOHANNAN, PAUL

A CURRICULUM GUIDE OUTLINES THE MAJOR CONCEPTS, STRUCTURE, AND METHODS OF ANTHROPOLOGY FOR GRADES K-6. THE FOLLOWING UNIT AREAS ARE INCLUDED--(1) NEEDS AND NEED SATISFACTION, (2) HUMAN PERSONALITY, (3) SOCIAL GROUPS, (4) SOCIAL NETWORKS, (5) HUMAN CULTURE, (6) CHANGE AND EVOLUTION, AND (7) CURRENT CULTURAL CHANGES. A SUMMARY CHART PRESENTS A FLOW…

The Effect of Online College Attendance on Job Obtainment through Social Connections

ERIC Educational Resources Information Center

Taggart, Gabel

2017-01-01

Attending college online has implications for students' ability to make social connections and eventually obtain jobs by means of social capital. Previous academic work has tested employer callback rates to fictitious resumes treated by indications of either online or face-to-face college attendance but such methods overlook the networking aspect…

Unpacking (In)formal Learning in an Academic Development Programme: A Mixed-Method Social Network Perspective

ERIC Educational Resources Information Center

Rienties, Bart; Hosein, Anesa

2015-01-01

How and with whom academics develop and maintain formal and informal networks for reflecting on their teaching practice has received limited attention even though academic development (AD) programmes have become an almost ubiquitous feature of higher education. The primary goal of this mixed-method study is to unpack how 114 academics in an AD…

A spectral method to detect community structure based on distance modularity matrix

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth

PubMed Central

2018-01-01

Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health. PMID:29695089

Early Warning and Outbreak Detection Using Social Networking Websites: The Potential of Twitter

NASA Astrophysics Data System (ADS)

de Quincey, Ed; Kostkova, Patty

Epidemic Intelligence is being used to gather information about potential diseases outbreaks from both formal and increasingly informal sources. A potential addition to these informal sources are social networking sites such as Facebook and Twitter. In this paper we describe a method for extracting messages, called "tweets" from the Twitter website and the results of a pilot study which collected over 135,000 tweets in a week during the current Swine Flu pandemic.

Report on Partial Findings of an Ongoing Research: Social Networking Sites (SNS) as a Platform to Support Teaching and Learning in Secondary Schools

ERIC Educational Resources Information Center

Bt. Ubaidullah, Nor Hasbiah; Samsuddin, Khairulanuar; Bt. Fabil, Norsikin; Bt. Mahadi, Norhayati

2011-01-01

This paper reports the partial findings of a survey that was carried out in the analysis phase of an ongoing research for the development of a prototype of a Social Networking Site (SNS) to support teaching and learning in secondary schools. For the initial phase of the study, a quantitative research method was used based on a survey involving 383…

Social network analysis in the study of nonhuman primates: A historical perspective

PubMed Central

Brent, Lauren J.N.; Lehmann, Julia; Ramos-Fernández, Gabriel

2011-01-01

Advances over the last fifteen years have made social network analysis (SNA) a powerful tool for the study of nonhuman primate social behavior. Although many SNA-based techniques have been only very recently adopted in primatological research, others have been commonly used by primatologists for decades. The roots of SNA also stem from some of the same conceptual frameworks as the majority of nonhuman primate behavioral research. The rapid development of SNA in recent years has led to questions within the primatological community of where and how SNA fits within this field. We aim to address these questions by providing an overview of the historical relationship between SNA and the study of nonhuman primates. We begin with a brief history of the development of SNA, followed by a detailed description of the network-based visualization techniques, analytical methods and conceptual frameworks which have been employed by primatologists since as early as the 1960s. We also introduce some of the latest advances to SNA, thereby demonstrating that this approach contains novel tools for study of nonhuman primate social behavior which may be used to shed light on questions that cannot be addressed fully using more conventional methods. PMID:21433047

Detection of communities with Naming Game-based methods

PubMed Central

Ribeiro, Carlos Henrique Costa

2017-01-01

Complex networks are often organized in groups or communities of agents that share the same features and/or functions, and this structural organization is built naturally with the formation of the system. In social networks, we argue that the dynamic of linguistic interactions of agreement among people can be a crucial factor in generating this community structure, given that sharing opinions with another person bounds them together, and disagreeing constantly would probably weaken the relationship. We present here a computational model of opinion exchange that uncovers the community structure of a network. Our aim is not to present a new community detection method proper, but to show how a model of social communication dynamics can reveal the (simple and overlapping) community structure in an emergent way. Our model is based on a standard Naming Game, but takes into consideration three social features: trust, uncertainty and opinion preference, that are built over time as agents communicate among themselves. We show that the separate addition of each social feature in the Naming Game results in gradual improvements with respect to community detection. In addition, the resulting uncertainty and trust values classify nodes and edges according to role and position in the network. Also, our model has shown a degree of accuracy both for non-overlapping and overlapping communities that are comparable with most algorithms specifically designed for topological community detection. PMID:28797097

How Urban Youth Perceive Relationships among School Environments, Social Networks, Self-Concept, and Substance Use

PubMed Central

Dudovitz, Rebecca N.; Perez-Aguilar, Giselle; Kim, Grace; Wong, Mitchell D.; Chung, Paul J.

2016-01-01

Objective Studies suggest adolescent substance use aligns with academic and behavioral self-concept (whether teens think of themselves as good or bad students and as rule followers or rule breakers) as well as peer and adult social networks. Schools are an important context in which self-concept and social networks develop, but it remains unclear how school environments might be leveraged to promote healthy development and prevent substance use. We sought to describe how youth perceive the relationships among school environments, adolescent self-concept, social networks, and substance use. Methods Semi-structured interviews with 32 low-income minority youth (ages 17-22) who participated in a prior study, explored self-concept development, school environments, social networks, and substance use decisions. Recruitment was stratified by whether, during high school, they had healthy or unhealthy self-concept profiles and had engaged in or abstained from substance use. Results Youth described feeling labeled by peers and teachers and how these labels became incorporated into their self-concept. Teachers who made students feel noticed (e.g., by learning students' names) and had high academic expectations reinforced healthy self-concepts. Academic tracking, extra-curricular activities, and school norms determined potential friendship networks, grouping students either with well-behaving or misbehaving peers. Youth described peer groups, combined with their self-concept, shaping their substance use decisions. Affirming healthy aspects of their self-concept at key risk behavior decision points helped youth avoid substance use in the face of peer pressure. Conclusions Youth narratives suggest school environments shape adolescent self-concept and adult and peer social networks, all of which impact substance use. PMID:28259338

Social Networks, Social Circles, and Job Satisfaction.

ERIC Educational Resources Information Center

Hurlbert, Jeanne S.

1991-01-01

Tests the hypothesis that social networks serve as a social resource that effects job satisfaction through the provision of social support. Argues that three types of networks are likely to affect job satisfaction: dense networks, social circles composed of co-workers, and kin-centered networks. (JOW)

Using social network methods to reach out-of-care or ART-nonadherent HIV+ injection drug users in Russia: addressing a gap in the treatment cascade.

PubMed

Amirkhanian, Yuri; Kelly, Jeffrey; Kuznetsova, Anna; Meylakhs, Anastasia; Yakovlev, Alexey; Musatov, Vladimir; Chaika, Nikolay

2014-01-01

HIV treatment to reduce downstream HIV incidence and to decrease disease mortality and morbidity at a population level both require that hidden, out-of-care people living with HIV (PLH) in the community be reached and engaged to enter care. This research evaluated the feasibility of reaching out-of-care or non-adherent PLH through members of their social networks in St Petersburg, Russia. To recruit a social network sample of HIV-positive injection drug users, 16 HIV+ seeds were enrolled into the study through PLH-oriented websites and online forums using recruitment ads or approached in needle exchange sites. Interested persons called the study phone number and completed a brief eligibility interview. Seed inclusion criteria were HIV+ status, being 18 years or older, having ever injected drugs, and having not visited an HIV doctor in the past 6 months. Seeds provided blood specimens tested for HIV to confirm their self-reported status. Eligible seeds were enrolled, completed brief network elicitation interview, and were asked to invite their own HIV+ friends into the study. Incentives were provided as compensation for participants' time and additional smaller incentives were provided for inviting each HIV+ network member to also participate. The seed's PLH friends established the first ring of participants who, in turn were asked to invite their own PLH friends (second ring). All study participants completed assessment of psychosocial wellbeing and sexual and injection-related HIV risk behaviour. Blood samples were collected from all participants to confirm their HIV+ status. Through this chain referral process, the initial 16 seeds led to the enrolment of a total of 66 PLH from the community (mean=4 per initial seed), most of whom - like the seed - were not presently in HIV care or were ART non-adherent. Implementation of treatment cascade goals requires complementing conventional paths of identifying PLH with feasible and effective community-based approaches such as described in this study. This research establishes that PLH are connected in their day-to-day social networks with other HIV+ persons and shows that social network methods can be employed to reach infected persons through their connections with other PLH. This method has the potential to expand the reach of medical care efforts and ART uptake.

A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

ERIC Educational Resources Information Center

Gou, Liang

2012-01-01

Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

Personal Network Correlates of Alcohol, Cigarette, and Marijuana Use Among Homeless Youth

PubMed Central

Wenzel, Suzanne L.; Tucker, Joan S.; Golinelli, Daniela; Green, Harold D.; Zhou, Annie

2013-01-01

Background Youth who are homeless and on their own are among the most marginalized individuals in the United States and face multiple risks, including use of substances. This study investigates how the use of alcohol, cigarettes, and marijuana among homeless youth may be influenced by characteristics of their social networks. Methods Homeless youth aged 13–24 were randomly sampled from 41 service and street sites in Los Angeles County (N = 419). Predictors of substance use were examined using linear regression analysis (for average number of drinks and average number of cigarettes per day) and negative binomal regression analysis (for frequency of past month marijuana use). Results Youth with more substance users in their networks reported greater alcohol, cigarette, and marijuana consumption regardless of whether these network members provided tangible or emotional support. Marijuana use was more frequent for youth who met more network members through homeless settings, but less frequent among those who met more network members through treatment or AA/NA. Greater alcohol use occurred among youth who met more network members through substance use-related activities. Youth having more adults in positions of responsibility in their networks consumed less alcohol, and those with more school attendees in their networks consumed less alcohol and cigarettes. Conclusions Findings highlight the importance of social context in understanding substance use among homeless youth. Results also support the relevance of network-based interventions to change social context for substance using youth, in terms of both enhancing pro-social influences and reducing exposure to substance use. PMID:20656423

As tall as my peers - similarity in body height between migrants and hosts.

PubMed

Bogin, Barry; Hermanussen, Michael; Scheffler, Christiane

2018-01-12

Background: We define migrants as people who move from their place of birth to a new place of residence. Migration usually is directed by "Push-Pull" factors, for example to escape from poor living conditions or to find more prosperous socio-economic conditions. Migrant children tend to assimilate quickly, and soon perceive themselves as peers within their new social networks. Differences exist between growth of first generation and second generation migrants. Methods: We review body heights and height distributions of historic and modern migrant populations to test two hypotheses: 1) that migrant and adopted children coming from lower social status localities to higher status localities adjust their height growth toward the mean of the dominant recipient social network, and 2) social dominant colonial and military migrants display growth that significantly surpasses the median height of both the conquered population and the population of origin. Our analytical framework also considered social networks. Recent publications indicate that spatial connectedness (community effects) and social competitiveness can affect human growth. Results: Migrant children and adolescents of lower social status rapidly adjust in height towards average height of their hosts, but tend to mature earlier, and are prone to overweight. The mean height of colonial/military migrants does surpass that of the conquered and origin population. Conclusion: Observations on human social networks, non-human animal strategic growth adjustments, and competitive growth processes strengthen the concept of social connectedness being involved in the regulation of human migrant growth.

Predicting Regional Self-identification from Spatial Network Models

PubMed Central

Almquist, Zack W.; Butts, Carter T.

2014-01-01

Social scientists characterize social life as a hierarchy of environments, from the micro level of an individual’s knowledge and perceptions to the macro level of large-scale social networks. In accordance with this typology, individuals are typically thought to reside in micro- and macro-level structures, composed of multifaceted relations (e.g., acquaintanceship, friendship, and kinship). This article analyzes the effects of social structure on micro outcomes through the case of regional identification. Self identification occurs in many different domains, one of which is regional; i.e., the identification of oneself with a locationally-associated group (e.g., a “New Yorker” or “Parisian”). Here, regional self-identification is posited to result from an influence process based on the location of an individual’s alters (e.g., friends, kin or coworkers), such that one tends to identify with regions in which many of his or her alters reside. The structure of this paper is laid out as follows: initially, we begin with a discussion of the relevant social science literature for both social networks and identification. This discussion is followed with one about competing mechanisms for regional identification that are motivated first from the social network literature, and second by the social psychological and cognitive literature of decision making and heuristics. Next, the paper covers the data and methods employed to test the proposed mechanisms. Finally, the paper concludes with a discussion of its findings and further implications for the larger social science literature. PMID:25684791

Social network analysis of public health programs to measure partnership.

PubMed

Schoen, Martin W; Moreland-Russell, Sarah; Prewitt, Kim; Carothers, Bobbi J

2014-12-01

In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

CI-KNOW: Cyberinfrastructure Knowledge Networks on the Web. A Social Network Enabled Recommender System for Locating Resources in Cyberinfrastructures

NASA Astrophysics Data System (ADS)

Green, H. D.; Contractor, N. S.; Yao, Y.

2006-12-01

A knowledge network is a multi-dimensional network created from the interactions and interconnections among the scientists, documents, data, analytic tools, and interactive collaboration spaces (like forums and wikis) associated with a collaborative environment. CI-KNOW is a suite of software tools that leverages automated data collection, social network theories, analysis techniques and algorithms to infer an individual's interests and expertise based on their interactions and activities within a knowledge network. The CI-KNOW recommender system mines the knowledge network associated with a scientific community's use of cyberinfrastructure tools and uses relational metadata to record connections among entities in the knowledge network. Recent developments in social network theories and methods provide the backbone for a modular system that creates recommendations from relational metadata. A network navigation portlet allows users to locate colleagues, documents, data or analytic tools in the knowledge network and to explore their networks through a visual, step-wise process. An internal auditing portlet offers administrators diagnostics to assess the growth and health of the entire knowledge network. The first instantiation of the prototype CI-KNOW system is part of the Environmental Cyberinfrastructure Demonstration project at the National Center for Supercomputing Applications, which supports the activities of hydrologic and environmental science communities (CLEANER and CUAHSI) under the umbrella of the WATERS network environmental observatory planning activities (http://cleaner.ncsa.uiuc.edu). This poster summarizes the key aspects of the CI-KNOW system, highlighting the key inputs, calculation mechanisms, and output modalities.

Semantic Networks and Social Networks

ERIC Educational Resources Information Center

Downes, Stephen

2005-01-01

Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

The Mediating Role of Loneliness in the Relation Between Social Engagement and Depressive Symptoms Among Older Korean Americans: Do Men and Women Differ?

PubMed Central

2013-01-01

Objectives. This study conceptualized loneliness as a mediator in the relation between social engagement and depressive symptoms and explored gender differences in the mediation model. Various indices of social engagement were considered including living arrangement, social network, and activity participation. Method. Using data from 674 community-dwelling Korean American older adults, we first examined the mediation effect of loneliness in the relation between each of 3 indices of social engagement (not living alone, social network, and activity participation) and depressive symptoms. Subsequently, gender differences in the mediation model were examined. Results. As hypothesized, loneliness was found to mediate the relation between each of the indices of social engagement and depressive symptoms in both men and women. We also observed gender differences in the strength of mediating effects; the effect of living alone was more likely to be mediated by loneliness among men, whereas women showed greater levels of mediation in the models with social network and activity participation. Discussion. Our findings suggest that loneliness may explain the mechanism by which deficits in social engagement exerts its effect on depressive symptoms and that gender differences should be considered in interventions targeting social engagement for mental health promotion. PMID:22929386

Interests diffusion on a semantic multiplex. Comparing Computer Science and American Physical Society communities

NASA Astrophysics Data System (ADS)

D'Agostino, Gregorio; De Nicola, Antonio

2016-10-01

Exploiting the information about members of a Social Network (SN) represents one of the most attractive and dwelling subjects for both academic and applied scientists. The community of Complexity Science and especially those researchers working on multiplex social systems are devoting increasing efforts to outline general laws, models, and theories, to the purpose of predicting emergent phenomena in SN's (e.g. success of a product). On the other side the semantic web community aims at engineering a new generation of advanced services tailored to specific people needs. This implies defining constructs, models and methods for handling the semantic layer of SNs. We combined models and techniques from both the former fields to provide a hybrid approach to understand a basic (yet complex) phenomenon: the propagation of individual interests along the social networks. Since information may move along different social networks, one should take into account a multiplex structure. Therefore we introduced the notion of "Semantic Multiplex". In this paper we analyse two different semantic social networks represented by authors publishing in the Computer Science and those in the American Physical Society Journals. The comparison allows to outline common and specific features.

A qualitative exploration of the role of social networks in educating urban African American adolescents about sex.

PubMed

George, Anne E; Abatemarco, Diane J; Terry, Martha Ann; Yonas, Michael; Butler, James; Akers, Aletha Y

2013-01-01

To explore social network members' role in educating African American adolescents about sexual health issues. We conducted 21 focus groups with urban African American mothers (n=51), fathers (n=18), sons (n=20), and daughters (n=36) from Allegheny County, Pennsylvania, USA, between December 2007 and March 2008. At least one biological parent (or legal guardian) and one adolescent aged 15-17 years from each family participated. Group conversations were audio-recorded, transcribed, and analyzed using directive content analysis and the constant comparison method. Two coders independently read each transcript to identify emergent themes. A broad range of people were reportedly involved in the education process. Older siblings, extended family, and peers were most commonly cited. However, unrelated adults were also described as playing important roles. Unrelated adults included the friends of an adolescent's parents and the parents of an adolescent's friends or romantic partners. Social network members were said to address three main issues: the facts about sex and sexuality, the social aspects of sexuality (e.g., appropriate dating behaviors, choosing dating partners), and promotion of family values. When educating adolescents about sex, social network members were described as playing eight functional roles, including that of a teacher, guide, challenger, confidant, shelterer, supervisor-chaperone, role model, and provider of access to reproductive health services. These roles were not mutually exclusive, meaning that social network members often assumed different roles depending on the situation. The influence of individuals who were not an adolescent's parent was highly dependent on adolescents' relationship with their parents or on their parents' comfort dealing with sexual issues. African American adolescents' social networks were described by parents and adolescents as dense, complex, and routinely involved in educating adolescents about sex.

Position-Specific HIV Risk in a Large Network of Homeless Youths

PubMed Central

Barman-Adhikari, Anamika; Milburn, Norweeta G.; Monro, William

2012-01-01

Objectives. We examined interconnections among runaway and homeless youths (RHYs) and how aggregated network structure position was associated with HIV risk in this population. Methods. We collected individual and social network data from 136 RHYs. On the basis of these data, we generated a sociomatrix, accomplished network visualization with a “spring embedder,” and examined k-cores. We used multivariate logistic regression models to assess associations between peripheral and nonperipheral network position and recent unprotected sexual intercourse. Results. Small numbers of nominations at the individual level aggregated into a large social network with a visible core, periphery, and small clusters. Female youths were more likely to be in the core, as were youths who had been homeless for 2 years or more. Youths at the periphery were less likely to report unprotected intercourse and had been homeless for a shorter duration. Conclusions. HIV risk was a function of risk-taking youths' connections with one another and was associated with position in the overall network structure. Social network–based prevention programs, young women's housing and health programs, and housing-first programs for peripheral youths could be effective strategies for preventing HIV among this population. PMID:22095350

An examination of the relationship between athlete leadership and cohesion using social network analysis.

PubMed

Loughead, Todd M; Fransen, Katrien; Van Puyenbroeck, Stef; Hoffmann, Matt D; De Cuyper, Bert; Vanbeselaere, Norbert; Boen, Filip

2016-11-01

Two studies investigated the structure of different athlete leadership networks and its relationship to cohesion using social network analysis. In Study 1, we examined the relationship between a general leadership quality network and task and social cohesion as measured by the Group Environment Questionnaire (GEQ). In Study 2, we investigated the leadership networks for four different athlete leadership roles (task, motivational, social and external) and their association with task and social cohesion networks. In Study 1, the results demonstrated that the general leadership quality network was positively related to task and social cohesion. The results from Study 2 indicated positive correlations between the four leadership networks and task and social cohesion networks. Further, the motivational leadership network emerged as the strongest predictor of the task cohesion network, while the social leadership network was the strongest predictor of the social cohesion network. The results complement a growing body of research indicating that athlete leadership has a positive association with cohesion.

Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks

PubMed Central

Wuchty, Stefan; Uzzi, Brian

2011-01-01

Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's “social network” of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions. PMID:22114665

Use of formative research and social network theory to develop a group walking intervention: Sumter County on the Move!

PubMed

Forthofer, Melinda; Burroughs-Girardi, Ericka; Stoisor-Olsson, Liliana; Wilcox, Sara; Sharpe, Patricia A; Pekuri, Linda M

2016-10-01

Although social support is a frequently cited enabler of physical activity, few studies have examined how to harness social support in interventions. This paper describes community-based formative research to design a walking program for mobilizing naturally occurring social networks to support increases in walking behavior. Focus group methods were used to engage community members in discussions about desired walking program features. The research was conducted with underserved communities in Sumter County, South Carolina. The majority of focus group participants were women (76%) and African American (92%). Several important themes emerged from the focus group results regarding attitudes toward walking, facilitators of and barriers to walking, ideal walking program characteristics, and strategies for encouraging community members to walk. Most noteably, the role of existing social networks as a supportive influence on physical activity was a recurring theme in our formative research and a gap in the existing evidence base. The resulting walking program focused on strategies for mobilizing, supporting and reinforcing existing social networks as mechanisms for increasing walking. Our approach to linking theory, empirical evidence and community-based formative research for the development of a walking intervention offers an example for practitioners developing intervention strategies for a wide range of behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Responses to a Self-Presented Suicide Attempt in Social Media

PubMed Central

Fu, King-wa; Cheng, Qijin; Wong, Paul W.C.; Yip, Paul S. F.

2014-01-01

Background The self-presentation of suicidal acts in social media has become a public health concern. Aims This article centers on a Chinese microblogger who posted a wrist-cutting picture that was widely circulated in Chinese social media in 2011. This exploratory study examines written reactions of a group of Chinese microbloggers exposed to the post containing a self-harming message and photo. In addition, we investigate the pattern of information diffusion via a social network. Methods We systematically collected and analyzed 5,971 generated microblogs and the network of information diffusion. Results We found that a significant portion of written responses (36.6%) could help vulnerable netizens by providing peer-support and calls for help. These responses were reposted and diffused via an online social network with markedly more clusters of users – and at a faster pace – than a set of randomly generated networks. Conclusions We conclude that social media can be a double-edged sword: While it may contagiously affect others by spreading suicidal thoughts and acts, it may also play a positive role by assisting people at risk for suicide, providing rescue or support. More research is needed to learn how suicidally vulnerable people interact with online suicide information, and how we can effectively intervene. PMID:23871954

Depression, Smoking, and Ego-Centric Social Network Characteristics in Ohio Appalachian Women.

PubMed

Lam, Jeffrey; Lu, Bo; Doogan, Nate; Thomson, Tiffany; Ferketich, Amy; Paskett, Electra D; Wewers, Mary Ellen

2017-01-01

Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73-0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02-1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24-1.45), loneliness score (OR = 1.37, 95% CI 1.05-1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02-1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice.

Sexual health promotion on social networking sites: a process evaluation of The FaceSpace Project.

PubMed

Nguyen, Phuong; Gold, Judy; Pedrana, Alisa; Chang, Shanton; Howard, Steve; Ilic, Olivia; Hellard, Margaret; Stoove, Mark

2013-07-01

This article reports findings from an evaluation of reach and engagement of The FaceSpace Project, a novel sexual health promotion project delivered through social networking sites that targeted young people aged 16-29 years. Multiple methods were used to evaluate project reach and engagement. The evaluation focussed on quantitative data (online usage statistics, online surveys), complemented by available qualitative data (project team meeting notes). The project reached 900 fans who were mostly between 18 and 34 years of age. The most successful ways of increasing audience reach were via Facebook advertisements and tagging photos of young people attending a music festival on the project Facebook page. Peaks in Facebook page interactions (comments and "likes") coincided with recruitment peaks and when videos were posted. However, video views varied greatly between postings. Feedback from the project team for increasing engagement in future social networking site interventions included having one centralized Facebook page and using episodic videos. This evaluation is among the first to assess the use of social networking sites for sexual health promotion and provides information to inform the implementation and evaluation of future projects using new media. Social networking sites offer great potential to reach and engage young people for sexual health promotion. However, further work is required to improve implementation and promote audience reach and engagement as well as to determine effectiveness of social networking sites in changing knowledge, attitudes, and behaviors. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Applications of Social Network Analysis

NASA Astrophysics Data System (ADS)

Thilagam, P. Santhi

A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

Using Facebook™ to recruit college-age men for a Human Papillomavirus vaccine trial

PubMed Central

Raviotta, Jonathan M.; Nowalk, Mary Patricia; Lin, Chyongchiou Jeng; Huang, Hsin-Hui; Zimmerman, Richard K.

2015-01-01

Background College-age men were recruited using Facebook™ advertisements (ads), as well as traditional recruitment methods, for a randomized controlled trial to compare immunological responses to human papilloma virus (HPV) vaccine administered in two dosing schedules. This study compares enrollees who were recruited through traditional recruitment methods vs. social networking sites including Facebook™. Methods Potential participants were recruited using fliers posted on and off campus(es), and distributed at health fairs, classes, sporting and other campus events; e-mails to students and student organizations; and print advertisements in student newspapers and on city buses. Facebook™ ads were displayed to users with specific age, geographic, and interest characteristics; ads were monitored daily to make adjustments to improve response. Results 220 males, ages 18–25 years enrolled between October 2010 and May 2011. The majority of participants (51%) reported print advertisements as the method by which they first heard about the study, followed by personal contact (29%) and Facebook™ or other social networking site (SNS; 20%). The likelihood of SNS being the source by which the participant first heard about the study compared with traditional methods was increased if the participant reported: 1) being homosexual or bisexual; or 2) posting daily updates on SNS. Conclusions Facebook™ and other social networking sites are a viable recruitment strategy for reaching potential clinical trial participants among groups who typically use social media to stay connected with their friends and hard-to-reach groups such as young men who self-identify as homosexual or bisexual. PMID:25389213

Trust Maximization in Social Networks

NASA Astrophysics Data System (ADS)

Zhan, Justin; Fang, Xing

Trust is a human-related phenomenon in social networks. Trust research on social networks has gained much attention on its usefulness, and on modeling propagations. There is little focus on finding maximum trust in social networks which is particularly important when a social network is oriented by certain tasks. In this paper, we propose a trust maximization algorithm based on the task-oriented social networks.

Information Extraction from Large-Multi-Layer Social Networks

DTIC Science & Technology

2015-08-06

mization [4]. Methods that fall into this category include spec- tral algorithms, modularity methods, and methods that rely on statistical inference...Snijders and Chris Baerveldt, “A multilevel network study of the effects of delinquent behavior on friendship evolution,” Journal of mathematical sociol- ogy...1970. [10] Ulrike Luxburg, “A tutorial on spectral clustering,” Statistics and Computing, vol. 17, no. 4, pp. 395–416, Dec. 2007. [11] R. A. Fisher, “On

The use of nodes attributes in social network analysis with an application to an international trade network

NASA Astrophysics Data System (ADS)

de Andrade, Ricardo Lopes; Rêgo, Leandro Chaves

2018-02-01

The social network analysis (SNA) studies the interactions among actors in a network formed through some relationship (friendship, cooperation, trade, among others). The SNA is constantly approached from a binary point of view, i.e., it is only observed if a link between two actors is present or not regardless of the strength of this link. It is known that different information can be obtained in weighted and unweighted networks and that the information extracted from weighted networks is more accurate and detailed. Another rarely discussed approach in the SNA is related to the individual attributes of the actors (nodes), because such analysis is usually focused on the topological structure of networks. Features of the nodes are not incorporated in the SNA what implies that there is some loss or misperception of information in those analyze. This paper aims at exploring more precisely the complexities of a social network, initially developing a method that inserts the individual attributes in the topological structure of the network and then analyzing the network in four different ways: unweighted, edge-weighted and two methods for using both edge-weights and nodes' attributes. The international trade network was chosen in the application of this approach, where the nodes represent the countries, the links represent the cash flow in the trade transactions and countries' GDP were chosen as nodes' attributes. As a result, it is possible to observe which countries are most connected in the world economy and with higher cash flows, to point out the countries that are central to the intermediation of the wealth flow and those that are most benefited from being included in this network. We also made a principal component analysis to study which metrics are more influential in describing the data variability, which turn out to be mostly the weighted metrics which include the nodes' attributes.

Looking for robust properties in the growth of an academic network: the case of the Uruguayan biological research community.

PubMed

Cabana, Alvaro; Mizraji, Eduardo; Pomi, Andrés; Valle-Lisboa, Juan Carlos

2008-04-01

Graph-theoretical methods have recently been used to analyze certain properties of natural and social networks. In this work, we have investigated the early stages in the growth of a Uruguayan academic network, the Biology Area of the Programme for the Development of Basic Science (PEDECIBA). This transparent social network is a territory for the exploration of the reliability of clustering methods that can potentially be used when we are confronted with opaque natural systems that provide us with a limited spectrum of observables (happens in research on the relations between brain, thought and language). From our social net, we constructed two different graph representations based on the relationships among researchers revealed by their co-participation in Master's thesis committees. We studied these networks at different times and found that they achieve connectedness early in their evolution and exhibit the small-world property (i.e. high clustering with short path lengths). The data seem compatible with power law distributions of connectivity, clustering coefficients and betweenness centrality. Evidence of preferential attachment of new nodes and of new links between old nodes was also found in both representations. These results suggest that there are topological properties observed throughout the growth of the network that do not depend on the representations we have chosen but reflect intrinsic properties of the academic collective under study. Researchers in PEDECIBA are classified according to their specialties. We analysed the community structure detected by a standard algorithm in both representations. We found that much of the pre-specified structure is recovered and part of the mismatches can be attributed to convergent interests between scientists from different sub-disciplines. This result shows the potentiality of some clustering methods for the analysis of partially known natural systems.

Use of Social Media for Professional Development by Health Care Professionals: A Cross-Sectional Web-Based Survey

PubMed Central

2016-01-01

Background Social media can be used in health care settings to enhance professional networking and education; patient communication, care, and education; public health programs; organizational promotion; and research. Objective The aim of this study was to explore the use of social media networks for the purpose of professional development among health care professionals in Saudi Arabia using a purpose-designed Web-based survey. Methods A cross-sectional web-based survey was undertaken. A link to the survey was posted on the investigator’s personal social media accounts including Twitter, LinkedIn, and WhatsApp. Results A total of 231 health care professionals, who are generally social media users, participated in the study. Of these professionals, 70.6% (163/231) use social media for their professional development. The social media applications most frequently used, in the descending order, for professional development were Twitter, YouTube, Instagram, Facebook, Snapchat, and LinkedIn. The majority of respondents used social media for professional development irrespective of their age group, with the highest proportion seen in those aged 20-30 years. Social media were perceived as being most beneficial for professional development in terms of their impact on the domains of knowledge and problem solving and least helpful for enhancing clinical skills. Twitter was perceived as the most helpful type of social media for all domains listed. Respondents most frequently reported that social media were useful for professional development for the reasons of knowledge exchange and networking. Conclusions Social media are frequently used by health care professionals in Saudi Arabia for the purposes of professional development, with Twitter most frequently used for this purpose. These findings suggest that social media networks can be powerful tools for engaging health care professionals in their professional development. PMID:27731855

Properties of on-line social systems

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kruszewska, N.; Kosiński, R. A.

2008-11-01

We study properties of five different social systems: (i) internet society of friends consisting of over 106 people, (ii) social network consisting of 3 × 104 individuals, who interact in a large virtual world of Massive Multiplayer Online Role Playing Games (MMORPGs), (iii) over 106 users of music community website, (iv) over 5 × 106 users of gamers community server and (v) over 0.25 × 106 users of books admirer website. Individuals included in large social network form an Internet community and organize themselves in groups of different sizes. The destiny of those systems, as well as the method of creating of new connections, are different, however we found that the properties of these networks are very similar. We have found that the network components size distribution follow the power-law scaling form. In all five systems we have found interesting scaling laws concerning human dynamics. Our research has shown how long people are interested in a single task, how much time they devote to it and how fast they are making friends. It is surprising that the time evolution of an individual connectivity is very similar in each system.

A snapshot of how latino heterosexual men promote sexual health within their social networks: process evaluation findings from an efficacious community-level intervention.

PubMed

Rhodes, Scott D; Daniel, Jason; Alonzo, Jorge; Vissman, Aaron T; Duck, Stacy; Downs, Mario; Gilbert, Paul A

2012-12-01

Hombres Manteniendo Bienestar y Relaciones Saludables (HoMBReS) was a community-level social network intervention designed to increase sexual health among Latino heterosexual men who were members of a multicounty soccer league. Process data were collected each month during 18 months of intervention implementation from each of 15 trained Latino male lay health advisors (known as Navegantes) to explore the activities that Navegantes conducted to increase condom and HIV testing among their social network members. The Navegantes reported conducting 2,364 activities, for a mean of 8.8 activities per Navegante per month. The most common activity was condom distribution. Most activities were conducted with men; about 2% were conducted with women. Among activities conducted with men, half were conducted with soccer teammates and half with nonteammates. Results suggest that Latino men's social networks can be leveraged to promote sexual health within the community. Innovative methods that reach large numbers of community members are needed given the lack of prevention resources for populations disproportionately impacted by HIV and STDs.

Understanding Process in Group-Based Intervention Delivery: Social Network Analysis and Intra-entity Variability Methods as Windows into the "Black Box".

PubMed

Molloy Elreda, Lauren; Coatsworth, J Douglas; Gest, Scott D; Ram, Nilam; Bamberger, Katharine

2016-11-01

Although the majority of evidence-based programs are designed for group delivery, group process and its role in participant outcomes have received little empirical attention. Data were collected from 20 groups of participants (94 early adolescents, 120 parents) enrolled in an efficacy trial of a mindfulness-based adaptation of the Strengthening Families Program (MSFP). Following each weekly session, participants reported on their relations to group members. Social network analysis and methods sensitive to intraindividual variability were integrated to examine weekly covariation between group process and participant progress, and to predict post-intervention outcomes from levels and changes in group process. Results demonstrate hypothesized links between network indices of group process and intervention outcomes and highlight the value of this unique analytic approach to studying intervention group process.

I am no longer alone – How do university students perceive the possibilities of social media?

PubMed Central

Uusiautti, Satu; Määttä, Kaarina

2014-01-01

An increasing number of people have become users of social media, mostly looking for social contacts and networking. But what kind of social capital do social networking services (SNSs) provide? University students' (N = 90) experiences of and opinions on social media were studied through a semi-structured questionnaire. The following research questions were set for this study: (1) What kinds of benefits do university students perceive in the usage of social media? and (2) What kind of social capital does social media produce according to university students' opinions? Their answers were analysed with the qualitative content analysis method. The results revealed that SNSs can increase students' social capital in many ways, such as in the form of peer support groups and learning environments, and enhance bonding and communality in them. These possibilities should be better studied in educational contexts, as they can have a positive impact on students' well-being, engagement to studies and, thus, study success. PMID:25431510