[Applying a social network for the practice and learning of psychiatry].

PubMed

Mondin, Estefanía; Matusevich, Daniel

2014-01-01

Social networking is a virtual space in which people relate and build their identity, share information, publish content and intervene on the content posted by others. We will describe an experiment carried out in the psychiatry service of Italian Hospital in Buenos Aires, in which we use Whatsapp Social Network applied to the development of clinical work and teaching task. From these new ways of relating between professional, emerge a new way to work, participate in groups or try to evaluate various options for dealing with a patient. We analyze the usefulness of this virtual platform as a working tool.

Know the Network, Knit the Network: Applying SNA to N2C2 Maturity Model Experiments

DTIC Science & Technology

2010-06-01

Networks (COINS) 2009. Procedia - Social and Behavioral Sciences (2009). Snijders, Tom A.B., Christian E. G. Steglich and Michael Schweinberger...8217 patterning that create social structures. As an interdisciplinary behavioural science specialty, SNA defends that social actors are interdependent...production of social science data involve a process of interpretation. To carry out such interpretation robustly it is understood that it is imperative to

Finding meaning in social media: content-based social network analysis of QuitNet to identify new opportunities for health promotion.

PubMed

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

2013-01-01

Unhealthy behaviors increase individual health risks and are a socioeconomic burden. Harnessing social influence is perceived as fundamental for interventions to influence health-related behaviors. However, the mechanisms through which social influence occurs are poorly understood. Online social networks provide the opportunity to understand these mechanisms as they digitally archive communication between members. In this paper, we present a methodology for content-based social network analysis, combining qualitative coding, automated text analysis, and formal network analysis such that network structure is determined by the content of messages exchanged between members. We apply this approach to characterize the communication between members of QuitNet, an online social network for smoking cessation. Results indicate that the method identifies meaningful theme-based social sub-networks. Modeling social network data using this method can provide us with theme-specific insights such as the identities of opinion leaders and sub-community clusters. Implications for design of targeted social interventions are discussed.

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.

Applying gene regulatory network logic to the evolution of social behavior.

PubMed

Baran, Nicole M; McGrath, Patrick T; Streelman, J Todd

2017-06-06

Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

Leverage Between the Buffering Effect and the Bystander Effect in Social Networking.

PubMed

Chiu, Yu-Ping; Chang, Shu-Chen

2015-08-01

This study examined encouraged and inhibited social feedback behaviors based on the theories of the buffering effect and the bystander effect. A system program was used to collect personal data and social feedback from a Facebook data set to test the research model. The results revealed that the buffering effect induced a positive relationship between social network size and feedback gained from friends when people's social network size was under a certain cognitive constraint. For people with a social network size that exceeds this cognitive constraint, the bystander effect may occur, in which having more friends may inhibit social feedback. In this study, two social psychological theories were applied to explain social feedback behavior on Facebook, and it was determined that social network size and social feedback exhibited no consistent linear relationship.

The Social Networks of Children With and Without Disabilities in Early Childhood Special Education Classrooms.

PubMed

Chen, Jing; Lin, Tzu-Jung; Justice, Laura; Sawyer, Brook

2017-09-01

Interaction with peers is an important contributor to young children's social and cognitive development. Yet, little is known about the nature of social networks within preschool inclusive classrooms. The current study applied a social network analysis to characterize children's peer interactions in inclusive classrooms and their relations with children's disability status. The participants were 485 preschoolers from 64 early childhood special education (ECSE) inclusive classrooms. Results from teachers' report of children's social networks showed that children with disabilities formed smaller play networks compared to their typically developing peers in the classroom, but no evidence indicated that children with disabilities engaged in more conflict networks than their counterparts. Children's play and conflict networks were segregated by children's disability status.

Does the social capital in networks of “fish and fire” scientists and managers suggest learning?

Treesearch

A. Paige Fischer; Ken Vance-Borland; Kelly M. Burnett; Susan Hummel; Janean H. Creighton; Sherri L. Johnson; Lorien Jasny

2014-01-01

Patterns of social interaction influence how knowledge is generated, communicated, and applied. Theories of social capital and organizational learning suggest that interactions within disciplinary or functional groups foster communication of knowledge, whereas interactions across groups foster generation of new knowledge. We used social network analysis to examine...

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.

Evaluating Form and Function of Regional Partnerships: Applying Social Network Analysis to the "Network for a Healthy California", 2001-2007

ERIC Educational Resources Information Center

Gregson, Jennifer; Sowa, Marcy; Flynn, Heather Kohler

2011-01-01

Objective: To evaluate the partnership structure of the "Network for a Healthy California" ("Network"), a social marketing program, from 2001-2007, to determine if California's program was able to establish and maintain partnerships that (1) provided access to a local audience, (2) facilitated regional collaboration, (3)…

Social Support and Social Network Ties among the Homeless in a Downtown Atlanta Park

ERIC Educational Resources Information Center

Reitzes, Donald C.; Crimmins, Timothy J.; Yarbrough, Johanna; Parker, Josie

2011-01-01

This study applies a typology of social support with 3 categories of social networks to investigate social ties and their benefits for homeless people. Data were derived from a 2-year long series of participant observations of homeless or precariously housed people who came regularly to a downtown Atlanta public park. The findings are as follows:…

Animal welfare: a social networks perspective.

PubMed

Kleinhappel, Tanja K; John, Elizabeth A; Pike, Thomas W; Wilkinson, Anna; Burman, Oliver H P

2016-01-01

Social network theory provides a useful tool to study complex social relationships in animals. The possibility to look beyond dyadic interactions by considering whole networks of social relationships allows researchers the opportunity to study social groups in more natural ways. As such, network-based analyses provide an informative way to investigate the factors influencing the social environment of group-living animals, and so has direct application to animal welfare. For example, animal groups in captivity are frequently disrupted by separations, reintroductions and/or mixing with unfamiliar individuals and this can lead to social stress and associated aggression. Social network analysis ofanimal groups can help identify the underlying causes of these socially-derived animal welfare concerns. In this review we discuss how this approach can be applied, and how it could be used to identify potential interventions and solutions in the area of animal welfare.

Applying the Uses and Gratifications Theory to Compare Higher Education Students' Motivation for Using Social Networking Sites: Experiences from Iran, Malaysia, United Kingdom, and South Africa

ERIC Educational Resources Information Center

Karimi, Leila; Khodabandelou, Rouhollah; Ehsani, Maryam; Ahmad, Muhammad

2014-01-01

Drawing from the Uses and Gratifications Theory, this study examined the Gratification Sought and the Gratification Obtained from using Social Networking Sites among Iranian, Malaysian, British, and South African higher education students. This comparison allowed to drawing conclusions about how social networking sites fulfill users' needs with…

A Study of the Predictive Relationship between Online Social Presence and ONLE Interaction

ERIC Educational Resources Information Center

Tu, Chih-Hsiung; Yen, Cherng-Jyh; Blocher, J. Michael; Chan, Junn-Yih

2012-01-01

Open Network Learning Environments (ONLE) are online networks that afford learners the opportunity to participate in creative content endeavors, personalized identity projections, networked mechanism management, and effective collaborative community integration by applying Web 2.0 tools in open environments. It supports social interaction by…

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.

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

Understanding how social networking influences perceived satisfaction with conference experiences

USGS Publications Warehouse

van Riper, Carena J.; van Riper, Charles; Kyle, Gerard T.; Lee, Martha E.

2013-01-01

Social networking is a key benefit derived from participation in conferences that bind the ties of a professional community. Building social networks can lead to satisfactory experiences while furthering participants' long- and short-term career goals. Although investigations of social networking can lend insight into how to effectively engage individuals and groups within a professional cohort, this area has been largely overlooked in past research. The present study investigates the relationship between social networking and satisfaction with the 10th Biennial Conference of Research on the Colorado Plateau using structural equation modelling. Results partially support the hypothesis that three dimensions of social networking – interpersonal connections, social cohesion, and secondary associations – positively contribute to the performance of various conference attributes identified in two focus group sessions. The theoretical and applied contributions of this paper shed light on the social systems formed within professional communities and resource allocation among service providers.

The Manifestation of Biblical Community Understanding in a Facebook Community: A Qualitative Study among Christian College Students

ERIC Educational Resources Information Center

Perkins, Paul W.

2012-01-01

Applying theoretical studies of social capital, social presence, cognitive presence, and community helps researchers understand more fully the phenomenon of online social networks. The debate has moved from the positive and negative effects of online social networks to understanding how they fit into daily life. However, do biblical community…

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

Online Social Networks - Opportunities for Empowering Cancer Patients.

PubMed

Mohammadzadeh, Zeinab; Davoodi, Somayeh; Ghazisaeidi, Marjan

2016-01-01

Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

Semantic Social Network Portal for Collaborative Online Communities

ERIC Educational Resources Information Center

Neumann, Marco; O'Murchu, Ina; Breslin, John; Decker, Stefan; Hogan, Deirdre; MacDonaill, Ciaran

2005-01-01

Purpose: The motivation for this investigation is to apply social networking features to a semantic network portal, which supports the efforts in enterprise training units to up-skill the employee in the company, and facilitates the creation and reuse of knowledge in online communities. Design/methodology/approach: The paper provides an overview…

Spreading gossip in social networks.

PubMed

Lind, Pedro G; da Silva, Luciano R; Andrade, José S; Herrmann, Hans J

2007-09-01

We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

Spreading gossip in social networks

NASA Astrophysics Data System (ADS)

Lind, Pedro G.; da Silva, Luciano R.; Andrade, José S., Jr.; Herrmann, Hans J.

2007-09-01

We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

An Approach Based on Social Network Analysis Applied to a Collaborative Learning Experience

ERIC Educational Resources Information Center

Claros, Iván; Cobos, Ruth; Collazos, César A.

2016-01-01

The Social Network Analysis (SNA) techniques allow modelling and analysing the interaction among individuals based on their attributes and relationships. This approach has been used by several researchers in order to measure the social processes in collaborative learning experiences. But oftentimes such measures were calculated at the final state…

Seeking Social Capital and Expertise in a Newly-Formed Research Community: A Co-Author Analysis

ERIC Educational Resources Information Center

Forte, Christine E.

2017-01-01

This exploratory study applies social network analysis techniques to existing, publicly available data to understand collaboration patterns within the co-author network of a federally-funded, interdisciplinary research program. The central questions asked: What underlying social capital structures can be determined about a group of researchers…

Transition to parenthood: the role of social interaction and endogenous networks.

PubMed

Diaz, Belinda Aparicio; Fent, Thomas; Prskawetz, Alexia; Bernardi, Laura

2011-05-01

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdependencies across individuals' transition to parenthood and its timing, we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics: age, intended education, and parity. Agents endogenously form their network based on social closeness. Network members may then influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social interactions can explain the shift of first-birth probabilities in Austria during the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

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.

Similar but Different: Dynamic Social Network Analysis Highlights Fundamental Differences between the Fission-Fusion Societies of Two Equid Species, the Onager and Grevy’s Zebra

PubMed Central

Rubenstein, Daniel I.; Sundaresan, Siva R.; Fischhoff, Ilya R.; Tantipathananandh, Chayant; Berger-Wolf, Tanya Y.

2015-01-01

Understanding why animal societies take on the form that they do has benefited from insights gained by applying social network analysis to patterns of individual associations. Such analyses typically aggregate data over long time periods even though most selective forces that shape sociality have strong temporal elements. By explicitly incorporating the temporal signal in social interaction data we re-examine the network dynamics of the social systems of the evolutionarily closely-related Grevy’s zebras and wild asses that show broadly similar social organizations. By identifying dynamic communities, previously hidden differences emerge: Grevy’s zebras show more modularity than wild asses and in wild asses most communities consist of solitary individuals; and in Grevy’s zebras, lactating females show a greater propensity to switch communities than non-lactating females and males. Both patterns were missed by static network analyses and in general, adding a temporal dimension provides insights into differences associated with the size and persistence of communities as well as the frequency and synchrony of their formation. Dynamic network analysis provides insights into the functional significance of these social differences and highlights the way dynamic community analysis can be applied to other species. PMID:26488598

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 networking for nurse education: Possibilities, perils and pitfalls.

PubMed

Green, Janet; Wyllie, Aileen; Jackson, Debra

2014-01-01

Abstract In this paper, we consider the potential and implications of using social networking sites such as Facebook® in nurse education. The concept of social networking and the use of Facebook will be explored, as will the theoretical constructs specific to the use of online technology and Web 2.0 tools. Theories around Communities of Inquiry (Garrison, Anderson, & Archer, 2000), Communities of Practice (Wenger, 1998), Activity Theory (Daniels, Cole, & Wertsch, 2007) and Actor-Network theory (Latour, 1997) will be briefly explored, as will the work of Vygotsky (1978), as applies to the social aspects of learning. Boundary issues, such as if and how faculty and students should or could be connected via social networking sites will also be explored.

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.

Aging and social networks in Spain: the importance of pubs and churches.

PubMed

Buz, José; Sanchez, Marta; Levenson, Michael R; Aldwin, Carolyn M

2014-01-01

We examined whether the social convoy model and socioemotional selectivity theory apply in collectivistic cultures by examining the contextual factors which are hypothesized to mediate age-related differences in social support in a collectivist European country. Five hundred Spanish community-dwelling older adults (Mean age = 74.78, SD = 7.76, range = 60-93) were interviewed to examine structural aspects of their social networks. We found that age showed highly complex relationships with network size and frequency of interaction, depending on the network circle and the mediation of cultural factors. Family structure was important for social relations in the inner circle, while pubs and churches were important for peripheral relations. Surprisingly, pub attendance was the most important variable for maintenance of social support of peripheral network members. In general, the results support the applicability of the social convoy and socioemotional selectivity constructs to social support among Spanish older adults.

Information diffusion in structured online social networks

NASA Astrophysics Data System (ADS)

Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

2015-05-01

Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

Social Networks and Welfare in Future Animal Management.

PubMed

Koene, Paul; Ipema, Bert

2014-03-17

It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

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.

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.

Friendship and Alcohol Use in Early Adolescence: A Multilevel Social Network Approach

ERIC Educational Resources Information Center

Knecht, Andrea B.; Burk, William J.; Weesie, Jeroen; Steglich, Christian

2011-01-01

This study applies multilevel social network analytic techniques to examine processes of homophilic selection and social influence related to alcohol use among friends in early adolescence. Participants included 3,041 Dutch youth (M age =12 years, 49% female) from 120 classrooms in 14 schools. Three waves with 3-month intervals of friendship…

Understanding complex interactions using social network analysis.

PubMed

Pow, Janette; Gayen, Kaberi; Elliott, Lawrie; Raeside, Robert

2012-10-01

The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Review of literature and illustration of the application of the method of social network analysis using research examples. First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider. © 2012 Blackwell Publishing Ltd.

Transformation of social networks in the late pre-Hispanic US Southwest.

PubMed

Mills, Barbara J; Clark, Jeffery J; Peeples, Matthew A; Haas, W R; Roberts, John M; Hill, J Brett; Huntley, Deborah L; Borck, Lewis; Breiger, Ronald L; Clauset, Aaron; Shackley, M Steven

2013-04-09

The late pre-Hispanic period in the US Southwest (A.D. 1200-1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure.

Transformation of social networks in the late pre-Hispanic US Southwest

PubMed Central

Mills, Barbara J.; Clark, Jeffery J.; Peeples, Matthew A.; Haas, W. R.; Roberts, John M.; Hill, J. Brett; Huntley, Deborah L.; Borck, Lewis; Breiger, Ronald L.; Clauset, Aaron; Shackley, M. Steven

2013-01-01

The late pre-Hispanic period in the US Southwest (A.D. 1200–1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure. PMID:23530201

Privacy-preserving discovery of topic-based events from social sensor signals: an experimental study on Twitter.

PubMed

Nguyen, Duc T; Jung, Jai E

2014-01-01

Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.

Can Burt's Theory of Structural Holes be Applied to Study Social Support Among Mid-Age Female Sex Workers? A Multi-Site Egocentric Network Study in China.

PubMed

Liu, Hongjie

2017-12-01

The epidemic of HIV/AIDS continues to spread among older adults and mid-age female sex workers (FSWs) over 35 years old. We used egocentric network data collected from three study sites in China to examine the applicability of Burt's Theory of Social Holes to study social support among mid-age FSWs. Using respondent-driven sampling, 1245 eligible mid-age FSWs were interviewed. Network structural holes were measured by network constraint and effective size. Three types of social networks were identified: family networks, workplace networks, and non-FSW networks. A larger effective size was significantly associated with a higher level of social support [regression coefficient (β) 5.43-10.59] across the three study samples. In contrast, a greater constraint was significantly associated with a lower level of social support (β -9.33 to -66.76). This study documents the applicability of the Theory of Structural Holes in studying network support among marginalized populations, such as FSWs.

Role of Social Networks in Developing Religious and Social Values of the Students of the World Islamic Sciences & Education University

ERIC Educational Resources Information Center

Al-Mosa, Nosiba Ali

2015-01-01

The study aimed to identify the role of Social Networks in the social and religious values of The World Islamic Sciences & Education University students. The study applied the survey and descriptive Approach. The population of the study represents all BA students who enrolled in the first academic semester for the year 2014-2015. The sample of…

Dynamic social networks based on movement

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-08-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure.

PubMed

Schleussner, Carl-Friedrich; Donges, Jonathan F; Engemann, Denis A; Levermann, Anders

2016-08-11

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

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 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.

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

PubMed

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

2016-05-01

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. This systematic literature review examining how social network analytic studies examine adolescent ATOD use behavior is guided by the following research questions: (1) How do studies conceptualize sex and network sex composition? (2) What types of network affiliations are employed to characterize adolescent networks? (3) What is the methodological quality of included studies? After searching several electronic databases (PsycINFO, EBSCO, and Communication Abstract) and applying our inclusion/exclusion criteria, 48 studies were included in the review. Overall, few studies considered sex composition of networks in which adolescents are embedded as a determinant that influences adolescent ATOD use. Although included studies all exhibited high methodological quality, the majority only used friendship networks to characterize adolescent social networks and subsequently failed to capture the influence of other network types, such as romantic networks. School-based prevention programs could be strengthened by (1) selecting and targeting peer leaders based on sex, and (2) leveraging other types of social networks beyond simply friendships. © 2016, American School Health Association.

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.

Smoking Behavior and Friendship Formation: The Importance of Time Heterogeneity in Studying Social Network Dynamics

DTIC Science & Technology

2010-01-01

Smoking Behavior and Friendship Formation: The Importance of Time Heterogeneity in Studying Social Network Dynamics Joshua A. Lospinoso Department of...djsatchell@gmail.com Abstract—This study illustrates the importance of assessing and accounting for time heterogeneity in longitudinal social net- work...analysis. We apply the time heterogeneity model selection procedure of [1] to a dataset collected on social tie formation for university freshman in the

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.

Validity of Social, Moral and Emotional Facets of Self-Description Questionnaire II

ERIC Educational Resources Information Center

Leung, Kim Chau; Marsh, Herbert W.; Yeung, Alexander Seeshing; Abduljabbar, Adel S.

2015-01-01

Studies adopting a construct validity approach can be categorized into within- and between-network studies. Few studies have applied between-network approach and tested the correlations of the social (same-sex relations, opposite-sex relations, parent relations), moral (honesty-trustworthiness), and emotional (emotional stability) facets of the…

Generalized epidemic process on modular networks.

PubMed

Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong

2014-05-01

Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

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.

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.

Social Work Agonistes

ERIC Educational Resources Information Center

Stoesz, David

2008-01-01

Social work should be founded on a powerful network of diverse practitioners applying the social sciences to advance social welfare today. Instead, social work education operates under the guise of identity politics, reserving its highest appointments for the politically correct and members of under-represented groups, with little concern for…

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

Technology acceptance perception for promotion of sustainable consumption.

PubMed

Biswas, Aindrila; Roy, Mousumi

2018-03-01

Economic growth in the past decades has resulted in change in consumption pattern and emergence of tech-savvy generation with unprecedented increase in the usage of social network technology. In this paper, the technology acceptance value gap adapted from the technology acceptance model has been applied as a tool supporting social network technology usage and subsequent promotion of sustainable consumption. The data generated through the use of structured questionnaires have been analyzed using structural equation modeling. The validity of the model and path estimates signifies the robustness of Technology Acceptance value gap in adjudicating the efficiency of social network technology usage in augmentation of sustainable consumption and awareness. The results indicate that subjective norm gap, ease-of-operation gap, and quality of green information gap have the most adversarial impact on social network technology usage. Eventually social networking technology usage has been identified as a significant antecedent of sustainable consumption.

Which Peers Matter: How Social Ties Affect Peer-Group Effects

ERIC Educational Resources Information Center

Poldin, Oleg; Valeeva, Diliara; Yudkevich, Maria

2016-01-01

We study how the achievements of university students are influenced by the characteristics and achievements of peers in individuals' social networks. Defining peer group in terms of friendship and study partner ties enables us to apply a network regression model and thereby disentangle the influence of peers' performance from that of peers'…

Lifespan Differences in the Social Networks of Prison Inmates

ERIC Educational Resources Information Center

Bond, Gary D.; Thompson, Laura A.; Malloy, Daniel M.

2005-01-01

Socioemotional Selectivity Theory (SST) (Carstensen, 1992, 1993) accounts for lifespan changes in human social networks and for the motivations which underlie those changes. SST is applied in this research with 256 prison inmates and non-inmates, ages 18-84, from Mississippi, Kansas, and New Mexico. Two research questions sought to identify (a)…

Higher Education Change and Social Networks: A Review of Research

ERIC Educational Resources Information Center

Kezar, Adrianna

2014-01-01

This article reviews literature on the potential for understanding higher education change processes through social network analysis (SNA). In this article, the main tenets of SNA are reviewed and, in conjunction with organizational theory, are applied to higher education change to develop a set of hypotheses that can be tested in future research.

A Learning Content Authoring Approach Based on Semantic Technologies and Social Networking: An Empirical Study

ERIC Educational Resources Information Center

Nesic, Sasa; Gasevic, Dragan; Jazayeri, Mehdi; Landoni, Monica

2011-01-01

Semantic web technologies have been applied to many aspects of learning content authoring including semantic annotation, semantic search, dynamic assembly, and personalization of learning content. At the same time, social networking services have started to play an important role in the authoring process by supporting authors' collaborative…

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

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

PubMed Central

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-01-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking. PMID:27510641

Social networks dynamics revealed by temporal analysis: An example in a non-human primate (Macaca sylvanus) in "La Forêt des Singes".

PubMed

Sosa, Sebastian; Zhang, Peng; Cabanes, Guénaël

2017-06-01

This study applied a temporal social network analysis model to describe three affiliative social networks (allogrooming, sleep in contact, and triadic interaction) in a non-human primate species, Macaca sylvanus. Three main social mechanisms were examined to determine interactional patterns among group members, namely preferential attachment (i.e., highly connected individuals are more likely to form new connections), triadic closure (new connections occur via previous close connections), and homophily (individuals interact preferably with others with similar attributes). Preferential attachment was only observed for triadic interaction network. Triadic closure was significant in allogrooming and triadic interaction networks. Finally, gender homophily was seasonal for allogrooming and sleep in contact networks, and observed in each period for triadic interaction network. These individual-based behaviors are based on individual reactions, and their analysis can shed light on the formation of the affiliative networks determining ultimate coalition networks, and how these networks may evolve over time. A focus on individual behaviors is necessary for a global interactional approach to understanding social behavior rules and strategies. When combined, these social processes could make animal social networks more resilient, thus enabling them to face drastic environmental changes. This is the first study to pinpoint some of the processes underlying the formation of a social structure in a non-human primate species, and identify common mechanisms with humans. The approach used in this study provides an ideal tool for further research seeking to answer long-standing questions about social network dynamics. © 2017 Wiley Periodicals, Inc.

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.

[Social support network and health of elderly individuals with chronic pneumopathies].

PubMed

Mesquita, Rafael Barreto de; Morano, Maria Tereza Aguiar Pessoa; Landim, Fátima Luna Pinheiro; Collares, Patrícia Moreira Costa; Pinto, Juliana Maria de Sousa

2012-05-01

This study sought to analyze characteristics of the social support network of the elderly with chronic pneumopathies, establishing links with health maintenance/rehabilitation. The assumptions of Social Network Analysis (SNA) methodology were used, addressing the social support concept. A questionnaire and semi-structured interviews, both applied to 16 elderly people attended by a public hospital in Fortaleza-CE, were used for data collection. Quantitative data were processed using the UCINET 6.123, NetDraw 2.38 and Microsoft Excel software programs. In the qualitative analysis, the body of material was subjected to interpretations based on relevant and current theoretical references. Each informant brought an average of 10.37 individuals into the network. Among the 3 types of social support, there was a predominance of informational support given by health professionals. The importance of reciprocity in providing/receiving social support was also noted, as well as the participation of health professionals and the family functioning as social support. The conclusion reached was that the network of the elderly with pneumopathies is not cohesive, being restricted to the personal network of each individual, and that even so, the informants recognize and are satisfied with the social support it provides.

Brand communities embedded in social networks.

PubMed

Zaglia, Melanie E

2013-02-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers' interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes.

Impact of Social Punishment on Cooperative Behavior in Complex Networks

NASA Astrophysics Data System (ADS)

Wang, Zhen; Xia, Cheng-Yi; Meloni, Sandro; Zhou, Chang-Song; Moreno, Yamir

2013-10-01

Social punishment is a mechanism by which cooperative individuals spend part of their resources to penalize defectors. In this paper, we study the evolution of cooperation in 2-person evolutionary games on networks when a mechanism for social punishment is introduced. Specifically, we introduce a new kind of role, punisher, which is aimed at reducing the earnings of defectors by applying to them a social fee. Results from numerical simulations show that different equilibria allowing the three strategies to coexist are possible as well as that social punishment further enhance the robustness of cooperation. Our results are confirmed for different network topologies and two evolutionary games. In addition, we analyze the microscopic mechanisms that give rise to the observed macroscopic behaviors in both homogeneous and heterogeneous networks. Our conclusions might provide additional insights for understanding the roots of cooperation in social systems.

Spreading in online social networks: the role of social reinforcement.

PubMed

Zheng, Muhua; Lü, Linyuan; Zhao, Ming

2013-07-01

Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

Learners' Attitudes toward Foreign Language Practice on Social Network Sites

ERIC Educational Resources Information Center

Villafuerte, Jhonny; Romero, Asier

2017-01-01

This work aims to study learners' attitudes towards practicing English Language on Social Networks Sites (SNS). The sample involved 110 students from the University Laica Eloy Alfaro de Manabi in Ecuador, and the University of the Basque Country in Spain. The instrument applied was a Likert scale questionnaire designed Ad hoc by the researchers,…

In-House Communication Support System Based on the Information Propagation Model Utilizes Social Network

NASA Astrophysics Data System (ADS)

Takeuchi, Susumu; Teranishi, Yuuichi; Harumoto, Kaname; Shimojo, Shinji

Almost all companies are now utilizing computer networks to support speedier and more effective in-house information-sharing and communication. However, existing systems are designed to support communications only within the same department. Therefore, in our research, we propose an in-house communication support system which is based on the “Information Propagation Model (IPM).” The IPM is proposed to realize word-of-mouth communication in a social network, and to support information-sharing on the network. By applying the system in a real company, we found that information could be exchanged between different and unrelated departments, and such exchanges of information could help to build new relationships between the users who are apart on the social network.

Finding Influential Spreaders from Human Activity beyond Network Location.

PubMed

Min, Byungjoon; Liljeros, Fredrik; Makse, Hernán A

2015-01-01

Most centralities proposed for identifying influential spreaders on social networks to either spread a message or to stop an epidemic require the full topological information of the network on which spreading occurs. In practice, however, collecting all connections between agents in social networks can be hardly achieved. As a result, such metrics could be difficult to apply to real social networks. Consequently, a new approach for identifying influential people without the explicit network information is demanded in order to provide an efficient immunization or spreading strategy, in a practical sense. In this study, we seek a possible way for finding influential spreaders by using the social mechanisms of how social connections are formed in real networks. We find that a reliable immunization scheme can be achieved by asking people how they interact with each other. From these surveys we find that the probabilistic tendency to connect to a hub has the strongest predictive power for influential spreaders among tested social mechanisms. Our observation also suggests that people who connect different communities is more likely to be an influential spreader when a network has a strong modular structure. Our finding implies that not only the effect of network location but also the behavior of individuals is important to design optimal immunization or spreading schemes.

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.

Support networks and people with physical disabilities: social inclusion and access to health services.

PubMed

Holanda, Cristina Marques de Almeida; De Andrade, Fabienne Louise Juvêncio Paes; Bezerra, Maria Aparecida; Nascimento, João Paulo da Silva; Neves, Robson da Fonseca; Alves, Simone Bezerra; Ribeiro, Kátia Suely Queiroz Silva

2015-01-01

This study seeks to identify the formation of social support networks of people with physical disabilities, and how these networks can help facilitate access to health services and promote social inclusion. It is a cross-sectional study, with data collected via a form applied to physically disabled persons over eighteen years of age registered with the Family Health Teams of the municipal district of João Pessoa in the state of Paraíba. It was observed that the support networks of these individuals predominantly consist of family members (parents, siblings, children, spouses) and people outside the family (friends and neighbors). However, 50% of the interviewees declared that they could not count on any support from outside the family. It was observed that the support network contributes to access to the services and participation in social groups. However, reduced social inclusion was detected, due to locomotion difficulties, this being the main barrier to social interaction. Among those individuals who began to interact in society, the part played by social support was fundamental.

Social Networks and Welfare in Future Animal Management

PubMed Central

Koene, Paul; Ipema, Bert

2014-01-01

Simple Summary Living in a stable social environment is important to animals. Animal species have developed social behaviors and rules of approach and avoidance of conspecifics in order to co-exist. Animal species are kept or domesticated without explicit regard for their inherent social behavior and rules. Examples of social structures are provided for four species kept and managed by humans. This information is important for the welfare management of these species. In the near future, automatic measurement of social structures will provide a tool for daily welfare management together with nearest neighbor information. Abstract It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future. PMID:26479886

The social network index and its relation to later-life depression among the elderly aged ≥80 years in Northern Thailand.

PubMed

Aung, Myo Nyein; Moolphate, Saiyud; Aung, Thin Nyein Nyein; Katonyoo, Chitima; Khamchai, Songyos; Wannakrairot, Pongsak

2016-01-01

Having a diverse social network is considered to be beneficial to a person's well-being. The significance, however, of social network diversity in the geriatric assessment of people aged ≥80 years has not been adequately investigated within the Southeast Asian context. This study explored the social networks belonging to the elderly aged ≥80 years and assessed the relation of social network and geriatric depression. This study was a community-based cross-sectional survey conducted in Chiang Mai Province, Northern Thailand. A representative sample of 435 community residents, aged ≥80 years, were included in a multistage sample. The participants' social network diversity was assessed by applying Cohen's social network index (SNI). The geriatric depression scale and activities of daily living measures were carried out during home visits. Descriptive analyses revealed the distribution of SNI, while the relationship between the SNI and the geriatric depression scale was examined by ordinal logistic regression models controlling possible covariants such as age, sex, and educational attainment. The median age of the sample was 83 years, with females comprising of 54.94% of the sample. The participants' children, their neighbors, and members of Buddhist temples were reported as the most frequent contacts of the study participants. Among the 435 participants, 25% were at risk of social isolation due to having a "limited" social network group (SNI 0-3), whereas 37% had a "medium" social network (SNI 4-5), and 38% had a "diverse" social network (SNI ≥6). The SNI was not different among the two sexes. Activities of daily living scores in the diverse social network group were significantly higher than those in the limited social network group. Multivariate ordinal logistic regression analysis models revealed a significant negative association between social network diversity and geriatric depression. Regular and frequent contact with various social contacts may safeguard common geriatric depression among persons aged ≥80 years. As a result, screening those at risk of social isolation is recommended to be integrated into routine primary health care-based geriatric assessment and intervention programs.

Individual social capital, neighbourhood deprivation, and self-rated health in England.

PubMed

Verhaeghe, Pieter-Paul; Tampubolon, Gindo

2012-07-01

Individual social capital is increasingly considered to be an important determinant of an individual's health. This study examines the extent to which individual social capital is associated with self-rated health and the extent to which individual social capital mediates t.he relationship between neighbourhood deprivation and self-rated health in an English sample. Individual social capital was conceptualized and operationalized in both the social cohesion- and network resource tradition, using measures of generalized trust, social participation and social network resources. Network resources were measured with the position generator. Multilevel analyses were applied to wave 2 and 3 of the Taking Part Surveys of England, which consist of face-to-face interviews among the adult population in England (N(i) = 25,366 respondents, N(j) = 12,388 neighbourhoods). The results indicate that generalized trust, participation with friends and relatives and having network members from the salariat class are positively associated with self-rated health. Having network members from the working class is, however, negatively related to self-rated health. Moreover, these social capital elements are partly mediating the negative relationship between neighbourhood deprivation and self-rated health. Copyright © 2012 Elsevier Ltd. All rights reserved.

State of the (net)work address Developing criteria for applying social networking to the work environment.

PubMed

Valdez, André Calero; Schaar, Anne Kathrin; Ziefle, Martina

2012-01-01

In an increasingly faster paced innovative world, maintaining the ability to innovate in spite of an aging work force will become every company's strongest leverage for success. Tapping the latent knowledge resources and creativity of overlooked employees and persisting crucial information for business conduct are promising results for social networking sites (SNS) in a working context. Usability and usefulness are exponential factors in creating a successful SNS. In order to make a SNS usable for a heterogeneous user group, analyses of user diversity in regard to social media need to be done. Furthermore differences in communication medium and frequency in regard to age, content, hierarchy position, departmental thresholds and company size need to be analyzed. For analysis purposes both qualitative and quantitative research methods were applied. Strong effects of age and communication content were found in survey with 194 participants.

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.

Social networks as embedded complex adaptive systems.

PubMed

Benham-Hutchins, Marge; Clancy, Thomas R

2010-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

PubMed Central

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

A Web Service-based framework model for people-centric sensing applications applied to social networking.

PubMed

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

Social Networks as the Context for Understanding Employment Services Utilization among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Rice, Eric

2014-01-01

Little is known about the factors associated with use of employment services among homeless youth. Social network characteristics have been known to be influential in motivating people's decision to seek services. Traditional theoretical frameworks applied to studies of service use emphasize individual factors over social contexts and interactions. Using key social network, social capital, and social influence theories, this paper developed an integrated theoretical framework that could capture the social network processes that act as barriers or facilitators of use of employment services by homeless youth, and understand empirically, the salience of each of these constructs in influencing the use of employment services among homeless youth. We used the “Event based-approach” strategy to recruit a sample of 136 homeless youth at one drop-in agency serving homeless youth in Los Angeles, California in 2008. The participants were queried regarding their individual and network characteristics. Data were entered into NetDraw 2.090 and the spring embedder routine was used to generate the network visualizations. Logistic regression was used to assess the influence of the network characteristics on use of employment services. The study findings suggest that social capital is more significant in understanding why homeless youth use employment services, relative to network structure and network influence. In particular, bonding and bridging social capital were found to have differential effects on use of employment services among this population. The results from this study provide specific directions for interventions aimed to increase use of employment services among homeless youth. PMID:24780279

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 networks as the context for understanding employment services utilization among homeless youth.

PubMed

Barman-Adhikari, Anamika; Rice, Eric

2014-08-01

Little is known about the factors associated with use of employment services among homeless youth. Social network characteristics have been known to be influential in motivating people's decision to seek services. Traditional theoretical frameworks applied to studies of service use emphasize individual factors over social contexts and interactions. Using key social network, social capital, and social influence theories, this paper developed an integrated theoretical framework that capture the social network processes that act as barriers or facilitators of use of employment services by homeless youth, and understand empirically, the salience of each of these constructs in influencing the use of employment services among homeless youth. We used the "Event based-approach" strategy to recruit a sample of 136 homeless youth at one drop-in agency serving homeless youth in Los Angeles, California in 2008. The participants were queried regarding their individual and network characteristics. Data were entered into NetDraw 2.090 and the spring embedder routine was used to generate the network visualizations. Logistic regression was used to assess the influence of the network characteristics on use of employment services. The study findings suggest that social capital is more significant in understanding why homeless youth use employment services, relative to network structure and network influence. In particular, bonding and bridging social capital were found to have differential effects on use of employment services among this population. The results from this study provide specific directions for interventions aimed to increase use of employment services among homeless youth. Copyright © 2014 Elsevier Ltd. All rights reserved.

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 pathways to health: On the mediating role of the social network in the relation between socio-economic position and health.

PubMed

Aartsen, Marja; Veenstra, Marijke; Hansen, Thomas

2017-12-01

Good health is one of the key qualities of life, but opportunities to be and remain healthy are unequally distributed across socio-economic groups. The beneficial health effects of the social network are well known. However, research on the social network as potential mediator in the pathway from socio-economic position (SEP) to health is scarce, while there are good reasons to expect a socio-economical patterning of networks. We aim to contribute to our understanding of socio-economic inequalities in health by examining the mediating role of structural and functional characteristics of the social network in the SEP-health relationship. Data were from the second wave of the Norwegian study on the life course, aging and generation study (NorLAG) and comprised 4534 men and 4690 women aged between 40 and 81. We applied multiple mediation models to evaluate the relative importance of each network characteristic, and multiple group analysis to examine differences between middle-aged and older men and women. Our results indicated a clear socio-economical patterning of the social network for men and women. People with higher SEP had social networks that better protect against loneliness, which in turn lead to better health outcomes. The explained variance in health in older people by the social network and SEP was only half of the explained variance observed in middle-aged people, suggesting that other factors than SEP were more important for health when people age. We conclude that it is the function of the network, rather than the structure, that counts for health.

Social network models predict movement and connectivity in ecological landscapes

USGS Publications Warehouse

Fletcher, R.J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, W.M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Information flow through threespine stickleback networks without social transmission

PubMed Central

Atton, N.; Hoppitt, W.; Webster, M. M.; Galef, B. G.; Laland, K. N.

2012-01-01

Social networks can result in directed social transmission of learned information, thus influencing how innovations spread through populations. Here we presented shoals of threespine sticklebacks (Gasterosteous aculeatus) with two identical foraging tasks and applied network-based diffusion analysis (NBDA) to determine whether the order in which individuals in a social group contacted and solved the tasks was affected by the group's network structure. We found strong evidence for a social effect on discovery of the foraging tasks with individuals tending to discover a task sooner when others in their group had previously done so, and with the spread of discovery of the foraging tasks influenced by groups' social networks. However, the same patterns of association did not reliably predict spread of solution to the tasks, suggesting that social interactions affected the time at which the tasks were discovered, but not the latency to its solution following discovery. The present analysis, one of the first applications of NBDA to a natural animal system, illustrates how NBDA can lead to insight into the mechanisms supporting behaviour acquisition that more conventional statistical approaches might miss. Importantly, we provide the first compelling evidence that the spread of novel behaviours can result from social learning in the absence of social transmission, a phenomenon that we refer to as an untransmitted social effect on learning. PMID:22896644

Quantifiable and objective approach to organizational performance enhancement.

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

Scholand, Andrew Joseph; Tausczik, Yla R.

This report describes a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to identify socially situated relationships between individuals which, though subtle, are highly influential. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships aremore » latent or unrecognized. This report outlines the philosophical antecedents of SLNA, the mechanics of preprocessing, processing, and post-processing stages, and some example results obtained by applying this approach to a 15-month corporate discussion archive.« less

Infectious disease transmission and contact networks in wildlife and livestock.

PubMed

Craft, Meggan E

2015-05-26

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Infectious disease transmission and contact networks in wildlife and livestock

PubMed Central

Craft, Meggan E.

2015-01-01

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools. PMID:25870393

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.

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.

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

Using Social Network Analysis to Investigate Positive EOL Communication.

PubMed

Xu, Jiayun; Yang, Rumei; Wilson, Andrew; Reblin, Maija; Clayton, Margaret F; Ellington, Lee

2018-04-30

End of life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider, will improve clinical understanding of EOL communication. To introduce the use of social network analysis to EOL communication data, and to provide an example of applying social network analysis to home hospice interactions. We provide a description of social network analysis using social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e. magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver gender and across time were also examined. Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined towards day of death, but increased on day of actual patient death. There was variation in reciprocity by the type of positive emotion expressed. Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision-making and health care teamwork. Copyright © 2018. Published by Elsevier Inc.

Social networks and treatment adherence among Latino offenders with mental illness.

PubMed

Eno Louden, Jennifer; Manchak, Sarah M

2018-02-01

Mental health treatment adherence is often required for offenders with mental illness supervised on probation and parole. However, research on offenders with mental illness has largely overlooked cultural and ethnic responsivity factors that may affect adherence to treatment. Latinos are a quickly growing subgroup of offenders whose social networks differ in meaningful ways from European Americans' (e.g., size, composition, centrality of family). Social networks are known to relate to both clinical and criminal justice outcomes for offenders with mental illness, and there are features of nonoffender Latinos' social networks that suggest that findings distilled from work with non-Latino offenders may not apply to them. The present study examined the social networks of 86 Latino probationers with serious mental illness to (a) describe the size and composition of these networks and (b) to determine which factors of social networks are related to treatment adherence. The authors found that Latino offenders' social networks are small (∼6 individuals), consisting primarily of family and professionals such as treatment providers and probation officers. Supportive relationships with nonprofessionals and treatment providers was related to lower likelihood of missing treatment appointments, whereas social control and pressure from family and friends to attend treatment was not related to treatment adherence. Findings are discussed within the context of improved practices for community corrections and mental health agencies in working with Latino offenders with mental illness. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

PubMed

Masías, Víctor Hugo; Valle, Mauricio; Morselli, Carlo; Crespo, Fernando; Vargas, Augusto; Laengle, Sigifredo

2016-01-01

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.

Social networking profiles and professionalism issues in residency applicants: an original study-cohort study.

PubMed

Ponce, Brent A; Determann, Jason R; Boohaker, Hikel A; Sheppard, Evan; McGwin, Gerald; Theiss, Steven

2013-01-01

To determine the frequency of social networking, the degree of information publicly disclosed, and whether unprofessional content was identified in applicants from the 2010 Residency Match. Medical professionalism is an essential competency for physicians to learn, and information found on social networking sites may be hazardous to the doctor-patient relationship and an institution's public perception. No study has analyzed the social network content of applicants applying for residency. Online review of social networking Facebook profiles of graduating medical students applying for a residency in orthopedic surgery. Evidence of unprofessional content was based upon Accreditation Council for Graduate Medical Education guidelines. Additional recorded applicant data included as follows: age, United States Medical Licensing Examination part I score, and residency composite score. Relationship between professionalism score and recorded data points was evaluated using an analysis of variance. Nearly half of all applicants, 46% (200/431), had a Facebook profile. The majority of profiles (85%) did not restrict online access to their profile. Unprofessional content was identified in 16% of resident applicant profiles. Variables associated with lower professionalism scores included unmarried relationship status and lower residency composite scores. It is critical for healthcare professionals to recognize both the benefits and risks present with electronic communication and to vigorously protect the content of material allowed to be publically accessed through the Internet. Copyright © 2013 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Infering and Calibrating Triadic Closure in a Dynamic Network

NASA Astrophysics Data System (ADS)

Mantzaris, Alexander V.; Higham, Desmond J.

In the social sciences, the hypothesis of triadic closure contends that new links in a social contact network arise preferentially between those who currently share neighbours. Here, in a proof-of-principle study, we show how to calibrate a recently proposed evolving network model to time-dependent connectivity data. The probabilistic edge birth rate in the model contains a triadic closure term, so we are also able to assess statistically the evidence for this effect. The approach is shown to work on data generated synthetically from the model. We then apply this methodology to some real, large-scale data that records the build up of connections in a business-related social networking site, and find evidence for triadic closure.

Animal Social Network Theory Can Help Wildlife Conservation.

PubMed

Snijders, Lysanne; Blumstein, Daniel T; Stanley, Christina R; Franks, Daniel W

2017-08-01

Many animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting, and potentially manipulating population dynamics. Various network statistics can correlate with individual fitness components and key population-level processes, yet the logical role and formal application of animal social network theory for conservation and management have not been well articulated. We outline how understanding of direct and indirect relationships between animals can be profitably applied by wildlife managers and conservationists. By doing so, we aim to stimulate the development and implementation of practical tools for wildlife conservation and management and to inspire novel behavioral research in this field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Age-friendly cities of Europe.

PubMed

Green, Geoff

2013-10-01

This article summarizes how members of the European Healthy Cities Network have applied the 'healthy ageing' approach developed by the World Health Organization in their influential report on Active Ageing. Network Cities can be regarded as social laboratories testing how municipal strategies and interventions can help maintain the health and independence which characterise older people of the third age. Evidence of the orientation and scope of city interventions is derived from a series of Healthy Ageing Sub-Network symposia but principally from responses by 59 member cities to a General Evaluation Questionnaire covering Phase IV (2003-2008) of the Network. Cities elaborated four aspects of healthy ageing (a) raising awareness of older people as a resource to society (b) personal and community empowerment (c) access to the full range of services, and (d) supportive physical and social environments. In conclusion, the key message is that by applying healthy ageing strategies to programmes and plans in many sectors, city governments can potentially compress the fourth age of 'decrepitude and dependence' and expand the third age of 'achievement and independence' with more older people contributing to the social and economic life of a city.

A Model of Biological Attacks on a Realistic Population

NASA Astrophysics Data System (ADS)

Carley, Kathleen M.; Fridsma, Douglas; Casman, Elizabeth; Altman, Neal; Chen, Li-Chiou; Kaminsky, Boris; Nave, Demian; Yahja, Alex

The capability to assess the impacts of large-scale biological attacks and the efficacy of containment policies is critical and requires knowledge-intensive reasoning about social response and disease transmission within a complex social system. There is a close linkage among social networks, transportation networks, disease spread, and early detection. Spatial dimensions related to public gathering places such as hospitals, nursing homes, and restaurants, can play a major role in epidemics [Klovdahl et. al. 2001]. Like natural epidemics, bioterrorist attacks unfold within spatially defined, complex social systems, and the societal and networked response can have profound effects on their outcome. This paper focuses on bioterrorist attacks, but the model has been applied to emergent and familiar diseases as well.

[Social network, social support and feeding habits of infants in their fourth month of life].

PubMed

Morgado, Caroline Maria da Costa; Werneck, Guilherme Loureiro; Hasselmann, Maria Helena

2013-02-01

The scope of this study was to investigate the association between the social network, social support and the feeding habits of infants in their fourth month of life. A cross-sectional study was conducted among 294 children selected at 4 Primary Health Care Units in Rio de Janeiro/ Brazil. A 24-hour dietary recall was applied to the mothers to evaluate the feeding habits. Questions related to the number of people upon whom the woman can rely were asked as well as their participation in social activities to measure the social network. The scale in the Medical Outcomes Study was used to measure social support. The analysis was based on multinomial logistic regression models. Most of the infants (84%) received breast milk, but only 16% were exclusively breastfed. Children whose mothers had a small number of relatives to rely on and with low social support were more likely to be bottle-fed rather than exclusively breastfed. The need to integrate members of the social network of the woman during pre-natal care, birth and the after birth period should be encouraged, in such a way that social support can serve the mother's requirements, contributing to exclusive breastfeeding.

Agricultural trade networks and patterns of economic development.

PubMed

Shutters, Shade T; Muneepeerakul, Rachata

2012-01-01

International trade networks are manifestations of a complex combination of diverse underlying factors, both natural and social. Here we apply social network analytics to the international trade network of agricultural products to better understand the nature of this network and its relation to patterns of international development. Using a network tool known as triadic analysis we develop triad significance profiles for a series of agricultural commodities traded among countries. Results reveal a novel network "superfamily" combining properties of biological information processing networks and human social networks. To better understand this unique network signature, we examine in more detail the degree and triadic distributions within the trade network by country and commodity. Our results show that countries fall into two very distinct classes based on their triadic frequencies. Roughly 165 countries fall into one class while 18, all highly isolated with respect to international agricultural trade, fall into the other. Only Vietnam stands out as a unique case. Finally, we show that as a country becomes less isolated with respect to number of trading partners, the country's triadic signature follows a predictable trajectory that may correspond to a trajectory of development.

Exposure, hazard, and survival analysis of diffusion on social networks.

PubMed

Wu, Jiacheng; Crawford, Forrest W; Kim, David A; Stafford, Derek; Christakis, Nicholas A

2018-04-29

Sociologists, economists, epidemiologists, and others recognize the importance of social networks in the diffusion of ideas and behaviors through human societies. To measure the flow of information on real-world networks, researchers often conduct comprehensive sociometric mapping of social links between individuals and then follow the spread of an "innovation" from reports of adoption or change in behavior over time. The innovation is introduced to a small number of individuals who may also be encouraged to spread it to their network contacts. In conjunction with the known social network, the pattern of adoptions gives researchers insight into the spread of the innovation in the population and factors associated with successful diffusion. Researchers have used widely varying statistical tools to estimate these quantities, and there is disagreement about how to analyze diffusion on fully observed networks. Here, we describe a framework for measuring features of diffusion processes on social networks using the epidemiological concepts of exposure and competing risks. Given a realization of a diffusion process on a fully observed network, we show that classical survival regression models can be adapted to estimate the rate of diffusion, and actor/edge attributes associated with successful transmission or adoption, while accounting for the topology of the social network. We illustrate these tools by applying them to a randomized network intervention trial conducted in Honduras to estimate the rate of adoption of 2 health-related interventions-multivitamins and chlorine bleach for water purification-and determine factors associated with successful social transmission. Copyright © 2018 John Wiley & Sons, Ltd.

Actor-network theory: a tool to support ethical analysis of commercial genetic testing.

PubMed

Williams-Jones, Bryn; Graham, Janice E

2003-12-01

Social, ethical and policy analysis of the issues arising from gene patenting and commercial genetic testing is enhanced by the application of science and technology studies, and Actor-Network Theory (ANT) in particular. We suggest the potential for transferring ANT's flexible nature to an applied heuristic methodology for gathering empirical information and for analysing the complex networks involved in the development of genetic technologies. Three concepts are explored in this paper--actor-networks, translation, and drift--and applied to the case of Myriad Genetics and their commercial BRACAnalysis genetic susceptibility test for hereditary breast cancer. Treating this test as an active participant in socio-technical networks clarifies the extent to which it interacts with, shapes and is shaped by people, other technologies, and institutions. Such an understanding enables more sophisticated and nuanced technology assessment, academic analysis, as well as public debate about the social, ethical and policy implications of the commercialization of new genetic technologies.

Brand communities embedded in social networks☆

PubMed Central

Zaglia, Melanie E.

2013-01-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers’ interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes. PMID:23564989

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

The association between social network factors and mental health at different life stages.

PubMed

Levula, Andrew; Wilson, Andrew; Harré, Michael

2016-07-01

Psychosocial factors are important determinants of an individual's health. This study examines the association between health scores and social network factors on mental health across different life stages. Data were drawn from the Household Income and Labour Dynamics in Australia survey for adolescents (n = 1739), adults (n = 10,309) and seniors (n = 2287). Hierarchical regression modelling was applied to examine effects within and across age groups. All the variables were derived from the self-completion questionnaire. The social network factors were statistically significant predictors of mental health outcomes for all three life stages. For adolescents, the three social network factors were statistically significant with social isolation having the largest impact (β = -.284, p < .001), followed by social connection (β = .084, p < .001) and social trust having a similar effect (β = .073, p < .001). For adults social isolation had the highest impact (β = -.203, p < .001), followed by social connection (β = .110, p < .001) and social trust (β = .087, p < .001).The results for seniors were social isolation (β = -.188, p < .001), social connection (β = .147, p < .001) and social trust (β = .032, p < .05). After adding the social network factors, the models improved significantly with social isolation playing the most significant role across all life stages, whereas the other social network factors played a differentiated role depending upon the life stage. These findings have practical implications in the design of mental health interventions across different life stages.

Process Challenges and Learning-Based Interactions in Stage 2 of Doctoral Education: Implications from Two Applied Social Science Fields

ERIC Educational Resources Information Center

Baker, Vicki L.; Pifer, Meghan J.; Flemion, Blair

2013-01-01

This article reports on an exploratory study that examined the transition to independence in Stage 2 of the doctoral student experience in two applied social science fields. We rely on an interdisciplinary framework that integrates developmental networks and sociocultural perspectives of learning to better understand the connection between the…

Promoting positive psychology using social networking sites: a study of new college entrants on Facebook.

PubMed

Chang, Shu-Man; Lin, Yung-Hsiu; Lin, Chi-Wei; Chang, Her-Kun; Chong, Ping Pete

2014-04-29

This study explores the potential of promoting college students' positive psychological development using popular online social networks. Online social networks have dramatically changed the ways college students manage their social relationships. Social network activities, such as checking Facebook posts dominates students' Internet time and has the potential to assist students' positive development. Positive psychology is a scientific study of how ordinary individuals can apply their strength effectively when facing objective difficulties and how this capability can be cultivated with certain approaches. A positive message delivery approach was designed for a group of new college entrants. A series of positive messages was edited by university counselors and delivered by students to their Facebook social groups. Responses from each posted positive messages were collected and analyzed by researchers. The responses indicated that: (1) relationships of individual engagement and social influence in this study can partially explain the observed student behavior; (2) using class-based social groups can promote a positive atmosphere to enhance strong-tie relationships in both the physical and virtual environments, and (3) promoting student's positive attitudes can substantially impact adolescents' future developments, and many positive attitudes can be cultivated by emotional events and social influence.

Promoting Positive Psychology Using Social Networking Sites: A Study of New College Entrants on Facebook

PubMed Central

Chang, Shu-Man; Lin, Yung-Hsiu; Lin, Chi-Wei; Chang, Her-Kun; Chong, Ping Pete

2014-01-01

This study explores the potential of promoting college students’ positive psychological development using popular online social networks. Online social networks have dramatically changed the ways college students manage their social relationships. Social network activities, such as checking Facebook posts dominates students’ Internet time and has the potential to assist students’ positive development. Positive psychology is a scientific study of how ordinary individuals can apply their strength effectively when facing objective difficulties and how this capability can be cultivated with certain approaches. A positive message delivery approach was designed for a group of new college entrants. A series of positive messages was edited by university counselors and delivered by students to their Facebook social groups. Responses from each posted positive messages were collected and analyzed by researchers. The responses indicated that: (1) relationships of individual engagement and social influence in this study can partially explain the observed student behavior; (2) using class-based social groups can promote a positive atmosphere to enhance strong-tie relationships in both the physical and virtual environments, and (3) promoting student’s positive attitudes can substantially impact adolescents’ future developments, and many positive attitudes can be cultivated by emotional events and social influence. PMID:24785540

Topology Analysis of Social Networks Extracted from Literature

PubMed Central

2015-01-01

In a world where complex networks are an increasingly important part of science, it is interesting to question how the new reading of social realities they provide applies to our cultural background and in particular, popular culture. Are authors of successful novels able to reproduce social networks faithful to the ones found in reality? Is there any common trend connecting an author’s oeuvre, or a genre of fiction? Such an analysis could provide new insight on how we, as a culture, perceive human interactions and consume media. The purpose of the work presented in this paper is to define the signature of a novel’s story based on the topological analysis of its social network of characters. For this purpose, an automated tool was built that analyses the dialogs in novels, identifies characters and computes their relationships in a time-dependent manner in order to assess the network’s evolution over the course of the story. PMID:26039072

[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.

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

Schools, Social Capital and Space

ERIC Educational Resources Information Center

Allan, Julie; Catts, Ralph

2014-01-01

This paper reports on the significance of social capital in relation to education, exploring its relevance to teachers and other professionals as well as among young people. It draws on aspects of five case studies undertaken by the Schools and Social Capital Network, within the Applied Educational Research Scheme in Scotland. These case studies…

Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects

NASA Astrophysics Data System (ADS)

de la Mata, Tamara; Llano, Carlos

2013-07-01

Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.

Social Network Analysis of the Irish Biotech Industry: Implications for Digital Ecosystems

NASA Astrophysics Data System (ADS)

van Egeraat, Chris; Curran, Declan

This paper presents an analysis of the socio-spatial structures of innovation, collaboration and knowledge flow among SMEs in the Irish biotech sector. The study applies social network analysis to determine the structure of networks of company directors and inventors in the biotech sector. In addition, the article discusses the implications of the findings for the role and contours of a biotech digital ecosystem. To distil these lessons, the research team organised a seminar which was attended by representatives of biotech actors and experts.

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases

PubMed Central

2016-01-01

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers–Logistic Regression, Naïve Bayes and Random Forest–with a range of social network measures and the necessary databases to model the verdicts in two real–world cases: the U.S. Watergate Conspiracy of the 1970’s and the now–defunct Canada–based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures. PMID:26824351

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.

Linking Individual and Collective Behavior in Adaptive Social Networks

NASA Astrophysics Data System (ADS)

Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

2016-03-01

Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

How events determine spreading patterns: information transmission via internal and external influences on social networks

NASA Astrophysics Data System (ADS)

Liu, Chuang; Zhan, Xiu-Xiu; Zhang, Zi-Ke; Sun, Gui-Quan; Hui, Pak Ming

2015-11-01

Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo, show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks.

Dental problems and Familismo: social network discussion of oral health issues among adults of Mexican origin living in the Midwest United States.

PubMed

Maupome, G; McConnell, W R; Perry, B L

2016-12-01

To examine the influence of collectivist orientation (often called familismo when applied to the Latino sub-group in the United States) in oral health discussion networks. Through respondent-driven sampling and face-to-face interviews, we identified respondents' (egos) personal social network members (alters). Egos stated whom they talked with about oral health, and how often they discussed dental problems in the preceding 12 months. An urban community of adult Mexican-American immigrants in the Midwest United States. We interviewed 332 egos (90% born in Mexico); egos named an average of 3.9 alters in their networks, 1,299 in total. We applied egocentric network methods to examine the ego, alter, and network variables that characterize health discussion networks. Kin were most often leveraged when dental problems arose; egos relied on individuals whom they perceive to have better knowledge about dental matters. However, reliance on knowledgeable alters decreased among egos with greater behavioral acculturation. This paper developed a network-based conceptualization of familismo. We describe the structure of oral health networks, including kin, fictive kin, peers, and health professionals, and examine how networks and acculturation help shape oral health among these Mexican-Americans. Copyright© 2016 Dennis Barber Ltd

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.

Tele-counseling and social-skill trainings using JGNII optical network and a mirror-interface system

NASA Astrophysics Data System (ADS)

Hashimoto, Sayuri; Hashimoto, Nobuyuki; Onozawa, Akira; Hosoya, Eiichi; Harada, Ikuo; Okunaka, Junzo

2007-09-01

"Tele-presence" communication using JGNII - an exclusive optical-fiber network system - was applied to social-skills training in the form of child-rearing support. This application focuses on internet counseling and social training skills that require interactive verbal and none-verbal communications. The motivation for this application is supporting local communities by constructing tele-presence education and entertainment systems using recently available, inexpensive IP networks. This latest application of tele-presence communication uses mirror-interface system which provides to users in remote locations a shared quasi-space where they can see themselves as if they were in the same room by overlapping video images from remote locations.

Estimating User Influence in Online Social Networks Subject to Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Sun, Yunchuan; Chen, Yingwen; Tian, Zhi

2014-11-01

Online social networks have attracted remarkable attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. Due to the existence of information overload, the research on diffusion dynamics in epidemiology cannot be adopted directly to that in online social networks. In this paper, we consider diffusion dynamics in online social networks subject to information overload, and model the information-processing process of a user by a queue with a batch arrival and a finite buffer. We use the average number of times a message is processed after it is generated by a given user to characterize the user influence, which is then estimated through theoretical analysis for a given network. We validate the accuracy of our estimation by simulations, and apply the results to study the impacts of different factors on the user influence. Among the observations, we find that the impact of network size on the user influence is marginal while the user influence decreases with assortativity due to information overload, which is particularly interesting.

Integrating social networks and human social motives to achieve social influence at scale

PubMed Central

Contractor, Noshir S.; DeChurch, Leslie A.

2014-01-01

The innovations of science often point to ideas and behaviors that must spread and take root in communities to have impact. Ideas, practices, and behaviors need to go from accepted truths on the part of a few scientists to commonplace beliefs and norms in the minds of the many. Moving from scientific discoveries to public good requires social influence. We introduce a structured influence process (SIP) framework to explain how social networks (i.e., the structure of social influence) and human social motives (i.e., the process of social influence wherein one person’s attitudes and behaviors affect another’s) are used collectively to enact social influence within a community. The SIP framework advances the science of scientific communication by positing social influence events that consider both the “who” and the “how” of social influence. This framework synthesizes core ideas from two bodies of research on social influence. The first is network research on social influence structures, which identifies who are the opinion leaders and who among their network of peers shapes their attitudes and behaviors. The second is research on social influence processes in psychology, which explores how human social motives such as the need for accuracy or the need for affiliation stimulate behavior change. We illustrate the practical implications of the SIP framework by applying it to the case of reducing neonatal mortality in India. PMID:25225373

Integrating social networks and human social motives to achieve social influence at scale.

PubMed

Contractor, Noshir S; DeChurch, Leslie A

2014-09-16

The innovations of science often point to ideas and behaviors that must spread and take root in communities to have impact. Ideas, practices, and behaviors need to go from accepted truths on the part of a few scientists to commonplace beliefs and norms in the minds of the many. Moving from scientific discoveries to public good requires social influence. We introduce a structured influence process (SIP) framework to explain how social networks (i.e., the structure of social influence) and human social motives (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's) are used collectively to enact social influence within a community. The SIP framework advances the science of scientific communication by positing social influence events that consider both the "who" and the "how" of social influence. This framework synthesizes core ideas from two bodies of research on social influence. The first is network research on social influence structures, which identifies who are the opinion leaders and who among their network of peers shapes their attitudes and behaviors. The second is research on social influence processes in psychology, which explores how human social motives such as the need for accuracy or the need for affiliation stimulate behavior change. We illustrate the practical implications of the SIP framework by applying it to the case of reducing neonatal mortality in India.

Tweeting badges: user motivations for displaying achievement in publicly networked environments.

PubMed

Kwon, K Hazel; Halavais, Alexander; Havener, Shannon

2015-02-01

Badge systems, a common mechanism for gamification on social media platforms, provide a way for users to present their knowledge or experience to others. This study aims to contribute to the understanding of why social media users publicize their achievements in the form of online badges. Five motivational factors for badge display in public networked environments are distinguished-self-efficacy, social incentives, networked support, passing time, and inattentive sharing-and it is suggested that different badge types are associated with different motivations. System developers are advised to consider these components in their designs, applying the elements most appropriate to the communities they serve. Comparing user motivations associated with badges shared across boundaries provides a better understanding of how online badges relate to the larger social media ecosystem.

Web 2.0 and internet social networking: a new tool for disaster management?--lessons from Taiwan.

PubMed

Huang, Cheng-Min; Chan, Edward; Hyder, Adnan A

2010-10-06

Internet social networking tools and the emerging web 2.0 technologies are providing a new way for web users and health workers in information sharing and knowledge dissemination. Based on the characters of immediate, two-way and large scale of impact, the internet social networking tools have been utilized as a solution in emergency response during disasters. This paper highlights the use of internet social networking in disaster emergency response and public health management of disasters by focusing on a case study of the typhoon Morakot disaster in Taiwan. In the case of typhoon disaster in Taiwan, internet social networking and mobile technology were found to be helpful for community residents, professional emergency rescuers, and government agencies in gathering and disseminating real-time information, regarding volunteer recruitment and relief supplies allocation. We noted that if internet tools are to be integrated in the development of emergency response system, the accessibility, accuracy, validity, feasibility, privacy and the scalability of itself should be carefully considered especially in the effort of applying it in resource poor settings. This paper seeks to promote an internet-based emergency response system by integrating internet social networking and information communication technology into central government disaster management system. Web-based networking provides two-way communication which establishes a reliable and accessible tunnel for proximal and distal users in disaster preparedness and management.

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

Content-Based Covert Group Detection in Social Networks

DTIC Science & Technology

2017-09-06

these features to learn a model that could be applied to the holdout set. This model was then used to test on the remaining posts . Accuracy: 51.4...Content-based Covert Group Detection in Social Networks The views, opinions and/or findings contained in this report are those of the author(s) and...should not contrued as an official Department of the Army position, policy or decision, unless so designated by other documentation. 9. SPONSORING

Effect of social networks and well-being on acute care needs.

PubMed

Sintonen, Sanna; Pehkonen, Aini

2014-01-01

The effect of social surroundings has been noted as an important component of the well-being of elderly people. A strong social network and strong and steady relationships are necessary for coping when illness or functional limitations occur in later life. Vulnerability can affect well-being and functioning particularly when sudden life changes occur. The objective of this study was to analyse how the determinants of social well-being affect individual acute care needs when sudden life changes occur. Empirical evidence was collected using a cross-sectional mail survey in Finland in January 2011 among individuals aged 55-79 years. The age-stratified random sample covered 3000 individuals, and the eventual response rate was 56% (1680). Complete responses were received from 1282 respondents (42.7%). The study focuses on the compactness of social networks, social disability, the stability of social relationships and the fear of loneliness as well as how these factors influence acute care needs. The measurement was based on a latent factor structure, and the key concepts were measured using two ordinal items. The results of the structural model suggest that the need for care is directly affected by social disability and the fear of loneliness. In addition, social disability is a determinant of the fear of loneliness and therefore plays an important role if sudden life changes occur. The compactness of social networks decreases social disability and partly diminishes the fear of loneliness and therefore has an indirect effect on the need for care. The stability of social relationships was influenced by the social networks and disability, but was an insignificant predictor of care needs. To conclude, social networks and well-being can decrease care needs, and supportive actions should be targeted to avoid loneliness and social isolation so that the informal network could be applied as an aspect of care-giving when acute life changes occur. © 2013 John Wiley & Sons Ltd.

The role of social networking web sites in influencing residency decisions.

PubMed

Schweitzer, Justin; Hannan, Alexander; Coren, Joshua

2012-10-01

Social networking Web sites such as Facebook have grown rapidly in popularity. It is unknown how such sites affect the ways in which medical trainees investigate and interact with graduate medical education (GME) programs. To evaluate the use of social networking Web sites as a means for osteopathic medical students, interns, residents, and fellows to interact with GME programs and report the degree to which that interaction impacts a medical trainee's choice of GME program. An anonymous, 10-item electronic survey on social networking Web sites was e-mailed to osteopathic medical student, intern, resident, and fellow members of the American College of Osteopathic Family Physicians. The weighted least squares test and the Fisher exact test were used for data analysis. A total of 9606 surveys were distributed, and 992 (10%) were completed. Nine hundred twenty-eight (93%) of the respondents used social networking Web sites, with the most popular services being Facebook (891 [90%]; P=.03), the Student Doctor Network (278 [28%]), and LinkedIn (89 [9%]; P=.03). Three hundred fifty-three respondents (36%; P=.52) were connected with a professional organization and 673 (68%; P=.73) used social networking Web sites for job searching related to GME programs or postresidency employment. Within the population of 497 third-, fourth-, and fifth-year osteopathic medical students, 136 (27%) reported gleaning information about programs through social networking Web sites (P=.01). Within the total population, 100 of 992 (10%) reported that this information influenced their decisions (P=.07). Of note, 144 (14%) of the total 992 respondents reported that the programs they applied to did not have any presence on social networking Web sites (P=.05). Our results indicate that social networking Web sites have a present and growing influence on how osteopathic medical students, interns, residents, and fellows learn about and select a GME program.

Who "owns" the network: a case study of new media artists' use of high-bandwidth networks

NASA Astrophysics Data System (ADS)

Lesage, F.

The objective of this paper is to briefly give an overview of a research project dealing with the social construction of use of information communication technologies among new media artists interested in online collaboration. It will outline the theoretical and methodological tools applied to the case study of the MARCEL Network.

Agricultural Trade Networks and Patterns of Economic Development

PubMed Central

Shutters, Shade T.; Muneepeerakul, Rachata

2012-01-01

International trade networks are manifestations of a complex combination of diverse underlying factors, both natural and social. Here we apply social network analytics to the international trade network of agricultural products to better understand the nature of this network and its relation to patterns of international development. Using a network tool known as triadic analysis we develop triad significance profiles for a series of agricultural commodities traded among countries. Results reveal a novel network “superfamily” combining properties of biological information processing networks and human social networks. To better understand this unique network signature, we examine in more detail the degree and triadic distributions within the trade network by country and commodity. Our results show that countries fall into two very distinct classes based on their triadic frequencies. Roughly 165 countries fall into one class while 18, all highly isolated with respect to international agricultural trade, fall into the other. Only Vietnam stands out as a unique case. Finally, we show that as a country becomes less isolated with respect to number of trading partners, the country's triadic signature follows a predictable trajectory that may correspond to a trajectory of development. PMID:22768310

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.

Exploring the Social Integration of Sexual Minority Youth Across High School Contexts

PubMed Central

Martin-Storey, Alexa; Cheadle, Jacob E.; Skalamera, Julie; Crosnoe, Robert

2014-01-01

Mental health disparities between sexual minority and other youth have been theorized to result in part from the effects of the stigmatization on social integration. Stochastic actor-based modeling was applied to complete network data from two high schools in the National Longitudinal Study of Adolescent Health (mean age =15 years, n=2,533). Same-sex attracted youth were socially marginalized in a smaller predominantly White school but not in a larger, more racially diverse school. For both schools, homophily was a critical network feature, and could represent social support for and social segregation of such youth. These findings emphasize school context in studying the social lives of sexual minority youth and suggest that youth may be better off socially in larger and more diverse schools. PMID:25689110

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.

42 CFR 121.1 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... PROCUREMENT AND TRANSPLANTATION NETWORK § 121.1 Applicability. (a) The provisions of this part, with the exception of § 121.13, apply to the operation of the Organ Procurement and Transplantation Network (OPTN... Social Security Act, hospitals in which organ transplants are performed and which participate in the...

42 CFR 121.1 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-10-01

... PROCUREMENT AND TRANSPLANTATION NETWORK § 121.1 Applicability. (a) The provisions of this part, with the exception of § 121.13, apply to the operation of the Organ Procurement and Transplantation Network (OPTN... Social Security Act, hospitals in which organ transplants are performed and which participate in the...

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

Bacterial social networks: structure and composition of Myxococcus xanthus outer membrane vesicle chains.

PubMed

Remis, Jonathan P; Wei, Dongguang; Gorur, Amita; Zemla, Marcin; Haraga, Jessica; Allen, Simon; Witkowska, H Ewa; Costerton, J William; Berleman, James E; Auer, Manfred

2014-02-01

The social soil bacterium, Myxococcus xanthus, displays a variety of complex and highly coordinated behaviours, including social motility, predatory rippling and fruiting body formation. Here we show that M. xanthus cells produce a network of outer membrane extensions in the form of outer membrane vesicle chains and membrane tubes that interconnect cells. We observed peritrichous display of vesicles and vesicle chains, and increased abundance in biofilms compared with planktonic cultures. By applying a range of imaging techniques, including three-dimensional (3D) focused ion beam scanning electron microscopy, we determined these structures to range between 30 and 60 nm in width and up to 5 μm in length. Purified vesicle chains consist of typical M. xanthus lipids, fucose, mannose, N-acetylglucosamine and N-acetylgalactoseamine carbohydrates and a small set of cargo protein. The protein content includes CglB and Tgl outer membrane proteins known to be transferable between cells in a contact-dependent manner. Most significantly, the 3D organization of cells within biofilms indicates that cells are connected via an extensive network of membrane extensions that may connect cells at the level of the periplasmic space. Such a network would allow the transfer of membrane proteins and other molecules between cells, and therefore could provide a mechanism for the coordination of social activities. © 2013 Society for Applied Microbiology and John Wiley & Sons Ltd.

Competitive diffusion in online social networks with heterogeneous users

NASA Astrophysics Data System (ADS)

Li, Pei; He, Su; Wang, Hui; Zhang, Xin

2014-06-01

Online social networks have attracted increasing attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. However, most research on diffusion dynamics in epidemiology cannot be applied directly to characterize online social networks, where users are heterogeneous and may act differently according to their standpoints. In this paper, we propose models to characterize the competitive diffusion in online social networks with heterogeneous users. We classify messages into two types (i.e., positive and negative) and users into three types (i.e., positive, negative and neutral). We estimate the positive (negative) influence for a user generating a given type message, which is the number of times that positive (negative) messages are processed (i.e., read) incurred by this action. We then consider the diffusion threshold, above which the corresponding influence will approach infinity, and the effect threshold, above which the unexpected influence of generating a message will exceed the expected one. We verify all these results by simulations, which show the analysis results are perfectly consistent with the simulation results. These results are of importance in understanding the diffusion dynamics in online social networks, and also critical for advertisers in viral marketing where there are fans, haters and neutrals.

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

PubMed

Martínez-Ferrer, Belén; Moreno, David; Musitu, Gonzalo

2018-01-01

The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression -overt vs. relational and reactive vs. instrumental-, and peer victimization -overt physical and verbal, and relational-, taking into account gender and age (in early and mid-adolescence). Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia) (50.4% boys), aged 11 to 16 ( M = 14.07, SD = 1.39). Results showed that girls and 14-16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt-reactive and instrumental-and relational-reactive and instrumental-aggressive behaviors, and self-reported higher levels of overt-physical and verbal-and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11-14) with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline and online domains with regard to maladjustment problems in adolescence.

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

PubMed Central

Martínez-Ferrer, Belén; Moreno, David; Musitu, Gonzalo

2018-01-01

The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression –overt vs. relational and reactive vs. instrumental–, and peer victimization –overt physical and verbal, and relational–, taking into account gender and age (in early and mid-adolescence). Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia) (50.4% boys), aged 11 to 16 (M = 14.07, SD = 1.39). Results showed that girls and 14–16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt—reactive and instrumental—and relational—reactive and instrumental—aggressive behaviors, and self-reported higher levels of overt—physical and verbal—and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11–14) with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline and online domains with regard to maladjustment problems in adolescence. PMID:29896139

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.

Effects of Social Support About Physical Activity on Social Networking Sites: Applying the Theory of Planned Behavior.

PubMed

Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Janz, Kathleen F; Snetselaar, Linda G; Eckler, Petya

2015-01-01

Despite the physical and mental health benefits of leisure-time physical activity (LTPA), only about half of college students participate in the recommended amount of LTPA. While college students are avid users of social network sites (SNSs), whether SNSs would be an effective channel for promoting LTPA through peer social support is unclear. The aim of this study was to explore the effects of social support from students' contacts on SNSs on their intention to participate in LTPA, applying the Theory of Planned Behavior. Participants were recruited through a mass e-mail sent to undergraduate students at a large Midwestern university in fall 2011. In total, 439 surveys were analyzed. Descriptive analyses and analysis for mediating effects were conducted. Social support about LTPA from contacts on SNSs has indirect effect on intention through affective attitude, instrumental attitude, and perceived behavioral control (PBC). The results indicate that social support about LTPA from contacts on SNSs might not be effective to change students' intention unless attitudes and PBC are changed. Future interventions aiming to promote students' intention to participate in LTPA by increasing support from contacts on SNSs should increase affective attitude, instrumental attitude, and PBC at the same time.

Message framing in social networking sites.

PubMed

Kao, Danny Tengti; Chuang, Shih-Chieh; Wang, Sui-Min; Zhang, Lei

2013-10-01

Online social networking sites represent significant new opportunities for Internet advertisers. However, results based on the real world cannot be generalized to all virtual worlds. In this research, the moderating effects of need for cognition (NFC) and knowledge were applied to examine the impact of message framing on attitudes toward social networking sites. A total of 216 undergraduates participated in the study. Results reveal that for social networking sites, while high-NFC individuals form more favorable attitudes toward negatively framed messages than positively framed messages, low-NFC individuals form more favorable attitudes toward positively framed messages than negatively framed messages. In addition, low-knowledge individuals demonstrate more favorable attitudes toward negatively framed messages than positively framed messages; however, the framing effect does not differentially affect the attitudes of high-knowledge individuals. Furthermore, the framing effect does not differentially affect the attitudes of high-NFC individuals with high knowledge. In contrast, low-NFC individuals with low knowledge hold more favorable attitudes toward positively framed messages than negatively framed messages.

[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.

Controllability of social networks and the strategic use of random information.

PubMed

Cremonini, Marco; Casamassima, Francesca

2017-01-01

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network and considers two well-known strategies for influencing social contexts: One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad hoc metrics which are defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills. These findings support our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable.

Improving Interaction in Teacher Training Programmes: The Rise of The Social Dimension in Pre-Service Teacher Education

ERIC Educational Resources Information Center

López Solé, Susana; Civís Zaragoza, Mireia; Díaz-Gibson, Jordi

2018-01-01

This paper studies the social side of pre-service teacher education and draws on social network analysis to explore the relation between the social capital of pre-service teachers and their academic and professional success. An online survey was applied to a sample of 321 students enrolled full time either in Preschool Education or Primary…

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.

Problems associated with the use of social networks--a pilot study.

PubMed

Szczegielniak, Anna; Pałka, Karol; Krysta, Krzysztof

2013-09-01

The definition of addiction is that it is an acquired, strong need to perform a specific activity or continued use of mood alerting substances. Increasing discussion about the development of Internet addiction, which like other addictions, have their roots in depression, impaired assessment esteem and social anxiety shows that it affects all users of the global network, regardless of gender or age. The aim of the study was to assess the impact of social networking on the ongoing behavior of respondents- the first step of a study on the possibility of dependence on social networks. The study was based on an authors questionnaire placed on popular polish websites on February 2013. Questions related to the types and frequency of specific activities undertaken by the private profiles of users. The study involved 221 respondents, 193 questionnaires were filled in completely and correctly, without missing any questions. 83.24% admitted to using social networking sites, 16.76% indicated that they never had their own profile. An overwhelming number of respondents are a member of Facebook (79.17%), specialized portals related to their profession or work were used by only 13.89%, Our-class (6.25%) and Twitter was a primary portal for one person only. Nobody marked a participation in dating services. There is a big difference between the addiction to the Internet and addictions existing within the Internet; the same pattern applies to social networking. There is a need to recognize the "social networking" for a particular activity, irrespective of Facebook, Twitter and Nasza-Klasa, which are commercial products.

Classroom Peer Relationships and Behavioral Engagement in Elementary School: The Role of Social Network Equity

PubMed Central

Cappella, Elise; Kim, Ha Yeon; Neal, Jennifer W.; Jackson, Daisy R.

2014-01-01

Applying social capital and systems theories of social processes, we examine the role of the classroom peer context in the behavioral engagement of low-income students (N = 80) in urban elementary school classrooms (N = 22). Systematic child observations were conducted to assess behavioral engagement among second to fifth graders in the fall and spring of the same school year. Classroom observations, teacher and child questionnaires, and social network data were collected in the fall. Confirming prior research, results from multilevel models indicate that students with more behavioral difficulties or less academic motivation in the fall were less behaviorally engaged in the spring. Extending prior research, classrooms with more equitably distributed and interconnected social ties—social network equity—had more behaviorally engaged students in the spring, especially in classrooms with higher levels of observed organization (i.e., effective management of behavior, time, and attention). Moreover, social network equity attenuated the negative relation between student behavioral difficulties and behavioral engagement, suggesting that students with behavioral difficulties were less disengaged in classrooms with more equitably distributed and interconnected social ties. Findings illuminate the need to consider classroom peer contexts in future research and intervention focused on the behavioral engagement of students in urban elementary schools. PMID:24081319

Does it pay to have a network contact? Social network ties, workplace racial context, and pay outcomes.

PubMed

Kmec, Julie A; Trimble, Lindsey B

2009-06-01

This article investigates how social network use to find work affects pay. Analyses using the Multi-City Study of Urban Inequality consider the extent to which a network contact's influence level affects a job applicant's pay, whether this effect differs for white, black, and Latino contacts, and how workplace racial context moderates this relationship. Three main findings emerge. First, having an influential contact--one with hiring authority--compared to having no contact yields higher pay. Second, white and minority contact influence on pay differs: among minority contacts, being an outsider (i.e., someone not employed by the firm to which the applicant applies) is associated with higher pay, but being an employee of the firm--an insider--is not. Third, regardless of workplace racial context, black and Latino contacts' influence is most beneficial when their race/ethnicity is not known to the hiring agent. We offer a new interpretation of the mixed findings with regard to the relationship between social network use and pay.

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

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.

Estimating the Importance of Terrorists in a Terror Network

NASA Astrophysics Data System (ADS)

Elhajj, Ahmed; Elsheikh, Abdallah; Addam, Omar; Alzohbi, Mohamad; Zarour, Omar; Aksaç, Alper; Öztürk, Orkun; Özyer, Tansel; Ridley, Mick; Alhajj, Reda

While criminals may start their activities at individual level, the same is in general not true for terrorists who are mostly organized in well established networks. The effectiveness of a terror network could be realized by watching many factors, including the volume of activities accomplished by its members, the capabilities of its members to hide, and the ability of the network to grow and to maintain its influence even after the loss of some members, even leaders. Social network analysis, data mining and machine learning techniques could play important role in measuring the effectiveness of a network in general and in particular a terror network in support of the work presented in this chapter. We present a framework that employs clustering, frequent pattern mining and some social network analysis measures to determine the effectiveness of a network. The clustering and frequent pattern mining techniques start with the adjacency matrix of the network. For clustering, we utilize entries in the table by considering each row as an object and each column as a feature. Thus features of a network member are his/her direct neighbors. We maintain the weight of links in case of weighted network links. For frequent pattern mining, we consider each row of the adjacency matrix as a transaction and each column as an item. Further, we map entries into a 0/1 scale such that every entry whose value is greater than zero is assigned the value one; entries keep the value zero otherwise. This way we can apply frequent pattern mining algorithms to determine the most influential members in a network as well as the effect of removing some members or even links between members of a network. We also investigate the effect of adding some links between members. The target is to study how the various members in the network change role as the network evolves. This is measured by applying some social network analysis measures on the network at each stage during the development. We report some interesting results related to two benchmark networks: the first is 9/11 and the second is Madrid bombing.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

PubMed Central

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

Behavior-Specific Social Support for Healthy Behaviors among African American Church Members: Applying Optimal Matching Theory

ERIC Educational Resources Information Center

Thrasher, James F.; Campbell, Marci Kramish; Oates, Veronica

2004-01-01

This study used data from 850 African Americans to test optimal matching theory (OMT). OMT predicts that (1) the most important dimensions of social support depend on the controllability of the behavior and (2) different network members often provide support across health behaviors. Data were gathered on social support source for physical…

Leadership Distribution Culturally? Education/Speech and Language Therapy Social Capital in Schools and Children's Services

ERIC Educational Resources Information Center

Forbes, Joan; McCartney, Elspeth

2012-01-01

This paper is concerned with the operation of professional networks, norms and trust for leadership in interprofessional relationships and cultures and so the analytic of social capital is used. A mapping is outlined of the sub-types, forms and conceptual key terms in social capital theory that is then applied to explore and better understand…

Applying a rateless code in content delivery networks

NASA Astrophysics Data System (ADS)

Suherman; Zarlis, Muhammad; Parulian Sitorus, Sahat; Al-Akaidi, Marwan

2017-09-01

Content delivery network (CDN) allows internet providers to locate their services, to map their coverage into networks without necessarily to own them. CDN is part of the current internet infrastructures, supporting multi server applications especially social media. Various works have been proposed to improve CDN performances. Since accesses on social media servers tend to be short but frequent, providing redundant to the transmitted packets to ensure lost packets not degrade the information integrity may improve service performances. This paper examines the implementation of rateless code in the CDN infrastructure. The NS-2 evaluations show that rateless code is able to reduce packet loss up to 50%.

Consumer-oriented social data fusion: controlled learning in social environments, social advertising, and more

NASA Astrophysics Data System (ADS)

Grewe, L.

2013-05-01

This paper explores the current practices in social data fusion and analysis as it applies to consumer-oriented applications in a slew of areas including business, economics, politics, sciences, medicine, education and more. A categorization of these systems is proposed and contributions to each area are explored preceded by a discussion of some special issues related to social data and networks. From this work, future paths of consumer-based social data analysis research and current outstanding problems are discovered.

Internet gaming disorder, social network disorder and laterality: handedness relates to pathological use of social networks.

PubMed

Bouna-Pyrrou, Polyxeni; Mühle, Christiane; Kornhuber, Johannes; Lenz, Bernd

2015-08-01

The internet age bears new challenges that include health risks. It is agreed that excessive internet use may reach pathological levels. However, the concept of internet addiction lacks specificity and, therefore, warrants studies on its diagnostic and etiologic classification. This study was conducted to characterize the novel DSM-5 criteria for internet gaming disorder and the adapted criteria for the "social network disorder". Based on the established association of handedness and substance use disorders, we also explored whether internet use related to laterality. For this study, 3,287 volunteers participated in the online survey and gave particulars concerning their internet use in general, internet gaming and use of social networks, laterality markers (hand, foot, eye, ear, rotational preference in gymnastics, and head turning asymmetry) and health status. Of the participants, 1.1 % fulfilled the criteria for internet gaming disorder, and 1.8 % fulfilled the criteria for social network disorder. The applied criteria were highly correlated with the time spent on the respective internet activities (p < 4 × 10(-56)). The analyses of comorbidity and working hours support the thresholds of 5/9 criteria and ≥30 h/week spent on the internet for the classification as pathological (p < 5 × 10(-2)). Moreover, we found that left-handedness related to more affirmed criteria and longer times spent on social networks (p ≤ 4 × 10(-2)). The provided criteria proved to be user-friendly, comprehensible and well accepted. The results contribute to a better understanding of pathological internet gaming and social network use and provide evidence that biological markers of substance use disorders are involved in internet addiction.

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.

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.

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.

The Role of Teacher's Initiation in Online Pedagogy

ERIC Educational Resources Information Center

Tsai, Chia-Wen

2012-01-01

Purpose: The author redesigned a course titled "Applied Information Technology: Networking" and applied online collaborative learning (CL) with initiation and self-regulated learning (SRL) to improve students' involvement in this course in an environment that is full of free online games, shopping websites, and social networking…

Modelling the evolution of a bi-partite network Peer referral in interlocking directorates*

PubMed Central

Edling, Christofer

2010-01-01

A central part of relational ties between social actors are constituted by shared affiliations and events. The action of joint participation reinforces personal ties between social actors as well as mutually shared values and norms that in turn perpetuate the patterns of social action that define groups. Therefore the study of bipartite networks is central to social science. Furthermore, the dynamics of these processes suggests that bipartite networks should not be considered static structures but rather be studied over time. In order to model the evolution of bipartite networks empirically we introduce a class of models and a Bayesian inference scheme that extends previous stochastic actor-oriented models for unimodal graphs. Contemporary research on interlocking directorates provides an area of research in which it seems reasonable to apply the model. Specifically, we address the question of how tie formation, i.e. director recruitment, contributes to the structural properties of the interlocking directorate network. For boards of directors on the Stockholm stock exchange we propose that a prolific mechanism in tie formation is that of peer referral. The results indicate that such a mechanism is present, generating multiple interlocks between boards. PMID:24944435

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

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.

Changes in Social Capital and Networks: A Study of Community-Based Environmental Management Through a School-Centered Research Program

NASA Astrophysics Data System (ADS)

Thornton, Teresa; Leahy, Jessica

2012-02-01

Social network analysis (SNA) is a social science research tool that has not been applied to educational programs. This analysis is critical to documenting the changes in social capital and networks that result from community based K-12 educational collaborations. We review SNA and show an application of this technique in a school-centered, community based environmental monitoring research (CBEMR) program. This CBEMR employs K-12 students, state and local government employees, environmental organization representatives, local businesses, colleges, and community volunteers. As citizen scientists and researchers, collaborators create a database of local groundwater quality to use as a baseline for long-term environmental health management and public education. Past studies have evaluated the reliability of data generated by students acting as scientists, but there have been few studies relating to power dynamics, social capital, and resilience in school-centered CBEMR programs. We use qualitative and quantitative data gathered from a science education program conducted in five states in the northeastern United States. SPSS and NVivo data were derived from semi-structured interviews with thirty-nine participants before and after their participation in the CBEMR. Pajek software was used to determine participant centralities and power brokers within networks. Results indicate that there were statistically significant increases in social capital and resilience in social networks after participation in the school-centered CBEMR program leading to an increased community involvement in environmental health management. Limiting factors to the CBMER were based on the educator/administration relationship.

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.

Developing an intelligence analysis process through social network analysis

NASA Astrophysics Data System (ADS)

Waskiewicz, Todd; LaMonica, Peter

2008-04-01

Intelligence analysts are tasked with making sense of enormous amounts of data and gaining an awareness of a situation that can be acted upon. This process can be extremely difficult and time consuming. Trying to differentiate between important pieces of information and extraneous data only complicates the problem. When dealing with data containing entities and relationships, social network analysis (SNA) techniques can be employed to make this job easier. Applying network measures to social network graphs can identify the most significant nodes (entities) and edges (relationships) and help the analyst further focus on key areas of concern. Strange developed a model that identifies high value targets such as centers of gravity and critical vulnerabilities. SNA lends itself to the discovery of these high value targets and the Air Force Research Laboratory (AFRL) has investigated several network measures such as centrality, betweenness, and grouping to identify centers of gravity and critical vulnerabilities. Using these network measures, a process for the intelligence analyst has been developed to aid analysts in identifying points of tactical emphasis. Organizational Risk Analyzer (ORA) and Terrorist Modus Operandi Discovery System (TMODS) are the two applications used to compute the network measures and identify the points to be acted upon. Therefore, the result of leveraging social network analysis techniques and applications will provide the analyst and the intelligence community with more focused and concentrated analysis results allowing them to more easily exploit key attributes of a network, thus saving time, money, and manpower.

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.

Developing algorithm for the critical care physician scheduling

NASA Astrophysics Data System (ADS)

Lee, Hyojun; Pah, Adam; Amaral, Luis; Northwestern Memorial Hospital Collaboration

Understanding the social network has enabled us to quantitatively study social phenomena such as behaviors in adoption and propagation of information. However, most work has been focusing on networks of large heterogeneous communities, and little attention has been paid to how work-relevant information spreads within networks of small and homogeneous groups of highly trained individuals, such as physicians. Within the professionals, the behavior patterns and the transmission of information relevant to the job are dependent not only on the social network between the employees but also on the schedules and teams that work together. In order to systematically investigate the dependence of the spread of ideas and adoption of innovations on a work-environment network, we sought to construct a model for the interaction network of critical care physicians at Northwestern Memorial Hospital (NMH) based on their work schedules. We inferred patterns and hidden rules from past work schedules such as turnover rates. Using the characteristics of the work schedules of the physicians and their turnover rates, we were able to create multi-year synthetic work schedules for a generic intensive care unit. The algorithm for creating shift schedules can be applied to other schedule dependent networks ARO1.

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

PubMed

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

2017-06-22

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. 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. A Web survey link was sent to undergraduate students at one of the Midwestern universities and 439 of them completed the survey. 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. 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. ©Ni Zhang, Shelly Campo, Jingzhen Yang, Petya Eckler, Linda Snetselaar, Kathleen Janz, Emily Leary. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.06.2017.

An examination of network position and childhood relational aggression: integrating resource control and social exchange theories.

PubMed

Neal, Jennifer Watling; Cappella, Elise

2012-01-01

Applying resource control theory and social exchange theory, we examined the social network conditions under which elementary age children were likely to engage in relational aggression. Data on classroom peer networks and peer-nominated behaviors were collected on 671 second- through fourth-grade children in 34 urban, low-income classrooms. Nested regression models with robust cluster standard errors demonstrated that the association between children's number of relationships and their levels of relational aggression was moderated by the number of relationships that their affiliates had. Children with more peer relationships (i.e., higher network centrality) exhibited higher levels of relational aggression, but only when these relationships were with peers who had fewer connections themselves (i.e., poorly connected peers). This finding remained significant even when controlling for common predictors of relational aggression including gender, overt aggression, prosocial behavior, victimization, social preference, and perceived popularity. Results are discussed in terms of their implications for advancing the literature on childhood relational aggression and their practical applications for identifying children at risk for these behaviors. © 2012 Wiley Periodicals, Inc.

CollaborationViz: Interactive Visual Exploration of Biomedical Research Collaboration Networks

PubMed Central

Bian, Jiang; Xie, Mengjun; Hudson, Teresa J.; Eswaran, Hari; Brochhausen, Mathias; Hanna, Josh; Hogan, William R.

2014-01-01

Social network analysis (SNA) helps us understand patterns of interaction between social entities. A number of SNA studies have shed light on the characteristics of research collaboration networks (RCNs). Especially, in the Clinical Translational Science Award (CTSA) community, SNA provides us a set of effective tools to quantitatively assess research collaborations and the impact of CTSA. However, descriptive network statistics are difficult for non-experts to understand. In this article, we present our experiences of building meaningful network visualizations to facilitate a series of visual analysis tasks. The basis of our design is multidimensional, visual aggregation of network dynamics. The resulting visualizations can help uncover hidden structures in the networks, elicit new observations of the network dynamics, compare different investigators and investigator groups, determine critical factors to the network evolution, and help direct further analyses. We applied our visualization techniques to explore the biomedical RCNs at the University of Arkansas for Medical Sciences – a CTSA institution. And, we created CollaborationViz, an open-source visual analytical tool to help network researchers and administration apprehend the network dynamics of research collaborations through interactive visualization. PMID:25405477

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

Effectiveness of closure of public places with time delay in disease control.

PubMed

Wang, Zhenggang; Szeto, Kwok Yip; Leung, Frederick Chi-Ching

2008-08-25

A theoretical basis for the evaluation of the effciency of quarantine measure is developed in a SIR model with time delay. In this model, the effectiveness of the closure of public places such as schools in disease control, modeled as a high degree node in a social network, is evaluated by considering the effect of the time delay in the identification of the infected. In the context of the SIR model, the relation between the number of infectious individuals who are identified with time delay and then quarantined and those who are not identified and continue spreading the virus are investigated numerically. The social network for the simulation is modeled by a scale free network. Closure measures are applied to those infected nodes with high degrees. The effectiveness of the measure can be controlled by the present value of the critical degree K(C): only those nodes with degree higher than K(C) will be quarantined. The cost C(Q) incurred for the closure measure is assumed to be proportional to the total links rendered inactive as a result of the measure, and generally decreases with K(C), while the medical cost C(Q) incurred for virus spreading increases with K(C). The total social cost (C(M) + C(Q)) will have a minimum at a critical K(*), which depends on the ratio of medical cost coeffcient alpha(M) and closure cost coeffcient alpha(Q). Our simulation results demonstrate a mathematical procedure to evaluate the effciency of quarantine measure. Although the numerical work is based on a scale free network, the procedure can be readily generalized and applied to a more realistic social network to determine the proper closure measure in future epidemics.

Evaluation Of Investments In Science, Technology And Innovation: Applying Scientific and Technical Human Capital Framework For Assessment of Doctoral Students In Cooperative Research Centers

NASA Astrophysics Data System (ADS)

Leonchuk, Olena

This dissertation builds on an alternative framework for evaluation of science, technology and innovation (STI) outcomes - the scientific & technical (S&T) human capital which was developed by Bozeman, Dietz and Gaughan (2001). At its core, this framework looks beyond simple economic and publication metrics and instead focuses on scientists' social capital. The premise of the framework is that science does not happen in vacuum and that resources embedded in scientists' social networks are important and enduring outcomes of the scientific process that were not being captured by traditional metrics. This dissertation examines social capital of science and engineering (S&E) graduate students, an underrepresented group of stakeholders in STI evaluations. S&E graduate students are unique for several reasons. In comparison with students in other disciplines, S&E graduate students have a greater proportion of international students; are widely employed by industry in numbers exceeded only by business graduates. And, most importantly, S&E graduates pursue education in fields that contribute the most to the US innovation capacity. This dissertation introduces a multidimensional measure of social capital based on the network theory of social capital proposed by Nan Lin (1999). According to Lin, social capital consists of three components: availability of resources and social embeddedness in one's network and mobilization of these resources. In order to address these elements, the dissertation employs two studies that focus on different components of social capital. Study 1 looks at accessibility of resources in students' social networks and whether students would be likely to mobilize them by using a proxy measure of norms and values about collaborations. The study also addresses the effect of social capital on students' experiences and outcomes, specifically, on their satisfaction and perceived career preparedness. The researcher investigates the mechanisms that explain other students' outcomes by employing data from a matched sample of S&E doctoral students trained at the Industry/University Cooperative Research Centers, I/UCRCs (N=173), and doctoral students from the same universities and disciplines who were trained more traditionally (N=87). Two exploratory path models demonstrate the important role of availability of network resources and proxy for mobilizing them on students' perceived career preparedness and satisfaction with their training. Study 2 is a case study of one I/UCRC's whole social network. The researcher attempts to provide a better understanding of the embeddedness components of students' social capital in their I/UCRC network. The case study has significant limitations in that findings cannot be generalized to the population of I/UCRC students. Nevertheless, findings are interesting for the one I/UCRC. The students scored significantly higher on preparedness when they had higher out-degree centrality, indicator of how much they reach out to other center's personnel. Also, a visual representation of the whole I/UCRC social network could be used to understand better students' embeddedness. Both studies show that social capital is a very hard concept to measure mainly because of its different dimensions. Nevertheless, they also show that social capital is a useful tool for comparing students' outcomes in different STI programs. A focus on students and social capital is one of the ways the S&T human capital model can be applied in evaluation of the STI programs. Such focus provides a considerable contrast to linear STI metrics that focus on long-term outcomes and often exclude students all together. It is important to provide information about the human side of science in its current state including students' graduate training, experiences and social networks. In addition, inclusion of students provides a view into the future - an opportunity to look at science of tomorrow as the same students will be part of the scientific elite networks in the near future.

Factors Affecting Intention to Use in Social Networking Sites: An Empirical Study on Thai Society

NASA Astrophysics Data System (ADS)

Jairak, Rath; Sahakhunchai, Napath; Jairak, Kallaya; Praneetpolgrang, Prasong

This research aims to explore the factors that affect the intention to use in Social Networking Sites (SNS). We apply the theory of Technology Acceptance Model (TAM), intrinsic motivation, and trust properties to develop the theoretical framework for SNS users' intention. The results show that the important factors influencing SNS users' intention for general purpose and collaborative learning are task-oriented, pleasure-oriented, and familiarity-based trust. In marketing usage, dispositional trust and pleasure-oriented are two main factors that reflect intention to use in SNS.

Can Social Network Analysis Help Address the High Rates of Bacterial Sexually Transmitted Infections in Saskatchewan?

PubMed

Trecker, Molly A; Dillon, Jo-Anne R; Lloyd, Kathy; Hennink, Maurice; Jolly, Ann; Waldner, Cheryl

2017-06-01

Saskatchewan has one of the highest rates of gonorrhea among the Canadian provinces-more than double the national rate. In light of these high rates, and the growing threat of untreatable infections, improved understanding of gonorrhea transmission dynamics in the province and evaluation of the current system and tools for disease control are important. We extracted data from a cross-sectional sample of laboratory-confirmed gonorrhea cases between 2003 and 2012 from the notifiable disease files of the Regina Qu'Appelle Health Region. The database was stratified by calendar year, and social network analysis combined with statistical modeling was used to identify associations between measures of connection within the network and the odds of repeat gonorrhea and risk of coinfection with chlamydia at the time of diagnosis. Networks were highly fragmented. Younger age and component size were positively associated with being coinfected with chlamydia. Being coinfected, reporting sex trade involvement, and component size were all positively associated with repeat infection. This is the first study to apply social network analysis to gonorrhea transmission in Saskatchewan and contributes important information about the relationship of network connections to gonorrhea/chlamydia coinfection and repeat gonorrhea. This study also suggests several areas for change of systems-related factors that could greatly increase understanding of social networks and enhance the potential for bacterial sexually transmitted infection control in Saskatchewan.

Semantic networks based on titles of scientific papers

NASA Astrophysics Data System (ADS)

Pereira, H. B. B.; Fadigas, I. S.; Senna, V.; Moret, M. A.

2011-03-01

In this paper we study the topological structure of semantic networks based on titles of papers published in scientific journals. It discusses its properties and presents some reflections on how the use of social and complex network models can contribute to the diffusion of knowledge. The proposed method presented here is applied to scientific journals where the titles of papers are in English or in Portuguese. We show that the topology of studied semantic networks are small-world and scale-free.

An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

PubMed

Shoham, David A; Tong, Liping; Lamberson, Peter J; Auchincloss, Amy H; Zhang, Jun; Dugas, Lara; Kaufman, Jay S; Cooper, Richard S; Luke, Amy

2012-01-01

Recent studies suggest that obesity may be "contagious" between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating "high risk" adolescents in isolation.

WATER SUPPLY PIPE REPLACEMENT CONSIDERING SUSTAINABLE TRANSITION TO POPULATION DECREASED SOCIETY

NASA Astrophysics Data System (ADS)

Hosoi, Yoshihiko; Iwasaki, Yoji; Aklog, Dagnachew; Masuda, Takanori

Social infrastructures are aging and population is decreasing in Japan. The aged social infrastructures should be renewed. At the same time, they are required to be moved into new framework suitable for population decreased societies. Furthermore, they have to continue to supply sufficient services even during transition term that renewal projects are carried out. Authors propose sustainable soft landing management of infrastructures and it is tried to apply to water supply pipe replacement in this study. Methodology to replace aged pipes not only aiming for the new water supply network which suits for population decreased condition but also ensuring supply service and feasibility while the project is carried out was developed. It is applied for a model water supply network and discussions were carried out.

Model, Framework, and Platform of Health Persuasive Social Network

ERIC Educational Resources Information Center

Al Ayubi, Soleh Udin

2013-01-01

Persuasive technology (PT) has the potential to support individuals to perform self-management and social support as a part of health behavior change. This has led a few researchers in the intersection of the areas of health behavior change and software engineering to apply behavior change and persuasion theories to software development practices,…

Effects of active links on epidemic transmission over social networks

NASA Astrophysics Data System (ADS)

Zhu, Guanghu; Chen, Guanrong; Fu, Xinchu

2017-02-01

A new epidemic model with two infection periods is developed to account for the human behavior in social network, where newly infected individuals gradually restrict most of future contacts or are quarantined, causing infectivity change from a degree-dependent form to a constant. The corresponding dynamics are formulated by a set of ordinary differential equations (ODEs) via mean-field approximation. The effects of diverse infectivity on the epidemic dynamics ​are examined, with a behavioral interpretation of the basic reproduction number. Results show that such simple adaptive reactions largely determine the impact of network structure on epidemics. Particularly, a theorem proposed by Lajmanovich and Yorke in 1976 is generalized, so that it can be applied for the analysis of the epidemic models with multi-compartments especially network-coupled ODE systems.

Social aggression and resource conflict across the female life-course in the Bolivian Amazon.

PubMed

Rucas, Stacey L; Gurven, Michael; Winking, Jeffrey; Kaplan, Hillard

2012-01-01

This work explores sources of conflict among forager-horticulturalist women in Amazonian Bolivia, and applies life history theory as a tool for understanding competitive and cooperative social networking behaviors among women. In this study, 121 Tsimane women and girls were interviewed regarding current and past disagreements with others in their community to identify categories of contested resources that instigate interpersonal conflicts, often resulting in incidences of social aggression. Analysis of frequency data on quarrels (N = 334) reveals that women target several diverse categories of resources, with social types appearing as frequently as food and mates. It was also found that the focus of women's competition changes throughout the life-course, consistent with the notion that current vs. future reproduction and quantity-quality trade-offs might have different influences on competition and social conflict over resources within women's social networks across different age groups. © 2012 Wiley Periodicals, Inc.

Rethinking agency and medical adherence technology: applying Actor Network Theory to the case study of Digital Pills.

PubMed

Hurtado-de-Mendoza, Alejandra; Cabling, Mark L; Sheppard, Vanessa B

2015-12-01

Much literature surrounding medical technology and adherence posits that technology is a mechanism for social control. This assumes that the medical establishment can take away patients' agency. Although power relationships and social control can play a key role, medical technology can also serve as an agentive tool to be utilized. We (1) offer the alternative framework of Actor Network Theory to view medical technology, (2) discuss the literature on medication adherence and technology, (3) delve into the ramifications of looking at adherence as a network and (4) use Digital Pills as a case study of dispersed agency. © 2015 John Wiley & Sons Ltd.

Taxonomies of networks from community structure

PubMed Central

Reid, Stephen; Porter, Mason A.; Mucha, Peter J.; Fricker, Mark D.; Jones, Nick S.

2014-01-01

The study of networks has become a substantial interdisciplinary endeavor that encompasses myriad disciplines in the natural, social, and information sciences. Here we introduce a framework for constructing taxonomies of networks based on their structural similarities. These networks can arise from any of numerous sources: they can be empirical or synthetic, they can arise from multiple realizations of a single process (either empirical or synthetic), they can represent entirely different systems in different disciplines, etc. Because mesoscopic properties of networks are hypothesized to be important for network function, we base our comparisons on summaries of network community structures. Although we use a specific method for uncovering network communities, much of the introduced framework is independent of that choice. After introducing the framework, we apply it to construct a taxonomy for 746 networks and demonstrate that our approach usefully identifies similar networks. We also construct taxonomies within individual categories of networks, and we thereby expose nontrivial structure. For example, we create taxonomies for similarity networks constructed from both political voting data and financial data. We also construct network taxonomies to compare the social structures of 100 Facebook networks and the growth structures produced by different types of fungi. PMID:23030977

Taxonomies of networks from community structure

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Fenn, Daniel J.; Reid, Stephen; Porter, Mason A.; Mucha, Peter J.; Fricker, Mark D.; Jones, Nick S.

2012-09-01

The study of networks has become a substantial interdisciplinary endeavor that encompasses myriad disciplines in the natural, social, and information sciences. Here we introduce a framework for constructing taxonomies of networks based on their structural similarities. These networks can arise from any of numerous sources: They can be empirical or synthetic, they can arise from multiple realizations of a single process (either empirical or synthetic), they can represent entirely different systems in different disciplines, etc. Because mesoscopic properties of networks are hypothesized to be important for network function, we base our comparisons on summaries of network community structures. Although we use a specific method for uncovering network communities, much of the introduced framework is independent of that choice. After introducing the framework, we apply it to construct a taxonomy for 746 networks and demonstrate that our approach usefully identifies similar networks. We also construct taxonomies within individual categories of networks, and we thereby expose nontrivial structure. For example, we create taxonomies for similarity networks constructed from both political voting data and financial data. We also construct network taxonomies to compare the social structures of 100 Facebook networks and the growth structures produced by different types of fungi.

[Role of the social support network which influences age of death and physical function of elderly people: study of trends in and outside of Japan and future problems].

PubMed

Kishi, Reiko; Horikawa, Naoko

2004-02-01

Concerning associations between the social support network and physical health of the elderly, longitudinal studies have been conducted using various measurement indexes. The studies indicated that the support network influences on physical function and life expectancy. In this study we compared research papers from Japan and elsewhere that appeared after 1980, from the viewpoint of 1) social support effects, and 2) social network effects, to examine potential problems in the future. The main knowledge obtained was that the receipt of emotional support, wide network size, and participation in social activities reduced the risk of early death and decrease in physical function of elderly people. Sex differences were indicated, and in many cases, the effects were more remarkable in men than women. In addition the positive influence of receiving help from a support network, a major subject of conventional research, the effects of offering help to others and negative findings were also examined. It has been indicated that participation in volunteer groups and offer of support to other people can prevent decrease in physical function or early death. As negative effects, improper instrumental support rather disturbs the mental and physical independence of elderly people. As future issues, it is necessary to focus on both positive/negative and receipt/offer effects of support network, and to clarify how to provide example which best match the life of elderly people by comparing sexes and regions. It is also important to actually apply the knowledge gained from observational studies to prevent the elderly from becoming a condition requiring care, and to develop intervention studies which can increase the social contacts of elderly people at the same time as conducting health education and medical treatment.

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

NASA Astrophysics Data System (ADS)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

NASA Astrophysics Data System (ADS)

Wu, Yu'E.; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

PubMed Central

Wu, Yu’e; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

2017-01-01

Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world. PMID:28112276

Coarse cluster enhancing collaborative recommendation for social network systems

NASA Astrophysics Data System (ADS)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Social–ecological network analysis of scale mismatches in estuary watershed restoration

PubMed Central

Sayles, Jesse S.

2017-01-01

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. PMID:28223529

Social Sensor Analytics: Making Sense of Network Models in Social Media

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

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013more » and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.« less

Inverse targeting —An effective immunization strategy

NASA Astrophysics Data System (ADS)

Schneider, C. M.; Mihaljev, T.; Herrmann, H. J.

2012-05-01

We propose a new method to immunize populations or computer networks against epidemics which is more efficient than any continuous immunization method considered before. The novelty of our method resides in the way of determining the immunization targets. First we identify those individuals or computers that contribute the least to the disease spreading measured through their contribution to the size of the largest connected cluster in the social or a computer network. The immunization process follows the list of identified individuals or computers in inverse order, immunizing first those which are most relevant for the epidemic spreading. We have applied our immunization strategy to several model networks and two real networks, the Internet and the collaboration network of high-energy physicists. We find that our new immunization strategy is in the case of model networks up to 14%, and for real networks up to 33% more efficient than immunizing dynamically the most connected nodes in a network. Our strategy is also numerically efficient and can therefore be applied to large systems.

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

Using social networking to understand social networks: analysis of a mobile phone closed user group used by a Ghanaian health team.

PubMed

Kaonga, Nadi Nina; Labrique, Alain; Mechael, Patricia; Akosah, Eric; Ohemeng-Dapaah, Seth; Sakyi Baah, Joseph; Kodie, Richmond; Kanter, Andrew S; Levine, Orin

2013-04-03

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. 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. 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. 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). 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.

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.

Advocacy Communication and Social Identity: An Exploration of Social Media Outreach.

PubMed

Ciszek, Erica L

2017-01-01

Increasingly, advocacy organizations employ social networking sites as inexpensive and often effective ways to disseminate outreach messages. For groups working to reach lesbian, gay, bisexual, transgender, and queer (LGBTQ) youth, social media provide key platforms for connecting with target audiences. Although these young people increasingly utilize social media, little is known about how digital advocacy campaigns influence their sexual identity formation. This article applies concepts of social identity to examine how LGBTQ youth understand advocacy campaigns, how they perceive LGBTQ as a social category presented in campaigns, and what values they assign to LGBTQ group membership.

20 CFR 411.310 - How does an entity other than a State VR agency apply to be an EN and who will determine whether...

Code of Federal Regulations, 2013 CFR

2013-04-01

....310 Employees' Benefits SOCIAL SECURITY ADMINISTRATION THE TICKET TO WORK AND SELF-SUFFICIENCY PROGRAM Employment Networks § 411.310 How does an entity other than a State VR agency apply to be an EN and who will...

20 CFR 411.310 - How does an entity other than a State VR agency apply to be an EN and who will determine whether...

Code of Federal Regulations, 2014 CFR

2014-04-01

....310 Employees' Benefits SOCIAL SECURITY ADMINISTRATION THE TICKET TO WORK AND SELF-SUFFICIENCY PROGRAM Employment Networks § 411.310 How does an entity other than a State VR agency apply to be an EN and who will...

20 CFR 411.310 - How does an entity other than a State VR agency apply to be an EN and who will determine whether...

Code of Federal Regulations, 2012 CFR

2012-04-01

....310 Employees' Benefits SOCIAL SECURITY ADMINISTRATION THE TICKET TO WORK AND SELF-SUFFICIENCY PROGRAM Employment Networks § 411.310 How does an entity other than a State VR agency apply to be an EN and who will...

Community-Sourcing a New Marketing Course: Collaboration in Social Media

ERIC Educational Resources Information Center

Schirr, Gary R.

2013-01-01

This paper shows the value of an online personal learning network or community in educational innovation. It shows how theories and best practices from service and product innovation, as well the theories of learning communities, were applied using social media to facilitate the grant proposal and course development processes for a new course in…

AB 540 Community College Students in Southern California: Making Connections and Realizing Dreams

ERIC Educational Resources Information Center

Bleza, Michelle Gonzales

2013-01-01

This study applies the construct of institutional agents and the associated theories of social capital and social networking to understand the influence of institutional agents on Latino undocumented community college students who qualify for tuition equity in California under AB 540. The purpose of this study was to identify the issues these…

Challenges in network science: Applications to infrastructures, climate, social systems and economics

NASA Astrophysics Data System (ADS)

Havlin, S.; Kenett, D. Y.; Ben-Jacob, E.; Bunde, A.; Cohen, R.; Hermann, H.; Kantelhardt, J. W.; Kertész, J.; Kirkpatrick, S.; Kurths, J.; Portugali, J.; Solomon, S.

2012-11-01

Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.

A social network analysis approach to alcohol use and co-occurring addictive behavior in young adults.

PubMed

Meisel, Matthew K; Clifton, Allan D; MacKillop, James; Goodie, Adam S

2015-12-01

The current study applied egocentric social network analysis (SNA) to investigate the prevalence of addictive behavior and co-occurring substance use in college students' networks. Specifically, we examined individuals' perceptions of the frequency of network members' co-occurring addictive behavior and investigated whether co-occurring addictive behavior is spread evenly throughout networks or is more localized in clusters. We also examined differences in network composition between individuals with varying levels of alcohol use. The study utilized an egocentric SNA approach in which respondents ("egos") enumerated 30 of their closest friends, family members, co-workers, and significant others ("alters") and the relations among alters listed. Participants were 281 undergraduates at a large university in the Southeastern United States. Robust associations were observed among the frequencies of gambling, smoking, drinking, and using marijuana by network members. We also found that alters tended to cluster together into two distinct groups: one cluster moderate-to-high on co-occurring addictive behavior and the other low on co-occurring addictive behavior. Lastly, significant differences were present when examining egos' perceptions of alters' substance use between the networks of at-risk, light, and nondrinkers. These findings provide empirical evidence of distinct clustering of addictive behavior among young adults and suggest the promise of social network-based interventions for this cohort. Copyright © 2015. Published by Elsevier Ltd.

Dopamine in the medial amygdala network mediates human bonding.

PubMed

Atzil, Shir; Touroutoglou, Alexandra; Rudy, Tali; Salcedo, Stephanie; Feldman, Ruth; Hooker, Jacob M; Dickerson, Bradford C; Catana, Ciprian; Barrett, Lisa Feldman

2017-02-28

Research in humans and nonhuman animals indicates that social affiliation, and particularly maternal bonding, depends on reward circuitry. Although numerous mechanistic studies in rodents demonstrated that maternal bonding depends on striatal dopamine transmission, the neurochemistry supporting maternal behavior in humans has not been described so far. In this study, we tested the role of central dopamine in human bonding. We applied a combined functional MRI-PET scanner to simultaneously probe mothers' dopamine responses to their infants and the connectivity between the nucleus accumbens (NAcc), the amygdala, and the medial prefrontal cortex (mPFC), which form an intrinsic network (referred to as the "medial amygdala network") that supports social functioning. We also measured the mothers' behavioral synchrony with their infants and plasma oxytocin. The results of this study suggest that synchronous maternal behavior is associated with increased dopamine responses to the mother's infant and stronger intrinsic connectivity within the medial amygdala network. Moreover, stronger network connectivity is associated with increased dopamine responses within the network and decreased plasma oxytocin. Together, these data indicate that dopamine is involved in human bonding. Compared with other mammals, humans have an unusually complex social life. The complexity of human bonding cannot be fully captured in nonhuman animal models, particularly in pathological bonding, such as that in autistic spectrum disorder or postpartum depression. Thus, investigations of the neurochemistry of social bonding in humans, for which this study provides initial evidence, are warranted.

Distributed Deliberative Recommender Systems

NASA Astrophysics Data System (ADS)

Recio-García, Juan A.; Díaz-Agudo, Belén; González-Sanz, Sergio; Sanchez, Lara Quijano

Case-Based Reasoning (CBR) is one of most successful applied AI technologies of recent years. Although many CBR systems reason locally on a previous experience base to solve new problems, in this paper we focus on distributed retrieval processes working on a network of collaborating CBR systems. In such systems, each node in a network of CBR agents collaborates, arguments and counterarguments its local results with other nodes to improve the performance of the system's global response. We describe D2ISCO: a framework to design and implement deliberative and collaborative CBR systems that is integrated as a part of jcolibritwo an established framework in the CBR community. We apply D2ISCO to one particular simplified type of CBR systems: recommender systems. We perform a first case study for a collaborative music recommender system and present the results of an experiment of the accuracy of the system results using a fuzzy version of the argumentation system AMAL and a network topology based on a social network. Besides individual recommendation we also discuss how D2ISCO can be used to improve recommendations to groups and we present a second case of study based on the movie recommendation domain with heterogeneous groups according to the group personality composition and a group topology based on a social network.

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.

Social Network Clustering and the Spread of HIV/AIDS Among Persons Who Inject Drugs in 2 Cities in the Philippines.

PubMed

Verdery, Ashton M; Siripong, Nalyn; Pence, Brian W

2017-09-01

The Philippines has seen rapid increases in HIV prevalence among people who inject drugs. We study 2 neighboring cities where a linked HIV epidemic differed in timing of onset and levels of prevalence. In Cebu, prevalence rose rapidly from below 1% to 54% between 2009 and 2011 and remained high through 2013. In nearby Mandaue, HIV remained below 4% through 2011 then rose rapidly to 38% by 2013. We hypothesize that infection prevalence differences in these cities may owe to aspects of social network structure, specifically levels of network clustering. Building on previous research, we hypothesize that higher levels of network clustering are associated with greater epidemic potential. Data were collected with respondent-driven sampling among men who inject drugs in Cebu and Mandaue in 2013. We first examine sample composition using estimators for population means. We then apply new estimators of network clustering in respondent-driven sampling data to examine associations with HIV prevalence. Samples in both cities were comparable in composition by age, education, and injection locations. Dyadic needle-sharing levels were also similar between the 2 cities, but network clustering in the needle-sharing network differed dramatically. We found higher clustering in Cebu than Mandaue, consistent with expectations that higher clustering is associated with faster epidemic spread. This article is the first to apply estimators of network clustering to empirical respondent-driven samples, and it offers suggestive evidence that researchers should pay greater attention to network structure's role in HIV transmission dynamics.

Networks of International Student Mobility: Enlargement and Consolidation of the European Transnational Education Space?

ERIC Educational Resources Information Center

Vögtle, Eva Maria; Windzio, Michael

2016-01-01

In this paper, we investigate the impact of membership in the Bologna Process on patterns and driving forces of cross-national student mobility. Student exchange flows are analyzed for almost all Bologna Process member states and non-Bologna OECD members over a ten-year period (from 2000 to 2010). We apply a social network approach focusing on…

Asymptotically inspired moment-closure approximation for adaptive networks

NASA Astrophysics Data System (ADS)

Shkarayev, Maxim; Shaw, Leah

2012-02-01

Adaptive social networks, in which nodes and network structure co-evolve, are often described using a mean-field system of equations for the density of node and link types. These equations constitute an open system due to dependence on higher order topological structures. We propose a moment-closure approximation based on the analytical description of the system in an asymptotic regime. We apply the proposed approach to two examples of adaptive networks: recruitment to a cause model and epidemic spread model. We show a good agreement between the improved mean-field prediction and simulations of the full network system.

Asymptotically inspired moment-closure approximation for adaptive networks

NASA Astrophysics Data System (ADS)

Shkarayev, Maxim

2013-03-01

Dynamics of adaptive social networks, in which nodes and network structure co-evolve, are often described using a mean-field system of equations for the density of node and link types. These equations constitute an open system due to dependence on higher order topological structures. We propose a systematic approach to moment closure approximation based on the analytical description of the system in an asymptotic regime. We apply the proposed approach to two examples of adaptive networks: recruitment to a cause model and adaptive epidemic model. We show a good agreement between the mean-field prediction and simulations of the full network system.

Asymptotically inspired moment-closure approximation for adaptive networks

NASA Astrophysics Data System (ADS)

Shkarayev, Maxim S.; Shaw, Leah B.

2013-11-01

Adaptive social networks, in which nodes and network structure coevolve, are often described using a mean-field system of equations for the density of node and link types. These equations constitute an open system due to dependence on higher-order topological structures. We propose a new approach to moment closure based on the analytical description of the system in an asymptotic regime. We apply the proposed approach to two examples of adaptive networks: recruitment to a cause model and adaptive epidemic model. We show a good agreement between the improved mean-field prediction and simulations of the full network system.

Color, Capital, and the Climb to the Headship: The Impact of Social Capital on People of Color when Applying to Become a Head of an Independent School

ERIC Educational Resources Information Center

Brown, Ara Carlos

2012-01-01

The literature on social networks, homophily, and educational backgrounds indicates that people of color have less access to the social capital that would be necessary to be considered for the position of head of an independent school in the United States. Furthermore, research indicates that people of color receive decreased returns on their…

Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale

PubMed Central

Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D.; Sinatra, Maria

2017-01-01

Aim Research into social networking addiction has greatly increased over the last decade. However, the number of validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship between attachment styles and SNS addiction. Methods A total of 769 participants were recruited to this study. Confirmatory factor analysis (CFA) and multigroup analyses were applied to assess construct validity of the Italian version of the BSMAS. Reliability analyses comprised the average variance extracted, the standard error of measurement, and the factor determinacy coefficient. Results Indices obtained from the CFA showed the Italian version of the BSMAS to have an excellent fit of the model to the data, thus confirming the single-factor structure of the instrument. Measurement invariance was established at configural, metric, and strict invariances across age groups, and at configural and metric levels across gender groups. Internal consistency was supported by several indicators. In addition, the theoretical associations between SNS addiction and attachment styles were generally supported. Conclusion This study provides evidence that the Italian version of the BSMAS is a psychometrically robust tool that can be used in future Italian research into social networking addiction. PMID:28494648

Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale.

PubMed

Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D; Sinatra, Maria

2017-06-01

Aim Research into social networking addiction has greatly increased over the last decade. However, the number of validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship between attachment styles and SNS addiction. Methods A total of 769 participants were recruited to this study. Confirmatory factor analysis (CFA) and multigroup analyses were applied to assess construct validity of the Italian version of the BSMAS. Reliability analyses comprised the average variance extracted, the standard error of measurement, and the factor determinacy coefficient. Results Indices obtained from the CFA showed the Italian version of the BSMAS to have an excellent fit of the model to the data, thus confirming the single-factor structure of the instrument. Measurement invariance was established at configural, metric, and strict invariances across age groups, and at configural and metric levels across gender groups. Internal consistency was supported by several indicators. In addition, the theoretical associations between SNS addiction and attachment styles were generally supported. Conclusion This study provides evidence that the Italian version of the BSMAS is a psychometrically robust tool that can be used in future Italian research into social networking addiction.

Social Networks, Engagement and Resilience in University Students.

PubMed

Fernández-Martínez, Elena; Andina-Díaz, Elena; Fernández-Peña, Rosario; García-López, Rosa; Fulgueiras-Carril, Iván; Liébana-Presa, Cristina

2017-12-01

Analysis of social networks may be a useful tool for understanding the relationship between resilience and engagement, and this could be applied to educational methodologies, not only to improve academic performance, but also to create emotionally sustainable networks. This descriptive study was carried out on 134 university students. We collected the network structural variables, degree of resilience (CD-RISC 10), and engagement (UWES-S). The computer programs used were excel, UCINET for network analysis, and SPSS for statistical analysis. The analysis revealed results of means of 28.61 for resilience, 2.98 for absorption, 4.82 for dedication, and 3.13 for vigour. The students had two preferred places for sharing information: the classroom and WhatsApp. The greater the value for engagement, the greater the degree of centrality in the friendship network among students who are beginning their university studies. This relationship becomes reversed as the students move to later academic years. In terms of resilience, the highest values correspond to greater centrality in the friendship networks. The variables of engagement and resilience influenced the university students' support networks.

Social Networks, Engagement and Resilience in University Students

PubMed Central

García-López, Rosa; Fulgueiras-Carril, Iván

2017-01-01

Analysis of social networks may be a useful tool for understanding the relationship between resilience and engagement, and this could be applied to educational methodologies, not only to improve academic performance, but also to create emotionally sustainable networks. This descriptive study was carried out on 134 university students. We collected the network structural variables, degree of resilience (CD-RISC 10), and engagement (UWES-S). The computer programs used were excel, UCINET for network analysis, and SPSS for statistical analysis. The analysis revealed results of means of 28.61 for resilience, 2.98 for absorption, 4.82 for dedication, and 3.13 for vigour. The students had two preferred places for sharing information: the classroom and WhatsApp. The greater the value for engagement, the greater the degree of centrality in the friendship network among students who are beginning their university studies. This relationship becomes reversed as the students move to later academic years. In terms of resilience, the highest values correspond to greater centrality in the friendship networks. The variables of engagement and resilience influenced the university students’ support networks. PMID:29194361

Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions.

PubMed

Fountain-Jones, Nicholas M; Packer, Craig; Troyer, Jennifer L; VanderWaal, Kimberly; Robinson, Stacie; Jacquot, Maude; Craft, Meggan E

2017-10-01

Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. Here, we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype-specific transmission pathways in a social carnivore. We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIV Ple ) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIV Ple molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father- and/or mother-offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype-specific FIV Ple co-occurrence networks and assessed what combination of social networks, spatial networks or co-infection best structured the FIV Ple network. While social organization (i.e., pride) was an important component of FIV Ple transmission pathways at all scales, we find that FIV Ple subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIV Ple transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype-specific. Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Benford’s Distribution in Complex Networks

PubMed Central

Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K.

2016-01-01

Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford’s distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford’s law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford’s law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford’s distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford’s law for scalefree networks but only for very narrow range of their parameters. PMID:27748398

Applying social network analysis to understand the knowledge sharing behaviour of practitioners in a clinical online discussion forum.

PubMed

Stewart, Samuel Alan; Abidi, Syed Sibte Raza

2012-12-04

Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment--an online discussion forum--for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is strong interprofessional and interregional communication, but a dearth of non-nurse participants has been identified as a shortcoming. The results of the analysis suggest that the discussion forum is active and healthy, and that, though few, the interprofessional and interinstitutional ties are strong.

Blood hero: An application for encouraging the blood donation by applying gamification.

PubMed

Domingos, Daniela C L; Lima, Luis F S G; Messias, Thiago F; Feijo, Jose V L; Diniz, Anthony A R; Soares, Heliana B

2016-08-01

There is a strong need for actions to supply the blood demand in the World. Based on this fact, it was designed an application, named `Blood Hero', by applying the `gamification' concept, which allows users to be rewarded by social acts related to the blood donation. It takes advantage of the application of mobile devices, implementing a specific social network, to attract and retain blood donators. This application makes possible an interaction between users and blood centers, and is being tested aiming at evaluating its acceptance and impact in bloodstocks.

A systematic review of nurse-related social network analysis studies.

PubMed

Benton, D C; Pérez-Raya, F; Fernández-Fernández, M P; González-Jurado, M A

2015-09-01

Nurses frequently work as part of both uni- and multidisciplinary teams. Communication between team members is critical in the delivery of quality care. Social network analysis is increasingly being used to explore such communication. To explore the use of social network analysis involving nurses either as subjects of the study or as researchers. Standard systematic review procedures were applied to identify nurse-related studies that utilize social network analysis. A comparative thematic approach to synthesis was used. Both published and grey literature written in English, Spanish and Portuguese between January 1965 and December 2013 were identified via a structured search of CINAHL, SciELO and PubMed. In addition, Google and Yahoo search engines were used to identify additional grey literature using the same search strategy. Forty-three primary studies were identified with literature from North America dominating the published work. So far it would appear that no author or group of authors have developed a programme of research in the nursing field using the social network analysis approach although several authors may be in the process of doing so. The dominance of literature from North America may be viewed as problematic as the underlying structures and themes may be an artefact of cultural communication norms from this region. The use of social network analysis in relation to nursing and by nurse researchers has increased rapidly over the past two decades. The lack of longitudinal studies and the absence of replication across multiple sites should be seen as an opportunity for further research. This analytical approach is relatively new in the field of nursing but does show considerable promise in offering insights into the way information flows between individuals, teams, institutions and other structures. An understanding of these structures provides a means of improving communication. © 2014 International Council of Nurses.

Social networks help to infer causality in the tumor microenvironment.

PubMed

Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis

2016-03-15

Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.

The cost of service quality improvements: tracking the flow of funds in social franchise networks in Myanmar

PubMed Central

2013-01-01

Introduction This paper examines the cost of quality improvements in Population Services International (PSI) Myanmar’s social franchise operations from 2007 to 2009. Methods The social franchise commodities studied were products for reproductive health, malaria, STIs, pneumonia, and diarrhea. This project applied ingredients based costing for labor, supplies, transport, and overhead. Data were gathered seven during key informant interviews with staff in the central Yangon office, examination of 3 years of payroll data, examination of a time motion study conducted by PSI, and spreadsheets recording the costs of acquiring and transporting supplies. Results In 2009 PSI Myanmar’s social franchise devoted $2.02 million towards a 94% reduction in commodity prices offered to its network of over 1700 primary care providers. These providers retained 1/3 of the subsidy as revenue and passed along the other 2/3 to their patients in the course of offering subsidized care for 1.5 million health episodes. In addition, PSI Myanmar devoted $2.09 million to support a team of franchise officers who conducted quality assurance for the private providers overseeing service quality and to distributing medical commodities. Conclusion In Myanmar, the social franchise operated by PSI spends roughly $1.00 in quality management and retailing for every $1.00 spent subsidizing medical commodities. Some services are free, but patients also pay fees for other lines of service. Overall patients contribute 1/6 as much as PSI does. Unlike other NGO’s, health services in social franchises like PSI are not all free to the patients, nor are the discounts uniformly applied. Discounts and subsidies evolve in response to public health concerns, market demand, providers’ cost structures as well as strategic objectives in maintaining the network and its portfolio of services. PMID:23826743

The cost of service quality improvements: tracking the flow of funds in social franchise networks in Myanmar.

PubMed

Bishai, David; LeFevre, Amnesty; Theuss, Marc; Boxshall, Matt; Hetherington, John D; Zaw, Min; Montagu, Dominic

2013-01-01

This paper examines the cost of quality improvements in Population Services International (PSI) Myanmar's social franchise operations from 2007 to 2009. The social franchise commodities studied were products for reproductive health, malaria, STIs, pneumonia, and diarrhea. This project applied ingredients based costing for labor, supplies, transport, and overhead. Data were gathered seven during key informant interviews with staff in the central Yangon office, examination of 3 years of payroll data, examination of a time motion study conducted by PSI, and spreadsheets recording the costs of acquiring and transporting supplies. In 2009 PSI Myanmar's social franchise devoted $2.02 million towards a 94% reduction in commodity prices offered to its network of over 1700 primary care providers. These providers retained 1/3 of the subsidy as revenue and passed along the other 2/3 to their patients in the course of offering subsidized care for 1.5 million health episodes. In addition, PSI Myanmar devoted $2.09 million to support a team of franchise officers who conducted quality assurance for the private providers overseeing service quality and to distributing medical commodities. In Myanmar, the social franchise operated by PSI spends roughly $1.00 in quality management and retailing for every $1.00 spent subsidizing medical commodities. Some services are free, but patients also pay fees for other lines of service. Overall patients contribute 1/6 as much as PSI does. Unlike other NGO's, health services in social franchises like PSI are not all free to the patients, nor are the discounts uniformly applied. Discounts and subsidies evolve in response to public health concerns, market demand, providers' cost structures as well as strategic objectives in maintaining the network and its portfolio of services.

Social networks: Evolving graphs with memory dependent edges

NASA Astrophysics Data System (ADS)

Grindrod, Peter; Parsons, Mark

2011-10-01

The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Common neighbour structure and similarity intensity in complex networks

NASA Astrophysics Data System (ADS)

Hou, Lei; Liu, Kecheng

2017-10-01

Complex systems as networks always exhibit strong regularities, implying underlying mechanisms governing their evolution. In addition to the degree preference, the similarity has been argued to be another driver for networks. Assuming a network is randomly organised without similarity preference, the present paper studies the expected number of common neighbours between vertices. A symmetrical similarity index is accordingly developed by removing such expected number from the observed common neighbours. The developed index can not only describe the similarities between vertices, but also the dissimilarities. We further apply the proposed index to measure of the influence of similarity on the wring patterns of networks. Fifteen empirical networks as well as artificial networks are examined in terms of similarity intensity and degree heterogeneity. Results on real networks indicate that, social networks are strongly governed by the similarity as well as the degree preference, while the biological networks and infrastructure networks show no apparent similarity governance. Particularly, classical network models, such as the Barabási-Albert model, the Erdös-Rényi model and the Ring Lattice, cannot well describe the social networks in terms of the degree heterogeneity and similarity intensity. The findings may shed some light on the modelling and link prediction of different classes of networks.

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.

Analysis of Layered Social Networks

DTIC Science & Technology

2006-09-01

C . Anderson , O . P . John , D . Keltner , and A. M. Kring. Who attains social sta- tus... of action is provided by the following equation, U ( c ) = ∑ d (PdEx), where 56 Religious Financial Commercial Military Infrastructure Avoid Secure...Assuming that this methodology can indeed be applied to the transmission of information, the matrix powers ( p > 2) actually capture a variety of walks

Exploring the Social Integration of Sexual Minority Youth across High School Contexts

ERIC Educational Resources Information Center

Martin-Storey, Alexa; Cheadle, Jacob E.; Skalamera, Julie; Crosnoe, Robert

2015-01-01

Mental health disparities between sexual minority and other youth have been theorized to result in part from the effects of the stigmatization on social integration. Stochastic actor-based modeling was applied to complete network data from two high schools in the National Longitudinal Study of Adolescent Health (M[subscript age] = 15 years,…

Mapping Functional Brain Development: Building a Social Brain through Interactive Specialization

ERIC Educational Resources Information Center

Johnson, Mark H.; Grossmann, Tobias; Kadosh, Kathrin Cohen

2009-01-01

The authors review a viewpoint on human functional brain development, interactive specialization (IS), and its application to the emerging network of cortical regions referred to as the "social brain." They advance the IS view in 2 new ways. First, they extend IS into a domain to which it has not previously been applied--the emergence of social…

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Ihli, Monica; Hendrick, Oscar; Delgado-Arias, Sabrina; Escobar, Vanessa M.; Griffith, Peter

2015-01-01

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

The roosting spatial network of a bird-predator bat.

PubMed

Fortuna, Miguel A; Popa-Lisseanu, Ana G; Ibáñez, Carlos; Bascompte, Jordi

2009-04-01

The use of roosting sites by animal societies is important in conservation biology, animal behavior, and epidemiology. The giant noctule bat (Nyctalus lasiopterus) constitutes fission-fusion societies whose members spread every day in multiple trees for shelter. To assess how the pattern of roosting use determines the potential for information exchange or disease spreading, we applied the framework of complex networks. We found a social and spatial segregation of the population in well-defined modules or compartments, formed by groups of bats sharing the same trees. Inside each module, we revealed an asymmetric use of trees by bats representative of a nested pattern. By applying a simple epidemiological model, we show that there is a strong correlation between network structure and the rate and shape of infection dynamics. This modular structure slows down the spread of diseases and the exchange of information through the entire network. The implication for management is complex, affecting differently the cohesion inside and among colonies and the transmission of parasites and diseases. Network analysis can hence be applied to quantifying the conservation status of individual trees used by species depending on hollows for shelter.

Immunization strategy for epidemic spreading on multilayer networks

NASA Astrophysics Data System (ADS)

Buono, C.; Braunstein, L. A.

2015-01-01

In many real-world complex systems, individuals have many kinds of interactions among them, suggesting that it is necessary to consider a layered-structure framework to model systems such as social interactions. This structure can be captured by multilayer networks and can have major effects on the spreading of process that occurs over them, such as epidemics. In this letter we study a targeted immunization strategy for epidemic spreading over a multilayer network. We apply the strategy in one of the layers and study its effect in all layers of the network disregarding degree-degree correlation among layers. We found that the targeted strategy is not as efficient as in isolated networks, due to the fact that in order to stop the spreading of the disease it is necessary to immunize more than 80% of the individuals. However, the size of the epidemic is drastically reduced in the layer where the immunization strategy is applied compared to the case with no mitigation strategy. Thus, the immunization strategy has a major effect on the layer were it is applied, but does not efficiently protect the individuals of other layers.

A Statistical Approach to Characterize and Detect degradation Within the Barabasi-Albert Network

DTIC Science & Technology

2016-09-01

Astrophysics Collaborations 16046 932.11 0.4948 520.10|6 57 High-Energy Physics Theory Collaborations 7610 251.54 0.9481 -16.27|6 22 High-Energy Physics ...social, physical , and biological phenomena [6, 70, 16, 107]. The Barabási-Albert network exhibits the scale-free property and is highly desired for...It was noted that there has also been considerable effort in applying various types of graph entropies in the field of network physics . Mowshowitz and

Social Network Influence and Personal Financial Status

NASA Astrophysics Data System (ADS)

Luo, Shaojun; Morone, Flaviano; Sarraute, Carlos; Makse, Hernan

Networks of social ties emerging from individual economic needs display a highly structured architecture. In response to socio-economic demands, people reshape their circle of contacts for maximizing their social status, and ipso facto, the pattern of their interconnections is strongly correlates with their personal financial situation. In this work we transform this qualitative and verbal statement into an operative definition, which allows us to quantify the economic wellness of individuals trough a measure of their collective influence. We consider the network of mobile phone calls made by the Mexican population during three months, in order to study the correlation of person's economic situation with her network location. Notably, we find that rich people tend to be also the most influential nodes, i.e., they self-organize to optimally position themselves in the network. This finding may be also raised at the level of a principle, a fact that would explain the emergence of the phenomenon of collective influence itself as the result of the local optimization of socio-economic interactions. Our method represents a powerful and efficient indicator of socio-economic robustness, which may be applied to maximize the effect of large scale economic intervention and stimulus policies

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Infection dynamics on spatial small-world network models

NASA Astrophysics Data System (ADS)

Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario

2017-11-01

The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.

Cooperation dynamics of generalized reciprocity in state-based social dilemmas

NASA Astrophysics Data System (ADS)

Stojkoski, Viktor; Utkovski, Zoran; Basnarkov, Lasko; Kocarev, Ljupco

2018-05-01

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone." Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation, and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation by dictating the degree of cooperation displayed both at the microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.

Influence of network dynamics on the spread of sexually transmitted diseases.

PubMed

Risau-Gusman, Sebastián

2012-06-07

Network epidemiology often assumes that the relationships defining the social network of a population are static. The dynamics of relationships is only taken indirectly into account by assuming that the relevant information to study epidemic spread is encoded in the network obtained, by considering numbers of partners accumulated over periods of time roughly proportional to the infectious period of the disease. On the other hand, models explicitly including social dynamics are often too schematic to provide a reasonable representation of a real population, or so detailed that no general conclusions can be drawn from them. Here, we present a model of social dynamics that is general enough so its parameters can be obtained by fitting data from surveys about sexual behaviour, but that can still be studied analytically, using mean-field techniques. This allows us to obtain some general results about epidemic spreading. We show that using accumulated network data to estimate the static epidemic threshold lead to a significant underestimation of that threshold. We also show that, for a dynamic network, the relative epidemic threshold is an increasing function of the infectious period of the disease, implying that the static value is a lower bound to the real threshold. A practical example is given of how to apply the model to the study of a real population.

Influence of network dynamics on the spread of sexually transmitted diseases

PubMed Central

Risau-Gusman, Sebastián

2012-01-01

Network epidemiology often assumes that the relationships defining the social network of a population are static. The dynamics of relationships is only taken indirectly into account by assuming that the relevant information to study epidemic spread is encoded in the network obtained, by considering numbers of partners accumulated over periods of time roughly proportional to the infectious period of the disease. On the other hand, models explicitly including social dynamics are often too schematic to provide a reasonable representation of a real population, or so detailed that no general conclusions can be drawn from them. Here, we present a model of social dynamics that is general enough so its parameters can be obtained by fitting data from surveys about sexual behaviour, but that can still be studied analytically, using mean-field techniques. This allows us to obtain some general results about epidemic spreading. We show that using accumulated network data to estimate the static epidemic threshold lead to a significant underestimation of that threshold. We also show that, for a dynamic network, the relative epidemic threshold is an increasing function of the infectious period of the disease, implying that the static value is a lower bound to the real threshold. A practical example is given of how to apply the model to the study of a real population. PMID:22112655

A Social Network Analysis of a Coalition Initiative to Prevent Underage Drinking in Los Angeles County

PubMed Central

Chu, Kar-Hai; Hoeppner, Elena; Valente, Thomas; Rohrbach, Luanne

2016-01-01

In 2011, the Los Angeles County Department of Public Health began a prevention services initiative to address problems dealing with alcohol and other drugs across the County. A major component of the strategy included the formation of eight coalitions. Defined by geographic borders, each coalition consisted of multiple service provider organizations, and were mandated to implement customized plans that would focus on preventing underage drinking by addressing availability and accessibility of alcohol. In this study, we collect survey data and observe coalition meetings to study the interactions within and between coalitions. We are informed by network tie strength theories to supplement our view of how organizations communicate. We apply social network analysis to learn how the multi-coalition network is functioning, and identify important unrealized connections. Our findings suggest there are many potential connections between coalitions that are not being leveraged. PMID:27899879

Application of actor level social characteristic indicator selection for the precursory detection of bullies in online social networks

NASA Astrophysics Data System (ADS)

White, Holly M.; Fields, Jeremy; Hall, Robert T.; White, Joshua S.

2016-05-01

Bullying is a national problem for families, courts, schools, and the economy. Social, educational, and professional lives of victims are affected. Early detection of bullies mitigates destructive effects of bullying. Our previous research found, given specific characteristics of an actor, actor logics can be developed utilizing input from natural language processing and graph analysis. Given similar characteristics of cyberbullies, in this paper, we create specific actor logics and apply these to a select social media dataset for the purpose of rapid identification of cyberbullying.

Social Milieu Oriented Routing: A New Dimension to Enhance Network Security in WSNs.

PubMed

Liu, Lianggui; Chen, Li; Jia, Huiling

2016-02-19

In large-scale wireless sensor networks (WSNs), in order to enhance network security, it is crucial for a trustor node to perform social milieu oriented routing to a target a trustee node to carry out trust evaluation. This challenging social milieu oriented routing with more than one end-to-end Quality of Trust (QoT) constraint has proved to be NP-complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this challenging problem. However, existing solutions cannot guarantee the efficiency of searching; that is, they can hardly avoid obtaining partial optimal solutions during a searching process. Quantum annealing (QA) uses delocalization and tunneling to avoid falling into local minima without sacrificing execution time. This has been proven a promising way to many optimization problems in recently published literatures. In this paper, for the first time, with the help of a novel approach, that is, configuration path-integral Monte Carlo (CPIMC) simulations, a QA-based optimal social trust path (QA_OSTP) selection algorithm is applied to the extraction of the optimal social trust path in large-scale WSNs. Extensive experiments have been conducted, and the experiment results demonstrate that QA_OSTP outperforms its heuristic opponents.

Applying Social Network Analysis to Identify the Social Support Needs of Adolescent and Young Adult Cancer Patients and Survivors.

PubMed

Koltai, Kolina; Walsh, Casey; Jones, Barbara; Berkelaar, Brenda L

2018-04-01

This article examines how theoretical and clinical applications of social network analysis (SNA) can inform opportunities for innovation and advancement of social support programming for adolescent and young adult (AYA) cancer patients and survivors. SNA can help address potential barriers and challenges to initiating and sustaining AYA peer support by helping to identify the diverse psychosocial needs among individuals in the AYA age range; find strategic ways to support and connect AYAs at different phases of the cancer trajectory with resources and services; and increase awareness of psychosocial resources and referrals from healthcare providers. Network perspectives on homophily, proximity, and evolution provide a foundational basis to explore the utility of SNA in AYA clinical care and research initiatives. The uniqueness of the AYA oncology community can also provide insight into extending and developing current SNA theories. Using SNA in AYA psychosocial cancer research has the potential to create new ideas and pathways for supporting AYAs across the continuum of care, while also extending theories of SNA. SNA may also prove to be a useful tool for examining social support resources for AYAs with various chronic health conditions and other like groups.

Online respondent-driven sampling for studying contact patterns relevant for the spread of close-contact pathogens: a pilot study in Thailand.

PubMed

Stein, Mart L; van Steenbergen, Jim E; Chanyasanha, Charnchudhi; Tipayamongkholgul, Mathuros; Buskens, Vincent; van der Heijden, Peter G M; Sabaiwan, Wasamon; Bengtsson, Linus; Lu, Xin; Thorson, Anna E; Kretzschmar, Mirjam E E

2014-01-01

Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens. We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks. We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts. Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks.

Online Respondent-Driven Sampling for Studying Contact Patterns Relevant for the Spread of Close-Contact Pathogens: A Pilot Study in Thailand

PubMed Central

Stein, Mart L.; van Steenbergen, Jim E.; Chanyasanha, Charnchudhi; Tipayamongkholgul, Mathuros; Buskens, Vincent; van der Heijden, Peter G. M.; Sabaiwan, Wasamon; Bengtsson, Linus; Lu, Xin; Thorson, Anna E.; Kretzschmar, Mirjam E. E.

2014-01-01

Background Information on social interactions is needed to understand the spread of airborne infections through a population. Previous studies mostly collected egocentric information of independent respondents with self-reported information about contacts. Respondent-driven sampling (RDS) is a sampling technique allowing respondents to recruit contacts from their social network. We explored the feasibility of webRDS for studying contact patterns relevant for the spread of respiratory pathogens. Materials and Methods We developed a webRDS system for facilitating and tracking recruitment by Facebook and email. One-day diary surveys were conducted by applying webRDS among a convenience sample of Thai students. Students were asked to record numbers of contacts at different settings and self-reported influenza-like-illness symptoms, and to recruit four contacts whom they had met in the previous week. Contacts were asked to do the same to create a network tree of socially connected individuals. Correlations between linked individuals were analysed to investigate assortativity within networks. Results We reached up to 6 waves of contacts of initial respondents, using only non-material incentives. Forty-four (23.0%) of the initially approached students recruited one or more contacts. In total 257 persons participated, of which 168 (65.4%) were recruited by others. Facebook was the most popular recruitment option (45.1%). Strong assortative mixing was seen by age, gender and education, indicating a tendency of respondents to connect to contacts with similar characteristics. Random mixing was seen by reported number of daily contacts. Conclusions Despite methodological challenges (e.g. clustering among respondents and their contacts), applying RDS provides new insights in mixing patterns relevant for close-contact infections in real-world networks. Such information increases our knowledge of the transmission of respiratory infections within populations and can be used to improve existing modelling approaches. It is worthwhile to further develop and explore webRDS for the detection of clusters of respiratory symptoms in social networks. PMID:24416371

Tracking the Evolution of Infrastructure Systems and Mass Responses Using Publically Available Data

PubMed Central

Guan, Xiangyang; Chen, Cynthia; Work, Dan

2016-01-01

Networks can evolve even on a short-term basis. This phenomenon is well understood by network scientists, but receive little attention in empirical literature involving real-world networks. On one hand, this is due to the deceitfully fixed topology of some networks such as many physical infrastructures, whose evolution is often deemed unlikely to occur in short term; on the other hand, the lack of data prohibits scientists from studying subjects such as social networks that seem likely to evolve on a short-term basis. We show that both networks—the infrastructure network and social network—are able to demonstrate evolutionary dynamics at the system level even in the short-term, characterized by shifting between different phases as predicted in network science. We develop a methodology of tracking the evolutionary dynamics of the two networks by incorporating flows and the microstructure of networks such as motifs. This approach is applied to the human interaction network and two transportation networks (subway and taxi) in the context of Hurricane Sandy, using publically available Twitter data and transportation data. Our result shows that significant changes in the system-level structure of networks can be detected on a continuous basis. This result provides a promising channel for real-time tracking in the future. PMID:27907061

Reciprocity and the Emergence of Power Laws in Social Networks

NASA Astrophysics Data System (ADS)

Schnegg, Michael

Research in network science has shown that many naturally occurring and technologically constructed networks are scale free, that means a power law degree distribution emerges from a growth model in which each new node attaches to the existing network with a probability proportional to its number of links (= degree). Little is known about whether the same principles of local attachment and global properties apply to societies as well. Empirical evidence from six ethnographic case studies shows that complex social networks have significantly lower scaling exponents γ ~ 1 than have been assumed in the past. Apparently humans do not only look for the most prominent players to play with. Moreover cooperation in humans is characterized through reciprocity, the tendency to give to those from whom one has received in the past. Both variables — reciprocity and the scaling exponent — are negatively correlated (r = -0.767, sig = 0.075). If we include this effect in simulations of growing networks, degree distributions emerge that are much closer to those empirically observed. While the proportion of nodes with small degrees decreases drastically as we introduce reciprocity, the scaling exponent is more robust and changes only when a relatively large proportion of attachment decisions follow this rule. If social networks are less scale free than previously assumed this has far reaching implications for policy makers, public health programs and marketing alike.

Caught in the middle? How women deal with conflicting pregnancy-advice from health professionals and their social networks.

PubMed

Schölmerich, Vera L N; Ghorashi, Halleh; Denktaş, Semiha; Groenewegen, Peter

2016-04-01

to investigate how pregnant women deal with conflicting advice from their social networks and their caregivers and how this influenced their pregnancy-related behaviours. a qualitative study based on face-to-face interviews and focus-groups. We applied an inductive analysis technique closely following the 'Gioia method'. impoverished neighbourhoods in Rotterdam, the Netherlands. 40 women who were pregnant, or had given birth within the last 12 months. 12 women were Native Dutch, 16 had a Moroccan background, and 12 had a Turkish background. all women faced a misalignment of advice by health professionals and social networks. For the native Dutch respondents, this misalignment did not seem to present a challenge. They had a strongly articulated preference for the advice of health professionals, and did not fear any social consequences for openly following their advice. For the women with a Turkish/Moroccan background, however, this discrepancy in advice presented a dilemma. Following one piece of advice seemed to exclude also following the other one, which would possibly entail social consequences. These women employed one of the three strategies to deal with this dilemma: a) avoiding the dilemma (secretly not following the advice of one side), b) embracing the dilemma (combining conflicting advice), and c) resolving the dilemma (communicating between both sides). we argue that the currently popular interventions geared towards increasing the health literacy of non-Western ethnic minority pregnant women and improving communication between ethnic minority clients and caregivers are not sufficient, and might even exacerbate the dilemma some pregnant women face. As an alternative, we recommend involving not only caregivers but also women's social network in intervention efforts. Interventions could aim to increase the negotiation capacity of the target group, but also to increase the health literacy of the members of their social network to enable the circulation of 'new' information within a rather homogeneous, tight-knit network. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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

Crafting a Social Context for Medical Informatics Networks

NASA Astrophysics Data System (ADS)

Patel, Salil H.

Effective healthcare delivery is increasingly predicated upon the availability, accuracy, and integrity of personal health information. Tracking and analysis of medical information throughout its lifeeycle may be viewed through the lenses of both physical network architecture and the broader social context in which such information is gathered and applied. As information technology and evidence-based practice models evolve in tandem, the development of interlinked multimodal and multidimensional databases has shown great promise for improving public health. To this end. providers, regulators, payers, and individual patients each share rights and responsibilities in creating a milieu which both, fosters and protects the practice and promise of medical information.

Community structure from spectral properties in complex networks

NASA Astrophysics Data System (ADS)

Servedio, V. D. P.; Colaiori, F.; Capocci, A.; Caldarelli, G.

2005-06-01

We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

Co-Production of Quality in the Applied Education Research Scheme

ERIC Educational Resources Information Center

Ozga, Jenny

2007-01-01

This contribution looks at the ways in which research quality is defined and addressed in the Applied Education Research Scheme (AERS), particularly within the network on Schools and Social Capital, which is one of the four areas of work within the overall AERS scheme. AERS is a five-year programme, funded jointly by the Scottish Executive and the…

Social support network and quality of life in multiple sclerosis patients.

PubMed

Costa, David Castro; Sá, Maria José; Calheiros, José Manuel

2017-05-01

To analyse the relationship between the social support network (SSN) and health related quality of life (HRQOL) in multiple sclerosis (MS) patients. The sample comprised 150 consecutive MS patients attending our MS clinic. To assess the socio-demographic data, a specifically designed questionnaire was applied. The HRQOL dimensions were measured with the Short-Form Health Survey Questionnaire-SF36 and the SSN with the Medical Outcomes Study Social Support Survey. Spearman's correlation was used to compare the magnitude of the relationship between the SSN and HRQOL. The mean patient age was 41.7 years (± 10.4; range: 18-70 yr); the mean Expanded Disability Status Score was 2.5 (±2.4; range: 0-9). There was a statistically significant correlation between the structure of the SSN and the HRQOL. The composition of the SSN, social group membership and participation in voluntary work have an important role in the HRQOL of patients with MS.

Implementing a social network intervention designed to enhance and diversify support for people with long-term conditions. A qualitative study.

PubMed

Kennedy, Anne; Vassilev, Ivaylo; James, Elizabeth; Rogers, Anne

2016-02-29

For people with long-term conditions, social networks provide a potentially central means of mobilising, mediating and accessing support for health and well-being. Few interventions address the implementation of improving engagement with and through social networks. This paper describes the development and implementation of a web-based tool which comprises: network mapping, user-centred preference elicitation and need assessment and facilitated engagement with resources. The study aimed to determine whether the intervention was acceptable, implementable and acted to enhance support and to add to theory concerning social networks and engagement with resources and activities. A longitudinal design with 15 case studies used ethnographic methods comprising video, non-participant observation of intervention delivery and qualitative interviews (baseline, 6 and 12 months). Participants were people with type 2 diabetes living in a marginalised island community. Facilitators were local health trainers and care navigators. Analysis applied concepts concerning implementation of technology for self-management support to explain how new practices of work were operationalised and how the technology impacted on relationships fit with everyday life and allowed for visual feedback. Most participants reported identifying and taking up new activities as a result of using the tool. Thematic analysis suggested that workability of the tool was predicated on disruption and reconstruction of networks, challenging/supportive facilitation and change and reflection over time concerning network support. Visualisation of the network enabled people to mobilise support and engage in new activities. The tool aligned synergistically with the facilitators' role of linking people to local resources. The social network tool works through a process of initiating positive disruption of established self-management practice through mapping and reflection on personal network membership and support. This opens up possibilities for reconstructing self-management differently from current practice. Key facets of successful implementation were: the visual maps of networks and support options; facilitation characterised by a perceived lack of status difference which assisted engagement and constructive discussion of support and preferences for activities; and background work (a reliable database, tailored preferences, option reduction) for facilitator and user ease of use.

Differential neural circuitry and self-interest in real vs hypothetical moral decisions

PubMed Central

Dalgleish, Tim; Thompson, Russell; Evans, Davy; Schweizer, Susanne; Mobbs, Dean

2012-01-01

Classic social psychology studies demonstrate that people can behave in ways that contradict their intentions—especially within the moral domain. We measured brain activity while subjects decided between financial self-benefit (earning money) and preventing physical harm (applying an electric shock) to a confederate under both real and hypothetical conditions. We found a shared neural network associated with empathic concern for both types of decisions. However, hypothetical and real moral decisions also recruited distinct neural circuitry: hypothetical moral decisions mapped closely onto the imagination network, while real moral decisions elicited activity in the bilateral amygdala and anterior cingulate—areas essential for social and affective processes. Moreover, during real moral decision-making, distinct regions of the prefrontal cortex (PFC) determined whether subjects make selfish or pro-social moral choices. Together, these results reveal not only differential neural mechanisms for real and hypothetical moral decisions but also that the nature of real moral decisions can be predicted by dissociable networks within the PFC. PMID:22711879

The UK-SEA-ME Psychosocial-Cultural Cancer Research Network: setting the stage for applied qualitative research on cancer health behaviour in southeast Asia and the Middle East.

PubMed

Lim, Jennifer N W

2011-01-01

Psychosocial and cultural factors influencing cancer health behaviour have not been systematically investigated outside the western culture, and qualitative research is the best approach for this type of social research. The research methods employed to study health problems in Asia predominantly are quantitative techniques. The set up of the first psychosocial cancer research network in Asia marks the beginning of a collaboration to promote and spearhead applied qualitative healthcare research in cancer in the UK, Southeast Asia and the Middle East. This paper sets out the rationale, objectives and mission for the UK-SEA-ME Psychosocial-Cultural Cancer Research Network. The UK-SEA-ME network is made up of collaborators from the University of Leeds (UK), the University of Malaya (Malaysia), the National University of Singapore (Singapore) and the University of United Arab Emirates (UAE). The network promotes applied qualitative research to investigate the psychosocial and cultural factors influencing delayed and late presentation and diagnosis for cancer (breast cancer) in partner countries, as well as advocating the use of the mixed-methods research approach. The network also offers knowledge transfer for capacity building within network universities. The mission of the network is to improve public awareness about the importance of early management and prevention of cancer through research in Asia.

Intimate-Partner and Client-Initiated Violence among Female Street-Based Sex Workers in China: Does a Support Network Help?

PubMed

Hail-Jares, Katie; Chang, Ruth C F; Choi, Sugy; Zheng, Huang; He, Na; Huang, Z Jennifer

2015-01-01

Globally, female street-based sex workers are vulnerable to gender-based violence. Previous research has shown having a peer social network can reduce sex workers' risks of victimization. However, mechanisms of how social network impacts violence among female street-based sex workers are still far from clear. Our study was based on data abstracted from a paper-and-pencil survey administered among 218 female street-based sex workers in Shanghai, China. We focused on self-reported client-initiated violence and intimate-partner violence in emotional, physical, and sexual forms. Social networks were characterized by the size and sources of financial and psychosocial support (e.g. family, friends, and peers). Multi-variable logistic regression was used to estimate adjusted odds ratios (AOR) of each type of violence exposure by social network structure after the adjustment of age, education, and years in Shanghai. The street-based female sex workers in our study were primarily rural-to-urban migrants (95.7%) with an average age of 41 years old. 24.3% and 62.8% of the sex workers reported intimate-partner violence and client-initiated violence respectively. Lack of financial support, as defined by having only one individual or none in her peer support system to help financially, was significantly associated with self-reported intimate-partner violence (AOR: 2.5; 95% CI: 1.1-5.9). Respondents who reported client-initiated violence, by contrast, were more likely to report lacked psychosocial support from family (AOR: 2.2, 95% CI: 1.0-4.6) and peers (AOR: 5.1, 95% CI: 2.2-11). This study is one of the first to systematically analyze the associations between social network and gender-based violence among street-based female sex worker. We reported a high prevalence of both types of gender-based violence and their complex associations with family, friends, and peer support network. Policies with goals to reduce violence against women may apply these findings to leverage social network in the interventions against gender-based violence.

Intimate-Partner and Client-Initiated Violence among Female Street-Based Sex Workers in China: Does a Support Network Help?

PubMed Central

Hail-Jares, Katie; Chang, Ruth C. F.; Choi, Sugy; Zheng, Huang; He, Na; Huang, Z. Jennifer

2015-01-01

Background Globally, female street-based sex workers are vulnerable to gender-based violence. Previous research has shown having a peer social network can reduce sex workers’ risks of victimization. However, mechanisms of how social network impacts violence among female street-based sex workers are still far from clear. Methods Our study was based on data abstracted from a paper-and-pencil survey administered among 218 female street-based sex workers in Shanghai, China. We focused on self-reported client-initiated violence and intimate-partner violence in emotional, physical, and sexual forms. Social networks were characterized by the size and sources of financial and psychosocial support (e.g. family, friends, and peers). Multi-variable logistic regression was used to estimate adjusted odds ratios (AOR) of each type of violence exposure by social network structure after the adjustment of age, education, and years in Shanghai. Results The street-based female sex workers in our study were primarily rural-to-urban migrants (95.7%) with an average age of 41 years old. 24.3% and 62.8% of the sex workers reported intimate-partner violence and client-initiated violence respectively. Lack of financial support, as defined by having only one individual or none in her peer support system to help financially, was significantly associated with self-reported intimate-partner violence (AOR: 2.5; 95% CI: 1.1–5.9). Respondents who reported client-initiated violence, by contrast, were more likely to report lacked psychosocial support from family (AOR: 2.2, 95% CI: 1.0–4.6) and peers (AOR: 5.1, 95% CI: 2.2–11). Conclusion This study is one of the first to systematically analyze the associations between social network and gender-based violence among street-based female sex worker. We reported a high prevalence of both types of gender-based violence and their complex associations with family, friends, and peer support network. Policies with goals to reduce violence against women may apply these findings to leverage social network in the interventions against gender-based violence. PMID:26413776

Matrix product algorithm for stochastic dynamics on networks applied to nonequilibrium Glauber dynamics

NASA Astrophysics Data System (ADS)

Barthel, Thomas; De Bacco, Caterina; Franz, Silvio

2018-01-01

We introduce and apply an efficient method for the precise simulation of stochastic dynamical processes on locally treelike graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for example, to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon ideas from quantum many-body theory, our approach is based on a matrix product approximation of the so-called edge messages—conditional probabilities of vertex variable trajectories. Computation costs and accuracy can be tuned by controlling the matrix dimensions of the matrix product edge messages (MPEM) in truncations. In contrast to Monte Carlo simulations, the algorithm has a better error scaling and works for both single instances as well as the thermodynamic limit. We employ it to examine prototypical nonequilibrium Glauber dynamics in the kinetic Ising model. Because of the absence of cancellation effects, observables with small expectation values can be evaluated accurately, allowing for the study of decay processes and temporal correlations.

A network approach for researching political feasibility of healthcare reform: the case of universal healthcare system in Taiwan.

PubMed

Wang, Guang-Xu

2012-12-01

This study evaluates the political feasibility of healthcare reform taking place in Taiwan in the past decade. Since Taiwan adopted National Health Insurance (NHI) in 1995, it has provided coverage for virtually all of the island's citizens. However, the imbalance between expenditure and revenue has resulted in a cycle of unsustainable spending which has necessitated financial reforms and political confrontations. By applying social network analysis, this paper examines multiple types of ties between policy elites and power distribution that have evolved in crucial policy events of the NHI's financial reforms between 1998 and 2010. Data sources include official documents and 62 social network interviews that were held with government officials and related unofficial policy participants. Blockmodeling and multidimensional scaling (MDS) are used to determine the major participants and network structures in the NHI domain, as well as the influential policy actors, based on information transmission, resource exchange, reputation attribution and action-set coalition networks in Taiwan's current political situation. The results show that although both public actors and all medical associations are the leading actors in the NHI reform, without good communication with societal actors, the promotion of reform proposals ends in failure. As a tool of political feasibility evaluation, social network analysis can map the political conflict between policy stakeholders systematically when policy makers pursue the result of policy adoption. Copyright © 2012 Elsevier Ltd. All rights reserved.

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks

PubMed Central

Mohammadi, Neda; Wang, Qi; Taylor, John E.

2016-01-01

Online social networks are today’s fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today’s online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets. PMID:27736912

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks.

PubMed

Mohammadi, Neda; Wang, Qi; Taylor, John E

2016-01-01

Online social networks are today's fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today's online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets.

L'interdisciplinarite en sciences sociales pour l'etude du contact des langues (Interdisciplinarity in Social Sciences of the Study of the Relationships of Languages). Proceedings of a Colloquium of the International Center for Research on Bilingualism and the Institute for Interethnic and Intercultural Studies and Research (2nd, Quebec City, Quebec, Canada, October 1-5, 1984).

ERIC Educational Resources Information Center

Prujiner, Alain, Ed.

Papers given at an international conference applying the social sciences to the study of the relationships of languages include the following: "Reseaux sociaux et comportements langagiers en milieu de contact des langues" ("Social Networks and Language Behaviors in a Language Contact Setting") by M. Blanc and J. Hamers, with…

A Network Analysis Perspective to Implementation: The Example of Health Links to Promote Coordinated Care.

PubMed

Yousefi Nooraie, Reza; Khan, Sobia; Gutberg, Jennifer; Baker, G Ross

2018-01-01

Although implementation models broadly recognize the importance of social relationships, our knowledge about applying social network analysis (SNA) to formative, process, and outcome evaluations of health system interventions is limited. We explored applications of adopting an SNA lens to inform implementation planning, engagement and execution, and evaluation. We used Health Links, a province-wide program in Canada aiming to improve care coordination among multiple providers of high-needs patients, as an example of a health system intervention. At the planning phase, an SNA can depict the structure, network influencers, and composition of clusters at various levels. It can inform the engagement and execution by identifying potential targets (e.g., opinion leaders) and by revealing structural gaps and clusters. It can also be used to assess the outcomes of the intervention, such as its success in increasing network connectivity; changing the position of certain actors; and bridging across specialties, organizations, and sectors. We provided an overview of how an SNA lens can shed light on the complexity of implementation along the entire implementation pathway, by revealing the relational barriers and facilitators, the application of network-informed and network-altering interventions, and testing hypotheses on network consequences of the implementation.

Modelling of information diffusion on social networks with applications to WeChat

NASA Astrophysics Data System (ADS)

Liu, Liang; Qu, Bo; Chen, Bin; Hanjalic, Alan; Wang, Huijuan

2018-04-01

Traces of user activities recorded in online social networks open new possibilities to systematically understand the information diffusion process on social networks. From the online social network WeChat, we collected a large number of information cascade trees, each of which tells the spreading trajectory of a message/information such as which user creates the information and which users view or forward the information shared by which neighbours. In this work, we propose two heterogeneous non-linear models, one for the topologies of the information cascade trees and the other for the stochastic process of information diffusion on a social network. Both models are validated by the WeChat data in reproducing and explaining key features of cascade trees. Specifically, we apply the Random Recursive Tree (RRT) to model the growth of cascade trees. The RRT model could capture key features, i.e. the average path length and degree variance of a cascade tree in relation to the number of nodes (size) of the tree. Its single identified parameter quantifies the relative depth or broadness of the cascade trees and indicates that information propagates via a star-like broadcasting or viral-like hop by hop spreading. The RRT model explains the appearance of hubs, thus a possibly smaller average path length as the cascade size increases, as observed in WeChat. We further propose the stochastic Susceptible View Forward Removed (SVFR) model to depict the dynamic user behaviour including creating, viewing, forwarding and ignoring a message on a given social network. Beside the average path length and degree variance of the cascade trees in relation to their sizes, the SVFR model could further explain the power-law cascade size distribution in WeChat and unravel that a user with a large number of friends may actually have a smaller probability to read a message (s)he receives due to limited attention.

Transmission of severe acute respiratory syndrome in dynamical small-world networks

NASA Astrophysics Data System (ADS)

Masuda, Naoki; Konno, Norio; Aihara, Kazuyuki

2004-03-01

The outbreak of severe acute respiratory syndrome (SARS) is still threatening the world because of a possible resurgence. In the current situation that effective medical treatments such as antiviral drugs are not discovered yet, dynamical features of the epidemics should be clarified for establishing strategies for tracing, quarantine, isolation, and regulating social behavior of the public at appropriate costs. Here we propose a network model for SARS epidemics and discuss why superspreaders emerged and why SARS spread especially in hospitals, which were key factors of the recent outbreak. We suggest that superspreaders are biologically contagious patients, and they may amplify the spreads by going to potentially contagious places such as hospitals. To avoid mass transmission in hospitals, it may be a good measure to treat suspected cases without hospitalizing them. Finally, we indicate that SARS probably propagates in small-world networks associated with human contacts and that the biological nature of individuals and social group properties are factors more important than the heterogeneous rates of social contacts among individuals. This is in marked contrast with epidemics of sexually transmitted diseases or computer viruses to which scale-free network models often apply.

#Stupidcancer: Exploring a Typology of Social Support and the Role of Emotional Expression in a Social Media Community.

PubMed

Myrick, Jessica Gall; Holton, Avery E; Himelboim, Itai; Love, Brad

2016-01-01

Social network sites (SNSs) like Twitter continue to attract users, many of whom turn to these spaces for social support for serious illnesses like cancer. Building on literature that explored the functionality of online spaces for health-related social support, we propose a typology that situates this type of support in an SNS-based open cancer community based on the type (informational or emotional) and the direction (expression or reception) of support. A content analysis applied the typology to a 2-year span of Twitter messages using the popular hashtag "#stupidcancer." Given that emotions form the basis for much of human communication and behavior, including aspects of social support, this content analysis also examined the relationship between emotional expression and online social support in tweets about cancer. Furthermore, this study looked at the various ways in which Twitter allows for message sharing across a user's entire network (not just among the cancer community). This work thus begins to lay the conceptual and empirical groundwork for future research testing the effects of various types of social support in open, interactive online cancer communities.

The social determinants of oral health: new approaches to conceptualizing and researching complex causal networks.

PubMed

Newton, J Timothy; Bower, Elizabeth J

2005-02-01

Oral epidemiological research into the social determinants of oral health has been limited by the absence of a theoretical framework which reflects the complexity of real life social processes and the network of causal pathways between social structure and oral health and disease. In the absence of such a framework, social determinants are treated as isolated risk factors, attributable to the individual, having a direct impact on oral health. There is little sense of how such factors interrelate over time and place and the pathways between the factors and oral health. Features of social life which impact on individuals' oral health but are not reducible to the individual remain under-researched. A conceptual framework informing mainstream epidemiological research into the social determinants of health is applied to oral epidemiology. The framework suggests complex causal pathways between social structure and health via interlinking material, psychosocial and behavioural pathways. Methodological implications for oral epidemiological research informed by the framework, such as the use of multilevel modelling, path analysis and structural equation modelling, combining qualitative and quantitative research methods, and collaborative research, are discussed. Copyright Blackwell Munksgaard, 2005.

A Social Network Family-Focused Intervention to Promote Smoking Cessation in Chinese and Vietnamese American Male Smokers: A Feasibility Study

PubMed Central

Burke, Nancy J.; Gildengorin, Ginny; Wong, Ching; Le, Khanh; Nguyen, Anthony; Chan, Joanne L.; Sun, Angela; McPhee, Stephen J.; Nguyen, Tung T.

2015-01-01

Introduction: Smoking prevalence is high among limited English-proficient Chinese and Vietnamese American men, who are frequently unmotivated to quit and who underutilize smoking cessation resources. This study applied lay health worker outreach to leverage peer and family networks to promote smoking cessation among these men. Methods: We integrated qualitative formative research findings and Social Network Theory to develop a social-network family-focused intervention. In a pilot single-group trial, 15 lay health workers recruited 96 dyads (N = 192, 75% Vietnamese) of Chinese or Vietnamese male daily smokers and their family members and delivered the intervention consisting of two small group education sessions and two individual telephone calls over 2 months. Results: At baseline, 42% of smokers were at precontemplation. At 3 months following the initiation of the intervention, 7-day and 30-day point prevalence smoking abstinence rates as reported by smokers and independently corroborated by family members were 30% and 24%, respectively. Utilization of smoking cessation resources (medication, quitline, physician’s advice) increased from 2% to 60% (P < .001). Findings showed high acceptability of the intervention as it facilitated learning about tobacco-related health risks and cessation resources, and communications between smokers and their families. Conclusions: This novel social network family-focused intervention to promote smoking cessation among Chinese and Vietnamese smokers appears to be acceptable, feasible, and potentially efficacious. Findings warrant evaluation of long-term efficacy of the intervention in a larger scale randomized controlled trial. PMID:26180229

Dopamine in the medial amygdala network mediates human bonding

PubMed Central

Touroutoglou, Alexandra; Rudy, Tali; Salcedo, Stephanie; Feldman, Ruth; Hooker, Jacob M.; Dickerson, Bradford C.; Catana, Ciprian; Barrett, Lisa Feldman

2017-01-01

Research in humans and nonhuman animals indicates that social affiliation, and particularly maternal bonding, depends on reward circuitry. Although numerous mechanistic studies in rodents demonstrated that maternal bonding depends on striatal dopamine transmission, the neurochemistry supporting maternal behavior in humans has not been described so far. In this study, we tested the role of central dopamine in human bonding. We applied a combined functional MRI-PET scanner to simultaneously probe mothers’ dopamine responses to their infants and the connectivity between the nucleus accumbens (NAcc), the amygdala, and the medial prefrontal cortex (mPFC), which form an intrinsic network (referred to as the “medial amygdala network”) that supports social functioning. We also measured the mothers’ behavioral synchrony with their infants and plasma oxytocin. The results of this study suggest that synchronous maternal behavior is associated with increased dopamine responses to the mother’s infant and stronger intrinsic connectivity within the medial amygdala network. Moreover, stronger network connectivity is associated with increased dopamine responses within the network and decreased plasma oxytocin. Together, these data indicate that dopamine is involved in human bonding. Compared with other mammals, humans have an unusually complex social life. The complexity of human bonding cannot be fully captured in nonhuman animal models, particularly in pathological bonding, such as that in autistic spectrum disorder or postpartum depression. Thus, investigations of the neurochemistry of social bonding in humans, for which this study provides initial evidence, are warranted. PMID:28193868

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.

Tripartite community structure in social bookmarking data

NASA Astrophysics Data System (ADS)

Neubauer, Nicolas; Obermayer, Klaus

2011-12-01

Community detection is a branch of network analysis concerned with identifying strongly connected subnetworks. Social bookmarking sites aggregate datasets of often hundreds of millions of triples (document, user, and tag), which, when interpreted as edges of a graph, give rise to special networks called 3-partite, 3-uniform hypergraphs. We identify challenges and opportunities of generalizing community detection and in particular modularity optimization to these structures. Two methods for community detection are introduced that preserve the hypergraph's special structure to different degrees. Their performance is compared on synthetic datasets, showing the benefits of structure preservation. Furthermore, a tool for interactive exploration of the community detection results is introduced and applied to examples from real datasets. We find additional evidence for the importance of structure preservation and, more generally, demonstrate how tripartite community detection can help understand the structure of social bookmarking data.

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

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.

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.

Emergence of criticality in the transportation passenger flow: scaling and renormalization in the Seoul bus system.

PubMed

Goh, Segun; Lee, Keumsook; Choi, Moo Young; Fortin, Jean-Yves

2014-01-01

Social systems have recently attracted much attention, with attempts to understand social behavior with the aid of statistical mechanics applied to complex systems. Collective properties of such systems emerge from couplings between components, for example, individual persons, transportation nodes such as airports or subway stations, and administrative districts. Among various collective properties, criticality is known as a characteristic property of a complex system, which helps the systems to respond flexibly to external perturbations. This work considers the criticality of the urban transportation system entailed in the massive smart card data on the Seoul transportation network. Analyzing the passenger flow on the Seoul bus system during one week, we find explicit power-law correlations in the system, that is, power-law behavior of the strength correlation function of bus stops and verify scale invariance of the strength fluctuations. Such criticality is probed by means of the scaling and renormalization analysis of the modified gravity model applied to the system. Here a group of nearby (bare) bus stops are transformed into a (renormalized) "block stop" and the scaling relations of the network density turn out to be closely related to the fractal dimensions of the system, revealing the underlying structure. Specifically, the resulting renormalized values of the gravity exponent and of the Hill coefficient give a good description of the Seoul bus system: The former measures the characteristic dimensionality of the network whereas the latter reflects the coupling between distinct transportation modes. It is thus demonstrated that such ideas of physics as scaling and renormalization can be applied successfully to social phenomena exemplified by the passenger flow.

Emergence of Criticality in the Transportation Passenger Flow: Scaling and Renormalization in the Seoul Bus System

PubMed Central

Goh, Segun; Lee, Keumsook; Choi, MooYoung; Fortin, Jean-Yves

2014-01-01

Social systems have recently attracted much attention, with attempts to understand social behavior with the aid of statistical mechanics applied to complex systems. Collective properties of such systems emerge from couplings between components, for example, individual persons, transportation nodes such as airports or subway stations, and administrative districts. Among various collective properties, criticality is known as a characteristic property of a complex system, which helps the systems to respond flexibly to external perturbations. This work considers the criticality of the urban transportation system entailed in the massive smart card data on the Seoul transportation network. Analyzing the passenger flow on the Seoul bus system during one week, we find explicit power-law correlations in the system, that is, power-law behavior of the strength correlation function of bus stops and verify scale invariance of the strength fluctuations. Such criticality is probed by means of the scaling and renormalization analysis of the modified gravity model applied to the system. Here a group of nearby (bare) bus stops are transformed into a (renormalized) “block stop” and the scaling relations of the network density turn out to be closely related to the fractal dimensions of the system, revealing the underlying structure. Specifically, the resulting renormalized values of the gravity exponent and of the Hill coefficient give a good description of the Seoul bus system: The former measures the characteristic dimensionality of the network whereas the latter reflects the coupling between distinct transportation modes. It is thus demonstrated that such ideas of physics as scaling and renormalization can be applied successfully to social phenomena exemplified by the passenger flow. PMID:24599221

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

Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling.

PubMed

Hermans, Frans; Sartas, Murat; van Schagen, Boudy; van Asten, Piet; Schut, Marc

2017-01-01

Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their 'capacity to innovate' and contribute to the 'scaling of innovations'. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts.

Early Childhood Years: The Social and Cognitive Realms.

ERIC Educational Resources Information Center

DeFord, LouAnn; And Others

1994-01-01

Six brief articles by elementary school teachers in Foxfire's East Tennessee Teachers' Network focus on applying Foxfire core practices in a developmentally appropriate manner in grades K-3, and describe kindergarten journals, student decision making, and projects involving local history and garbage recycling. (SV)

The physics of teams: Interdependence, measurable entropy and computational emotion

NASA Astrophysics Data System (ADS)

Lawless, William F.

2017-08-01

Most of the social sciences, including psychology, economics and subjective social network theory, are modeled on the individual, leaving the field not only a-theoretical, but also inapplicable to a physics of hybrid teams, where hybrid refers to arbitrarily combining humans, machines and robots into a team to perform a dedicated mission (e.g., military, business, entertainment) or to solve a targeted problem (e.g., with scientists, engineers, entrepreneurs). As a common social science practice, the ingredient at the heart of the social interaction, interdependence, is statistically removed prior to the replication of social experiments; but, as an analogy, statistically removing social interdependence to better study the individual is like statistically removing quantum effects as a complication to the study of the atom. Further, in applications of Shannon’s information theory to teams, the effects of interdependence are minimized, but even there, interdependence is how classical information is transmitted. Consequently, numerous mistakes are made when applying non-interdependent models to policies, the law and regulations, impeding social welfare by failing to exploit the power of social interdependence. For example, adding redundancy to human teams is thought by subjective social network theorists to improve the efficiency of a network, easily contradicted by our finding that redundancy is strongly associated with corruption in non-free markets. Thus, built atop the individual, most of the social sciences, economics and social network theory have little if anything to contribute to the engineering of hybrid teams. In defense of the social sciences, the mathematical physics of interdependence is elusive, non-intuitive and non-rational. However, by replacing determinism with bistable states, interdependence at the social level mirrors entanglement at the quantum level, suggesting the applicability of quantum tools for social science. We report how our quantum-like models capture some of the essential aspects of interdependence, a tool for the metrics of hybrid teams; as an example, we find additional support for our model of the solution to the open problem of team size. We also report on progress with the theory of computational emotion for hybrid teams, linking it qualitatively to the second law of thermodynamics. We conclude that the science of interdependence

Applying social network analysis to the examination of interruptions in healthcare.

PubMed

McCurdie, Tara; Sanderson, Penelope; Aitken, Leanne M

2018-02-01

Examinations of interruptions in healthcare often focus on a single clinical discipline, and solutions are targeted accordingly. This approach does not take into account the inter-disciplinary dependencies and other sociotechnical aspects that make up the healthcare work system, and suggested solutions may not meet the needs of all stakeholders. In this article a sociotechnical systems perspective is used to uncover the interdependencies between 16 unique work roles that result in interruptions in an intensive care unit (ICU). By applying social network analysis techniques to data collected using the Dual Perspectives Method, we identified targeted systems-based interventions that may reduce unnecessary interruptions while avoiding unintended consequences that impose additional burden on ICU staff. The rich insights gained into the interruptive communication patterns in the ICU work system stand in contrast to findings that would have otherwise been obtained by focusing only on a single clinical discipline or a single perspective. Copyright © 2017. Published by Elsevier Ltd.

Mapping and discrimination of networks in the complexity-entropy plane

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis. Here we explore the possibility to classify complex networks by means of a statistical complexity measure that has formerly been successfully applied to distinguish different types of chaotic and stochastic time series. It is composed of a network's averaged per-node entropic measure characterizing the network's information content and the associated Jenson-Shannon divergence as a measure of disequilibrium. We study 29 real-world networks and show that networks of the same category tend to cluster in distinct areas of the resulting complexity-entropy plane. We demonstrate that within our framework, connectome networks exhibit among the highest complexity while, e.g., transportation and infrastructure networks display significantly lower values. Furthermore, we demonstrate the utility of our framework by applying it to families of random scale-free and Watts-Strogatz model networks. We then show in a second application that the proposed framework is useful to objectively construct threshold-based networks, such as functional climate networks or recurrence networks, by choosing the threshold such that the statistical network complexity is maximized.

Human Rights Event Detection from Heterogeneous Social Media Graphs.

PubMed

Chen, Feng; Neill, Daniel B

2015-03-01

Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions.

Using attractiveness model for actors ranking in social media networks.

PubMed

Qasem, Ziyaad; Jansen, Marc; Hecking, Tobias; Hoppe, H Ulrich

2017-01-01

Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc. This work aims to extend our formally defined T measure to present a new measure aiming to recognize the actor's influence by the strength of attracting new important actors into a networked community. Therefore, we propose a model of the actor's influence based on the attractiveness of the actor in relation to the number of other attractors with whom he/she has established connections over time. Using an empirically collected social network for the underlying graph, we have applied the above-mentioned measure of influence in order to determine optimal seeds in a simulation of influence maximization. We study our extended measure in the context of information diffusion because this measure is based on a model of actors who attract others to be active members in a community. This corresponds to the idea of the IC simulation model which is used to identify the most important spreaders in a set of actors.

Role of Social Knowledge Networking technology in facilitating meaningful use of Electronic Health Record medication reconciliation.

PubMed

Rangachari, Pavani

2016-06-01

Despite the federal policy impetus towards EHR Medication Reconciliation, hospital adherence has lagged for one chief reason; low physician engagement, which in turn emanates from lack of consensus in regard to which physician is responsible for managing a patient's medication list, and the importance of medication reconciliation as a tool for improving patient safety and quality of care. The Technology-in-Practice (TIP) framework stresses the role of human action in enacting structures of technology use or "technologies-in-practice." Applying the TIP framework to the EHR Medication Reconciliation context, helps frame the problem as one of low physician engagement in performing EHR Medication Reconciliation, translating to limited-use-EHR-in-practice. Concurrently, the problem suggests a hierarchical network structure, reflecting limited communication among hospital administrators and clinical providers on the importance of EHR Medication Reconciliation in improving patient safety. Integrating the TIP literature with the more recent knowledge-in-Practice (KIP) literature suggests that EHR-in-practice could be transformed from "limited use" to "meaningful use" through the use of Social Knowledge Networking (SKN) Technology to create new social network structures, and enable engagement, learning, and practice change. Correspondingly, the objectives of this paper are to: 1) Conduct a narrative review of the literature on "technology use," to understand how technologies-in-practice may be transformed from limited use to meaningful use; 2) Conduct a narrative review of the literature on "organizational change implementation," to understand how changes in technology use could be successfully implemented and sustained in a healthcare organizational context; and 3) Apply lessons learned from the narrative literature reviews to identify strategies for the meaningful use and successful implementation of EHR Medication Reconciliation technology.

A multilevel cross-lagged structural equation analysis for reciprocal relationship between social capital and health.

PubMed

Yu, Ge; Sessions, John G; Fu, Yu; Wall, Martin

2015-10-01

We investigated the reciprocal relationship between individual social capital and perceived mental and physical health in the UK. Using data from the British Household Panel Survey from 1991 to 2008, we fitted cross-lagged structural equation models that include three indicators of social capital vis. social participation, social network, and loneliness. Given that multiple measurement points (level 1) are nested within individuals (level 2), we also applied a multilevel model to allow for residual variation in the outcomes at the occasion and individual levels. Controlling for gender, age, employment status, educational attainment, marital status, household wealth, and region, our analyses suggest that social participation predicts subsequent change in perceived mental health, and vice versa. However, whilst loneliness is found to be significantly related to perceived mental and physical health, reciprocal causality is not found for perceived mental health. Furthermore, we find evidence for reverse effects with both perceived mental and physical health appearing to be the dominant causal factor with respect to the prospective level of social network. Our findings thus shed further light on the importance of social participation and social inclusion in health promotion and aid the development of more effective public health policies in the UK. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Resilience of natural gas networks during conflicts, crises and disruptions.

PubMed

Carvalho, Rui; Buzna, Lubos; Bono, Flavio; Masera, Marcelo; Arrowsmith, David K; Helbing, Dirk

2014-01-01

Human conflict, geopolitical crises, terrorist attacks, and natural disasters can turn large parts of energy distribution networks offline. Europe's current gas supply network is largely dependent on deliveries from Russia and North Africa, creating vulnerabilities to social and political instabilities. During crises, less delivery may mean greater congestion, as the pipeline network is used in ways it has not been designed for. Given the importance of the security of natural gas supply, we develop a model to handle network congestion on various geographical scales. We offer a resilient response strategy to energy shortages and quantify its effectiveness for a variety of relevant scenarios. In essence, Europe's gas supply can be made robust even to major supply disruptions, if a fair distribution strategy is applied.

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

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

Soundarajan, Sucheta; Wendt, Jeremy D.

2016-06-01

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to bemore » found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.« less

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

Social Media and Mentoring in Biomedical Research Faculty Development.

PubMed

Teruya, Stacey Alan; Bazargan-Hejazi, Shahrzad

2014-09-01

To determine how effective and collegial mentoring in biomedical research faculty development may be implemented and facilitated through social media. The authors reviewed the literature for objectives, concerns, and limitations of career development for junior research faculty. They tabularized these as developmental goals, and aligned them with relevant social media strengths and capabilities facilitated through traditional and/or peer mentoring. The authors derived a model in which social media is leveraged to achieve developmental goals reflected in independent and shared projects, and in the creation and expansion of support and research networks. Social media may be successfully leveraged and applied in achieving developmental goals for biomedical research faculty, and potentially for those in other fields and disciplines.

[Using web 2.0 technologies and social media for the nephrologist].

PubMed

Santoro, Eugenio; Quintaliani, Giuseppe

2013-01-01

New media tools such as web 2.0 are increasingly being used in the medical field. RSS feeds, podcasts, blogs, wikis, online social networks and social media have all been proposed as innovative tools for the education and updating of clinicians, nurses, other health workers and medical students because of their ease of access and widespread use. Nephrology is one of the medical fields where these technologies have been successfully applied. Medical journals such as the American Journal Kidney Diseases and the Journal of the American Society of Nephrology, and medical societies such as the American Society of Nephrology, are all using these new and powerful communication tools. In addition, blogs and social networks have been developed to allow physicians to distribute, share and comment medical material concerning issues related to nephrology and kidney disease, including images, videos, slides, scientific abstracts and clinical trials updates. This review provides background information on the evolution of both web 2.0 and the social media and describes some of the most interesting applications of web 2.0 and its correlated tools in the field of nephrology.

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.

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)

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…

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.

Social network analysis: Presenting an underused method for nursing research.

PubMed

Parnell, James Michael; Robinson, Jennifer C

2018-06-01

This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.

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.

Coevolution of Epidemics, Social Networks, and Individual Behavior: A Case Study

NASA Astrophysics Data System (ADS)

Chen, Jiangzhuo; Marathe, Achla; Marathe, Madhav

This research shows how a limited supply of antivirals can be distributed optimally between the hospitals and the market so that the attack rate is minimized and enough revenue is generated to recover the cost of the antivirals. Results using an individual based model find that prevalence elastic demand behavior delays the epidemic and change in the social contact network induced by isolation reduces the peak of the epidemic significantly. A microeconomic analysis methodology combining behavioral economics and agent-based simulation is a major contribution of this work. In this paper we apply this methodology to analyze the fairness of the stockpile distribution, and the response of human behavior to disease prevalence level and its interaction with the market.

Are Social Networking Sites Making Health Behavior Change Interventions More Effective? A Meta-Analytic Review.

PubMed

Yang, Qinghua

2017-03-01

The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen's d ranging from -1.17 to 1.28. To provide a better understanding of SNS-based interventions' effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.

Mental illness disclosure in Chinese immigrant communities

PubMed Central

Chen, Fang-pei; Ying-Chi Lai, Grace; Yang, Lawrence

2014-01-01

Support from social networks is imperative to mental health recovery of persons with mental illness. However, disclosing mental illness may damage a person’s participation in networks due to mental illness stigma, especially in Chinese-immigrant communities where social networks (the guanxi network) has specific social-cultural significance. This study focused on mental illness disclosure in Chinese-immigrant communities in New York City. Fifty-three Chinese psychiatric patients were recruited consecutively from two Chinese bilingual psychiatric inpatient units from 2006 to 2010. Two bilingual psychologists interviewed each participant once in a semi-structured interview, including 6 questions on mental illness disclosure. Conventional content analysis was applied to conceptualize the phenomenon. Results showed that participants voluntarily disclosed to a circle of people composed primarily of family and relatives. The decisions and strategies to disclose depended on participants’ consideration of three critical elements of social relationships. Ganqing, affection associated with relationship-building, ultimately determined who had the privilege to know. Renqing, the moral code of reciprocal kindness, further influenced disclosure decisions and what participants anticipated as responses to disclosure. Lastly, concerns over preserving face (lian), a construct representing personal and familial dignity, oftentimes prohibited disclosure. Additionally, in this tight-knit network involuntary disclosure could happen without participants’ permission or knowledge. Participants commonly suffered from stigma after disclosure. However, half of our participants reported situations where they experienced little discriminatory treatment and some experienced support and care as a result of cultural dynamics. Recommendations for culturally sensitive practice to facilitate mental illness disclosure among Chinese immigrants were discussed. PMID:23647389

Mental illness disclosure in Chinese immigrant communities.

PubMed

Chen, Fang-Pei; Lai, Grace Ying-Chi; Yang, Lawrence

2013-07-01

Support from social networks is imperative to mental health recovery of persons with mental illness. However, disclosing mental illness may damage a person's participation in networks due to mental illness stigma, especially in Chinese immigrant communities where social networks (the guanxi network) have specific social-cultural significance. This study focused on mental illness disclosure in Chinese immigrant communities in New York City. Fifty-three Chinese psychiatric patients were recruited consecutively from 2 Chinese bilingual psychiatric inpatient units from 2006 to 2010. Two bilingual psychologists interviewed each participant once in a semistructured interview, including 6 questions on mental illness disclosure. Conventional content analysis was applied to conceptualize the phenomenon. Results showed that participants voluntarily disclosed to a circle of people composed primarily of family and relatives. The decisions and strategies to disclose depended on participants' consideration of 3 critical elements of social relationships. Ganqing, affection associated with relationship building, ultimately determined who had the privilege to know. Renqing, the moral code of reciprocal kindness, further influenced disclosure decisions and what participants anticipated as responses to disclosure. Lastly, concerns over preserving face (lian), a construct representing personal and familial dignity, oftentimes prohibited disclosure. Additionally, in this tight-knit network, involuntary disclosure could happen without participants' permission or knowledge. Participants commonly suffered from stigma after disclosure. However, half of our participants reported situations in which they experienced little discriminatory treatment, and some experienced support and care as a result of cultural dynamics. Recommendations for culturally sensitive practice to facilitate mental illness disclosure among Chinese immigrants were discussed. PsycINFO Database Record (c) 2013 APA, 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.

Social Networks and Participation with Others for Youth with Learning, Attention and Autism Spectrum Disorders

PubMed Central

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

2015-01-01

Background Social participation involves activities and roles providing interactions with others, including those within their social networks. Purpose Characterize social networks and participation with others for 36 adolescents, ages 11-16 years, with (n = 19) and without (n = 17) learning disability, attention disorder or high-functioning autism. Methods Social networks were measured using methods of personal network analysis. The Children's Assessment of Participation and Enjoyment With Whom dimension scores was used to measure participation with others. Youth from the clinical group were interviewed regarding their experiences within their social networks. Findings Group differences were observed for six social network variables and in the proportion of overall, physical, recreational, social and informal activities engaged with family and/or friends. Qualitative findings explicated strategies used in building, shaping and maintaining their social networks. Implications Social network factors should be considered when seeking to understand social participation. PMID:26755040

Bridging gaps to promote networked care between teams and groups in health delivery systems: a systematic review of non-health literature

PubMed Central

Braithwaite, Jeffrey

2015-01-01

Objectives To assess non-health literature, identify key strategies in promoting more networked teams and groups, apply external ideas to healthcare, and build a model based on these strategies. Design A systematic review of the literature outside of healthcare. Method Searches guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of ABI/INFORM Global, CINAHL, IBSS, MEDLINE and Psychinfo databases following a mind-mapping exercise generating key terms centred on the core construct of gaps across organisational social structures that uncovered 842 empirical articles of which 116 met the inclusion criteria. Data extraction and content analysis via data mining techniques were performed on these articles. Results The research involved subjects in 40 countries, with 32 studies enrolling participants in multiple countries. There were 40 studies conducted wholly or partly in the USA, 46 wholly or partly in continental Europe, 29 wholly or partly in Asia and 12 wholly or partly in Russia or Russian federated countries. Methods employed included 30 mixed or triangulated social science study designs, 39 qualitative studies, 13 experimental studies and 34 questionnaire-based studies, where the latter was mostly to gather data for social network analyses. Four recurring factors underpin a model for promoting networked behaviours and fortifying cross-group cooperation: appreciating the characteristics and nature of gaps between groups; using the leverage of boundary-spanners to bridge two or more groups; applying various mechanisms to stimulate interactive relationships; and mobilising those who can exert positive external influences to promote connections while minimising the impact of those who exacerbate divides. Conclusions The literature assessed is rich and varied. An evidence-oriented model and strategies for promoting more networked systems are now available for application to healthcare. While caution needs to be exercised in translating outside ideas and studies, drawing on non-health ideas is useful in providing insights into other sectors. PMID:26408280

Using social network analysis to inform disease control interventions.

PubMed

Marquetoux, Nelly; Stevenson, Mark A; Wilson, Peter; Ridler, Anne; Heuer, Cord

2016-04-01

Contact patterns between individuals are an important determinant for the spread of infectious diseases in populations. Social network analysis (SNA) describes contact patterns and thus indicates how infectious pathogens may be transmitted. Here we explore network characteristics that may inform the development of disease control programes. This study applies SNA methods to describe a livestock movement network of 180 farms in New Zealand from 2006 to 2010. We found that the number of contacts was overall consistent from year to year, while the choice of trading partners tended to vary. This livestock movement network illustrated how a small number of farms central to the network could play a potentially dominant role for the spread of infection in this population. However, fragmentation of the network could easily be achieved by "removing" a small proportion of farms serving as bridges between otherwise isolated clusters, thus decreasing the probability of large epidemics. This is the first example of a comprehensive analysis of pastoral livestock movements in New Zealand. We conclude that, for our system, recording and exploiting livestock movements can contribute towards risk-based control strategies to prevent and monitor the introduction and the spread of infectious diseases in animal populations. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparative analysis of the effectiveness of three immunization strategies in controlling disease outbreaks in realistic social networks.

PubMed

Xu, Zhijing; Zu, Zhenghu; Zheng, Tao; Zhang, Wendou; Xu, Qing; Liu, Jinjie

2014-01-01

The high incidence of emerging infectious diseases has highlighted the importance of effective immunization strategies, especially the stochastic algorithms based on local available network information. Present stochastic strategies are mainly evaluated based on classical network models, such as scale-free networks and small-world networks, and thus are insufficient. Three frequently referred stochastic immunization strategies-acquaintance immunization, community-bridge immunization, and ring vaccination-were analyzed in this work. The optimal immunization ratios for acquaintance immunization and community-bridge immunization strategies were investigated, and the effectiveness of these three strategies in controlling the spreading of epidemics were analyzed based on realistic social contact networks. The results show all the strategies have decreased the coverage of the epidemics compared to baseline scenario (no control measures). However the effectiveness of acquaintance immunization and community-bridge immunization are very limited, with acquaintance immunization slightly outperforming community-bridge immunization. Ring vaccination significantly outperforms acquaintance immunization and community-bridge immunization, and the sensitivity analysis shows it could be applied to controlling the epidemics with a wide infectivity spectrum. The effectiveness of several classical stochastic immunization strategies was evaluated based on realistic contact networks for the first time in this study. These results could have important significance for epidemic control research and practice.

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.

Generalised power graph compression reveals dominant relationship patterns in complex networks

PubMed Central

Ahnert, Sebastian E.

2014-01-01

We introduce a framework for the discovery of dominant relationship patterns in complex networks, by compressing the networks into power graphs with overlapping power nodes. When paired with enrichment analysis of node classification terms, the most compressible sets of edges provide a highly informative sketch of the dominant relationship patterns that define the network. In addition, this procedure also gives rise to a novel, link-based definition of overlapping node communities in which nodes are defined by their relationships with sets of other nodes, rather than through connections within the community. We show that this completely general approach can be applied to undirected, directed, and bipartite networks, yielding valuable insights into the large-scale structure of real-world networks, including social networks and food webs. Our approach therefore provides a novel way in which network architecture can be studied, defined and classified. PMID:24663099

Enhancing (In)Formal Learning Ties in Interdisciplinary Management Courses: A Quasi-Experimental Social Network Study

ERIC Educational Resources Information Center

Rienties, Bart; Héliot, YingFei

2018-01-01

While interdisciplinary courses are regarded as a promising method for students to learn and apply knowledge from other disciplines, there is limited empirical evidence available whether interdisciplinary courses can effectively "create" interdisciplinary students. In this innovative quasi-experimental study amongst 377 Master's…

Knowledge Management in Higher Education in Thailand

ERIC Educational Resources Information Center

Chumjit, Surat

2012-01-01

This study examines how knowledge management (KM) is applied to higher education in Thailand, and it will also examine whether higher education in Thailand is ready to combine KM with their educational missions in terms of teaching, research, administration, and strategic planning. Knowledge creation and social networking frameworks are used to…

Social networks, social support and psychiatric symptoms: social determinants and associations within a multicultural community population.

PubMed

Smyth, Natasha; Siriwardhana, Chesmal; Hotopf, Matthew; Hatch, Stephani L

2015-07-01

Little is known about how social networks and social support are distributed within diverse communities and how different types of each are associated with a range of psychiatric symptoms. This study aims to address such shortcomings by: (1) describing the demographic and socioeconomic characteristics of social networks and social support in a multicultural population and (2) examining how each is associated with multiple mental health outcomes. Data is drawn from the South East London Community Health Study; a cross-sectional study of 1,698 adults conducted between 2008 and 2010. The findings demonstrate variation in social networks and social support by socio-demographic factors. Ethnic minority groups reported larger family networks but less perceived instrumental support. Older individuals and migrant groups reported lower levels of particular network and support types. Individuals from lower socioeconomic groups tended to report less social networks and support across the indicators measured. Perceived emotional and instrumental support, family and friend network size emerged as protective factors for common mental disorder, personality dysfunction and psychotic experiences. In contrast, both social networks and social support appear less relevant for hazardous alcohol use. The findings both confirm established knowledge that social networks and social support exert differential effects on mental health and furthermore suggest that the particular type of social support may be important. In contrast, different types of social network appear to impact upon poor mental health in a more uniform way. Future psychosocial strategies promoting mental health should consider which social groups are vulnerable to reduced social networks and poor social support and which diagnostic groups may benefit most.

Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

ERIC Educational Resources Information Center

Baker-Doyle, Kira J.

2015-01-01

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Identifying influencers from sampled social networks

NASA Astrophysics Data System (ADS)

Tsugawa, Sho; Kimura, Kazuma

2018-10-01

Identifying influencers who can spread information to many other individuals from a social network is a fundamental research task in the network science research field. Several measures for identifying influencers have been proposed, and the effectiveness of these influence measures has been evaluated for the case where the complete social network structure is known. However, it is difficult in practice to obtain the complete structure of a social network because of missing data, false data, or node/link sampling from the social network. In this paper, we investigate the effects of node sampling from a social network on the effectiveness of influence measures at identifying influencers. Our experimental results show that the negative effect of biased sampling, such as sample edge count, on the identification of influencers is generally small. For social media networks, we can identify influencers whose influence is comparable with that of those identified from the complete social networks by sampling only 10%-30% of the networks. Moreover, our results also suggest the possible benefit of network sampling in the identification of influencers. Our results show that, for some networks, nodes with higher influence can be discovered from sampled social networks than from complete social networks.

Social media users have different experiences, motivations, and quality of life.

PubMed

Campisi, Jay; Folan, Denis; Diehl, Grace; Kable, Timothy; Rademeyer, Candice

2015-08-30

While the number of individuals participating in internet-based social networks has continued to rise, it is unclear how participating in social networks might influence quality of life (QOL). Individuals differ in their experiences, motivations for, and amount of time using internet-based social networks, therefore, we examined if individuals differing in social network user experiences, motivations and frequency of social network also differed in self-reported QOL. Two-hundred and thirty-seven individuals (aged 18-65) were recruited online using the online platform Mechanical Turk (MTurk). All participants completed a web-based survey examining social network use and the World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-Bref) to assess QOL. Individuals who reported positive associations with the use of social networks demonstrated higher QOL while those reporting negative associates demonstrated lower QOL. Moreover, individuals using social networks to stay connected to friends demonstrated higher QOL while those using social networking for dating purposes reported lower QOL. Frequency of social network use did not relate to QOL. These results suggest that QOL differs among social network users. Thus, participating in social networking may be a way to either promote or detract from QOL. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Confidant Network Types and Well-Being Among Older Europeans

PubMed Central

Litwin, Howard; Stoeckel, Kimberly J.

2014-01-01

Purpose of the Study: To derive a typology of confidant networks among older adults in Europe and to examine them in relation to country differences and well-being (CASP-12). Design and Methods: The study population was composed of persons aged 65 and older in 16 countries from the 4th wave of the Survey of Health, Ageing and Retirement in Europe (N = 28,697). K-means cluster analysis was applied to data from a newly implemented name-generating network inventory. CASP-12 scores were regressed on network type controlling for country and potential sociodemographic and health confounders. Results: Six prototypical confidant network types were discerned, including proximal and distal family-based networks of varying configurations, as well as friend-based and other-based network types. Regional country differences in network type constellations were observed. Better well-being was found to be associated with network types with greater social capital. Respondents with no named confidants had the lowest CASP-12 scores, and those embedded in “other” network types also exhibited a negative association with well-being. Implications: The study demonstrates the utility of name-generating network inventories in understanding the social capital of older persons. It also shows that accessible family ties are strong correlates of well-being in this population. Finally, it documents the importance of improving the means to detect the small but significant subgroup of isolated older people—those who have no confidants on whom they may rely. PMID:23749390

The Analysis of Duocentric Social Networks: A Primer.

PubMed

Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

2015-02-01

Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

Support and Social Contact as a Decisive Meta-Variable in Morbidity and Social Welfare of the Older Person.

PubMed

Rondon Garcia, Luis Miguel; Aguirre Arizala, Blanca Aranzazu; Garcia Garcia, Francisco Jose; Gallego, Carmen Castillo

2017-01-01

Bacground: This article tackles social support as a meta-variable that is reinforced by a set of social variables, which correlate and act as predictors of social welfare and life quality of the older person. The objective of the study is to know how social support, networks and social contacts can influence the health of the elderly person, especially if these are interrelated factors. The population studied are individuals from both sexes living in Toledo (Spanish people) and who were 65 years of age or over. Several scales were applied to assess the frequency of and the degree of satisfaction with perceived social support received from different sources in relation to social support. The co relational analysis showed significant positive associations between scores and measures of and social support, social relations, contact and social networks. We conclude that the support in general is very good, over 90% of people from the sample have someone who would help if needed. Social and health factors are interrelated with social support. Social contact can also be considered as a life quality estimate. He progressive loss of contact over the years is a social factor that affects the quality of life. The meta-analysis we find that social support and the emotional factor, along with social interactions, have powerful effects on preventing morbidity and mortality, which are important social indicators. We conclude that social support based on positive social interactions provides an optimal state of health in the older person. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

eHealth promotion and social innovation with youth: using social and visual media to engage diverse communities.

PubMed

Norman, Cameron D; Yip, Andrea L

2012-01-01

Social media and the multimedia networks that they support provide a platform for engaging youth and young adults across diverse contexts in a manner that supports different forms of creative expression. Drawing on more than 15 years of experience using eHealth promotion strategies to youth engagement, the Youth Voices Research Group (YVRG) and its partners have created novel opportunities for young people to explore health topics ranging from tobacco use, food security, mental health, to navigation of health services. Through applying systems and design thinking, the YVRG approach to engaging youth will be presented using examples from its research and practice that combine social organizing with arts-informed methods for creative expression using information technology. This presentation focuses on the way in which the YVRG has introduced interactive blogging, photographic elicitation, and video documentaries, alongside real-world social action projects, to promote youth health and to assist in research and evaluation. Opportunities and barriers including literacy and access to technology are discussed and presented along with emerging areas of research including more effective use of smartphones and social networking platforms such as Twitter, Facebook, and YouTube in health promotion and public health.

Pairing Increases Activation of V1aR, but not OTR, in Auditory Regions of Zebra Finches: The Importance of Signal Modality in Nonapeptide-Social Behavior Relationships.

PubMed

Tomaszycki, Michelle L; Atchley, Derek

2017-10-01

Social relationships are complex, involving the production and comprehension of signals, individual recognition, and close coordination of behavior between two or more individuals. The nonapeptides oxytocin and vasopressin are widely believed to regulate social relationships. These findings come largely from prairie voles, in which nonapeptide receptors in olfactory neural circuits drive pair bonding. This research is assumed to apply to all species. Previous reviews have offered two competing hypotheses. The work of Sarah Newman has implicated a common neural network across species, the Social Behavior Network. In contrast, others have suggested that there are signal modality-specific networks that regulate social behavior. Our research focuses on evaluating these two competing hypotheses in the zebra finch, a species that relies heavily on vocal/auditory signals for communication, specifically the neural circuits underlying singing in males and song perception in females. We have demonstrated that the quality of vocal interactions is highly important for the formation of long-term monogamous bonds in zebra finches. Qualitative evidence at first suggests that nonapeptide receptor distributions are very different between monogamous rodents (olfactory species) and monogamous birds (vocal/auditory species). However, we have demonstrated that social bonding behaviors are not only correlated with activation of nonapeptide receptors in vocal and auditory circuits, but also involve regions of the common Social Behavior Network. Here, we show increased Vasopressin 1a receptor, but not oxytocin receptor, activation in two auditory regions following formation of a pair bond. To our knowledge, this is the first study to suggest a role of nonapeptides in the auditory circuit in pair bonding. Thus, we highlight converging mechanisms of social relationships and also point to the importance of studying multiple species to understand mechanisms of behavior. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

A survey of social media data analysis for physical activity surveillance.

PubMed

Liu, Sam; Young, Sean D

2018-07-01

Social media data can provide valuable information regarding people's behaviors and health outcomes. Previous studies have shown that social media data can be extracted to monitor and predict infectious disease outbreaks. These same approaches can be applied to other fields including physical activity research and forensic science. Social media data have the potential to provide real-time monitoring and prediction of physical activity level in a given region. This tool can be valuable to public health organizations as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (e.g. surveys, observational studies). As a result, this tool could help public health organizations better mobilize and target physical activity interventions. The first part of this paper aims to describe current approaches (e.g. topic modeling, sentiment analysis and social network analysis) that could be used to analyze social media data to provide real-time monitoring of physical activity level. The second aim of this paper was to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling

PubMed Central

Hermans, Frans; Sartas, Murat; van Schagen, Boudy; van Asten, Piet

2017-01-01

Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their ‘capacity to innovate’ and contribute to the ‘scaling of innovations’. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts. PMID:28166226

Social inheritance can explain the structure of animal social networks

PubMed Central

Ilany, Amiyaal; Akçay, Erol

2016-01-01

The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

The networked student: A design-based research case study of student constructed personal learning environments in a middle school science course

NASA Astrophysics Data System (ADS)

Drexler, Wendy

This design-based research case study applied a networked learning approach to a seventh grade science class at a public school in the southeastern United States. Students adapted emerging Web applications to construct personal learning environments for in-depth scientific inquiry of poisonous and venomous life forms. The personal learning environments constructed used Application Programming Interface (API) widgets to access, organize, and synthesize content from a number of educational Internet resources and social network connections. This study examined the nature of personal learning environments; the processes students go through during construction, and patterns that emerged. The project was documented from both an instructional and student-design perspective. Findings revealed that students applied the processes of: practicing digital responsibility; practicing digital literacy; organizing content; collaborating and socializing; and synthesizing and creating. These processes informed a model of the networked student that will serve as a framework for future instructional designs. A networked learning approach that incorporates these processes into future designs has implications for student learning, teacher roles, professional development, administrative policies, and delivery. This work is significant in that it shifts the focus from technology innovations based on tools to student empowerment based on the processes required to support learning. It affirms the need for greater attention to digital literacy and responsibility in K12 schools as well as consideration for those skills students will need to achieve success in the 21st century. The design-based research case study provides a set of design principles for teachers to follow when facilitating student construction of personal learning environments.

[Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service].

PubMed

Kim, Minji; Choi, Mona; Youm, Yoosik

2017-12-01

As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies. © 2017 Korean Society of Nursing Science

Establishing the reliability of rhesus macaque social network assessment from video observations

PubMed Central

Feczko, Eric; Mitchell, Thomas A. J.; Walum, Hasse; Brooks, Jenna M.; Heitz, Thomas R.; Young, Larry J.; Parr, Lisa A.

2015-01-01

Understanding the properties of a social environment is important for understanding the dynamics of social relationships. Understanding such dynamics is relevant for multiple fields, ranging from animal behaviour to social and cognitive neuroscience. To quantify social environment properties, recent studies have incorporated social network analysis. Social network analysis quantifies both the global and local properties of a social environment, such as social network efficiency and the roles played by specific individuals, respectively. Despite the plethora of studies incorporating social network analysis, methods to determine the amount of data necessary to derive reliable social networks are still being developed. Determining the amount of data necessary for a reliable network is critical for measuring changes in the social environment, for example following an experimental manipulation, and therefore may be critical for using social network analysis to statistically assess social behaviour. In this paper, we extend methods for measuring error in acquired data and for determining the amount of data necessary to generate reliable social networks. We derived social networks from a group of 10 male rhesus macaques, Macaca mulatta, for three behaviours: spatial proximity, grooming and mounting. Behaviours were coded using a video observation technique, where video cameras recorded the compound where the 10 macaques resided. We collected, coded and used 10 h of video data to construct these networks. Using the methods described here, we found in our data that 1 h of spatial proximity observations produced reliable social networks. However, this may not be true for other studies due to differences in data acquisition. Our results have broad implications for measuring and predicting the amount of error in any social network, regardless of species. PMID:26392632

Dim Networks: The Utility of Social Network Analysis for Illuminating Partner Security Force Networks

DTIC Science & Technology

2015-12-01

use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements...data to improve SC. 14. SUBJECT TERMS social network analysis, dark networks, light networks, dim networks, security cooperation, Southeast Asia...task may already exist. Recently, the use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations

[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.

From Social Integration to Social Isolation: The Relationship Between Social Network Types and Perceived Availability of Social Support in a National Sample of Older Canadians.

PubMed

Harasemiw, Oksana; Newall, Nancy; Shooshtari, Shahin; Mackenzie, Corey; Menec, Verena

2017-01-01

It is well-documented that social isolation is detrimental to health and well-being. What is less clear is what types of social networks allow older adults to get the social support they need to promote health and well-being. In this study, we identified social network types in a national sample of older Canadians and explored whether they are associated with perceived availability of different types of social support (affectionate, emotional, or tangible, and positive social interactions). Data were drawn from the baseline questionnaire of the Canadian Longitudinal Study on Aging for participants aged 65-85 (unweighted n = 8,782). Cluster analyses revealed six social network groups. Social support generally declined as social networks became more restricted; however, different patterns of social support availability emerged for different social network groups. These findings suggest that certain types of social networks place older adults at risk of not having met specific social support needs.

Functional connectivity associated with social networks in older adults: A resting-state fMRI study.

PubMed

Pillemer, Sarah; Holtzer, Roee; Blumen, Helena M

2017-06-01

Poor social networks and decreased levels of social support are associated with worse mood, health, and cognition in younger and older adults. Yet, we know very little about the brain substrates associated with social networks and social support, particularly in older adults. This study examined functional brain substrates associated with social networks using the Social Network Index (SNI) and resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI data from 28 non-demented older adults were analyzed with independent components analyses. As expected, four established resting-state networks-previously linked to motor, vision, speech, and other language functions-correlated with the quality (SNI-1: total number of high-contact roles of a respondent) and quantity (SNI-2: total number of individuals in a respondent's social network) of social networks: a sensorimotor, a visual, a vestibular/insular, and a left frontoparietal network. Moreover, SNI-1 was associated with greater functional connectivity in the lateral prefrontal regions of the left frontoparietal network, while SNI-2 was associated with greater functional connectivity in the medial prefrontal regions of this network. Thus, lateral prefrontal regions may be particularly linked to the quality of social networks while medial prefrontal regions may be particularly linked to the quantity of social networks.

Social Media Use Among Living Kidney Donors and Recipients: Survey on Current Practice and Potential

PubMed Central

2016-01-01

Background In the United States, there is a national shortage of organs donated for transplant. Among the solid organs, most often kidneys are donated by living donors, but the lack of information and complicated processes limit the number of individuals who serve as living kidney donors. Social media can be a tool for advocacy, educating the public about the need, process, and outcomes of live kidney donors, yet little is known about social media use by kidney transplant patients. Objective The purpose of this study was to examine the social media use of potential kidney transplant patients and their willingness to use social media and their networks to advocate and educate about living kidney donation. Methods Using a validated survey, we modified the instrument to apply to the patient population of interest attending the Medical University of South Carolina, Charleston, SC, USA. The questions on the survey inquired about current social media use, sites visited, frequency and duration of social media use, and willingness to use social media to share the need for living kidney donors. We asked patients who had received a transplant and those awaiting a transplant to complete the survey during an office visit. Participation was voluntary. Results A total of 199 patients completed the survey. Approximately half of all kidney transplant patients surveyed used social media (104/199, 52.3%), and approximately one-third (66/199, 33.2%) had more than 100 friends in their social media network. Facebook was the most popular site, and 51% (102/199) reported that they would be willing to post information about living kidney donation on their social networks. More than a quarter of the sample (75/199, 37.7%) had posted about their health status in the past. Conclusions Social media holds great promise for health-related education and awareness. Our study shows the current social media use of kidney transplant patients. In turn, such information can be used to design interventions to ensure appropriate decision making about live kidney donation. Transplant programs can help increase the number of living donors by providing guidance to kidney transplant patients in how to use social media, to be advocates, and to provide information about living kidney donation to their social network. PMID:27998880

Social Media Use Among Living Kidney Donors and Recipients: Survey on Current Practice and Potential.

PubMed

Kazley, Abby Swanson; Hamidi, Bashir; Balliet, Wendy; Baliga, Prabhakar

2016-12-20

In the United States, there is a national shortage of organs donated for transplant. Among the solid organs, most often kidneys are donated by living donors, but the lack of information and complicated processes limit the number of individuals who serve as living kidney donors. Social media can be a tool for advocacy, educating the public about the need, process, and outcomes of live kidney donors, yet little is known about social media use by kidney transplant patients. The purpose of this study was to examine the social media use of potential kidney transplant patients and their willingness to use social media and their networks to advocate and educate about living kidney donation. Using a validated survey, we modified the instrument to apply to the patient population of interest attending the Medical University of South Carolina, Charleston, SC, USA. The questions on the survey inquired about current social media use, sites visited, frequency and duration of social media use, and willingness to use social media to share the need for living kidney donors. We asked patients who had received a transplant and those awaiting a transplant to complete the survey during an office visit. Participation was voluntary. A total of 199 patients completed the survey. Approximately half of all kidney transplant patients surveyed used social media (104/199, 52.3%), and approximately one-third (66/199, 33.2%) had more than 100 friends in their social media network. Facebook was the most popular site, and 51% (102/199) reported that they would be willing to post information about living kidney donation on their social networks. More than a quarter of the sample (75/199, 37.7%) had posted about their health status in the past. Social media holds great promise for health-related education and awareness. Our study shows the current social media use of kidney transplant patients. In turn, such information can be used to design interventions to ensure appropriate decision making about live kidney donation. Transplant programs can help increase the number of living donors by providing guidance to kidney transplant patients in how to use social media, to be advocates, and to provide information about living kidney donation to their social network. ©Abby Swanson Kazley, Bashir Hamidi, Wendy Balliet, Prabhakar Baliga. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.12.2016.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

PubMed

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Resilience of Natural Gas Networks during Conflicts, Crises and Disruptions

PubMed Central

Carvalho, Rui; Buzna, Lubos; Bono, Flavio; Masera, Marcelo; Arrowsmith, David K.; Helbing, Dirk

2014-01-01

Human conflict, geopolitical crises, terrorist attacks, and natural disasters can turn large parts of energy distribution networks offline. Europe's current gas supply network is largely dependent on deliveries from Russia and North Africa, creating vulnerabilities to social and political instabilities. During crises, less delivery may mean greater congestion, as the pipeline network is used in ways it has not been designed for. Given the importance of the security of natural gas supply, we develop a model to handle network congestion on various geographical scales. We offer a resilient response strategy to energy shortages and quantify its effectiveness for a variety of relevant scenarios. In essence, Europe's gas supply can be made robust even to major supply disruptions, if a fair distribution strategy is applied. PMID:24621655

Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial.

PubMed

Kulin, Merima; Fortuna, Carolina; De Poorter, Eli; Deschrijver, Dirk; Moerman, Ingrid

2016-06-01

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves.

Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial

PubMed Central

Kulin, Merima; Fortuna, Carolina; De Poorter, Eli; Deschrijver, Dirk; Moerman, Ingrid

2016-01-01

Data science or “data-driven research” is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves. PMID:27258286

Graduate Employability: The Perspective of Social Network Learning

ERIC Educational Resources Information Center

Chen, Yong

2017-01-01

This study provides a conceptual framework for understanding how the graduate acquire employability through the social network in the Chinese context, using insights from the social network theory. This paper builds a conceptual model of the relationship among social network, social network learning and the graduate employability, and uses…

Ubiquitousness of link-density and link-pattern communities in real-world networks

NASA Astrophysics Data System (ADS)

Šubelj, L.; Bajec, M.

2012-01-01

Community structure appears to be an intrinsic property of many complex real-world networks. However, recent work shows that real-world networks reveal even more sophisticated modules than classical cohesive (link-density) communities. In particular, networks can also be naturally partitioned according to similar patterns of connectedness among the nodes, revealing link-pattern communities. We here propose a propagation based algorithm that can extract both link-density and link-pattern communities, without any prior knowledge of the true structure. The algorithm was first validated on different classes of synthetic benchmark networks with community structure, and also on random networks. We have further applied the algorithm to different social, information, technological and biological networks, where it indeed reveals meaningful (composites of) link-density and link-pattern communities. The results thus seem to imply that, similarly as link-density counterparts, link-pattern communities appear ubiquitous in nature and design.

Social Media and Mentoring in Biomedical Research Faculty Development

PubMed Central

Teruya, Stacey Alan; Bazargan-Hejazi, Shahrzad

2015-01-01

Purpose To determine how effective and collegial mentoring in biomedical research faculty development may be implemented and facilitated through social media. Method The authors reviewed the literature for objectives, concerns, and limitations of career development for junior research faculty. They tabularized these as developmental goals, and aligned them with relevant social media strengths and capabilities facilitated through traditional and/or peer mentoring. Results The authors derived a model in which social media is leveraged to achieve developmental goals reflected in independent and shared projects, and in the creation and expansion of support and research networks. Conclusions Social media may be successfully leveraged and applied in achieving developmental goals for biomedical research faculty, and potentially for those in other fields and disciplines. PMID:26120494

Wayfinding in Social Networks

NASA Astrophysics Data System (ADS)

Liben-Nowell, David

With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza outbreak.

PubMed

Liu, Jianhua; Jiang, Hongbo; Zhang, Hao; Guo, Chun; Wang, Lei; Yang, Jing; Nie, Shaofa

2017-06-27

In the summer of 2014, an influenza A(H3N2) outbreak occurred in Yichang city, Hubei province, China. A retrospective study was conducted to collect and interpret hospital and epidemiological data on it using social network analysis and global sensitivity and uncertainty analyses. Results for degree (χ2=17.6619, P<0.0001) and betweenness(χ2=21.4186, P<0.0001) centrality suggested that the selection of sampling objects were different between traditional epidemiological methods and newer statistical approaches. Clique and network diagrams demonstrated that the outbreak actually consisted of two independent transmission networks. Sensitivity analysis showed that the contact coefficient (k) was the most important factor in the dynamic model. Using uncertainty analysis, we were able to better understand the properties and variations over space and time on the outbreak. We concluded that use of newer approaches were significantly more efficient for managing and controlling infectious diseases outbreaks, as well as saving time and public health resources, and could be widely applied on similar local outbreaks.

An ANOVA approach for statistical comparisons of brain networks.

PubMed

Fraiman, Daniel; Fraiman, Ricardo

2018-03-16

The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.

Relationship between Social Networks Adoption and Social Intelligence

ERIC Educational Resources Information Center

Gunduz, Semseddin

2017-01-01

The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

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

Build your own social network laboratory with Social Lab: a tool for research in social media.

PubMed

Garaizar, Pablo; Reips, Ulf-Dietrich

2014-06-01

Social networking has surpassed e-mail and instant messaging as the dominant form of online communication (Meeker, Devitt, & Wu, 2010). Currently, all large social networks are proprietary, making it difficult to impossible for researchers to make changes to such networks for the purpose of study design and access to user-generated data from the networks. To address this issue, the authors have developed and present Social Lab, an Internet-based free and open-source social network software system available from http://www.sociallab.es . Having full availability of navigation and communication data in Social Lab allows researchers to investigate behavior in social media on an individual and group level. Automated artificial users ("bots") are available to the researcher to simulate and stimulate social networking situations. These bots respond dynamically to situations as they unfold. The bots can easily be configured with scripts and can be used to experimentally manipulate social networking situations in Social Lab. Examples for setting up, configuring, and using Social Lab as a tool for research in social media are provided.

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

Social Network Assessments and Interventions for Health Behavior Change: A Critical Review.

PubMed

Latkin, Carl A; Knowlton, Amy R

2015-01-01

Social networks provide a powerful approach for health behavior change. This article documents how social network interventions have been successfully used for a range of health behaviors, including HIV risk practices, smoking, exercise, dieting, family planning, bullying, and mental health. We review the literature that suggests the relationship between health behaviors and social network attributes demonstrates a high degree of specificity. The article then examines hypothesized social influence mechanisms including social norms, modeling, and social rewards and the factors of social identity and social rewards that can be employed to sustain social network interventions. Areas of future research avenues are highlighted, including the need to examine and to adjust analytically for contamination and social diffusion, social influence versus differential affiliation, and network change. Use and integration of mhealth and face-to-face networks for promoting health behavior change are also critical research areas.

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

Social Network Types and Mental Health Among LGBT Older Adults.

PubMed

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

2017-02-01

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. 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. 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. 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. © The Author 2017. 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.

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

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

PubMed

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

2016-11-01

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. 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. 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. Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted.

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

Social network, social support, and risk of incident stroke: Atherosclerosis Risk in Communities study.

PubMed

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

2014-10-01

Having a small social network and lack of social support have been associated with incident coronary heart disease; however, epidemiological 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. The Atherosclerosis Risk in Communities study measured social network and social support in 13 686 men and women (mean, 57 years; 56% women; 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. During 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 (hazard ratio [95% confidence interval], 1.44 [1.02-2.04]) after adjustment for demographics, socioeconomic variables, 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. 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. © 2014 American Heart Association, Inc.

Promoting Social Network Awareness: A Social Network Monitoring System

ERIC Educational Resources Information Center

Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

2010-01-01

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

Understanding Social Networks: Theories, Concepts, and Findings

ERIC Educational Resources Information Center

Kadushin, Charles

2012-01-01

Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…

The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic.

PubMed

Han, Hye Joo; Schweickert, Richard; Xi, Zhuangzhuang; Viau-Quesnel, Charles

2016-04-01

For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream social network is not a copy of the cognitive social network. Waking life social networks tend to have positive assortativity; that is, people tend to be connected to others with similar connectivity. Instead, in our sample of dream social networks assortativity is more often negative or near 0, as in online social networks. We show that if characters appear via a random walk, negative assortativity can result, particularly if the random walk is biased as suggested by remote associations. Copyright © 2015 Cognitive Science Society, Inc.

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

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

NASA Astrophysics Data System (ADS)

Hattam, Laura; Greetham, Danica Vukadinović

2018-01-01

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes' model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes' equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

Generating realistic environments for cyber operations development, testing, and training

NASA Astrophysics Data System (ADS)

Berk, Vincent H.; Gregorio-de Souza, Ian; Murphy, John P.

2012-06-01

Training eective cyber operatives requires realistic network environments that incorporate the structural and social complexities representative of the real world. Network trac generators facilitate repeatable experiments for the development, training and testing of cyber operations. However, current network trac generators, ranging from simple load testers to complex frameworks, fail to capture the realism inherent in actual environments. In order to improve the realism of network trac generated by these systems, it is necessary to quantitatively measure the level of realism in generated trac with respect to the environment being mimicked. We categorize realism measures into statistical, content, and behavioral measurements, and propose various metrics that can be applied at each level to indicate how eectively the generated trac mimics the real world.

Reconfiguration and Search of Social Networks

PubMed Central

Zhang, Lianming; Peng, Aoyuan

2013-01-01

Social networks tend to exhibit some topological characteristics different from regular networks and random networks, such as shorter average path length and higher clustering coefficient, and the node degree of the majority of social networks obeys exponential distribution. Based on the topological characteristics of the real social networks, a new network model which suits to portray the structure of social networks was proposed, and the characteristic parameters of the model were calculated. To find out the relationship between two people in the social network, and using the local information of the social network and the parallel mechanism, a hybrid search strategy based on k-walker random and a high degree was proposed. Simulation results show that the strategy can significantly reduce the average number of search steps, so as to effectively improve the search speed and efficiency. PMID:24574861

Adoption of Social Networking in Education: A Study of the Use of Social Networks by Higher Education Students in Oman

ERIC Educational Resources Information Center

Al-Mukhaini, Elham M.; Al-Qayoudhi, Wafa S.; Al-Badi, Ali H.

2014-01-01

The use of social networks is a growing phenomenon, being increasingly important in both private and academic life. Social networks are used as tools to enable users to have social interaction. The use of social networks (SNs) complements and enhances the teaching in traditional classrooms. For example, YouTube, Facebook, wikis, and blogs provide…

The moderating role of attachment anxiety on social network site use intensity and social capital.

PubMed

Liu, Haihua; Shi, Junqi; Liu, Yihao; Sheng, Zitong

2013-02-01

This study examined the moderating role of attachment anxiety on the relationship between intensity of social network site use and bridging, bonding, and maintained social capital. Data from 322 undergraduate Chinese students were collected. Hierarchical regression analyses showed positive relationships between online intensity of social network site use and the three types of social capital. Moreover, attachment anxiety moderated the effect of intensity of social network site use on social capital. Specifically, for students with lower attachment anxiety, the relationships between intensity of social network site use and bonding and bridging social capital were stronger than those with higher attachment anxiety. The result suggested that social network sites cannot improve highly anxiously attached individuals' social capital effectively; they may need more face-to-face communications.

Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

NASA Astrophysics Data System (ADS)

Bruun, Jesper; Brewe, Eric

2013-12-01

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1) communication about how to solve physics problems in the course (called the PS category), (2) communications about the nature of physics concepts (called the CD category), and (3) social interactions that are not strictly related to the content of the physics classes (called the ICS category) in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI) scores. We find highly significant correlations (p<0.001) between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network), the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively) with future grades. In the CD network, the network measure target entropy shows the highest correlation (r=0.45) with future grades. In the network composed solely of noncontent related social interactions, these patterns of correlation are maintained in the sense that these network measures show the highest correlations and maintain their internal ranking. Using hierarchical linear regression, we find that a linear model that adds the network measures hide and target entropy, calculated on the ICS network, significantly improves a base model that uses only the FCI pretest scores from the beginning of the semester. Though one should not infer causality from these results, they do point to how social interactions in class are intertwined with academic interactions. We interpret this as an integral part of learning, and suggest that physics is a robust example.

Privacy-Preserving Relationship Path Discovery in Social Networks

NASA Astrophysics Data System (ADS)

Mezzour, Ghita; Perrig, Adrian; Gligor, Virgil; Papadimitratos, Panos

As social networks sites continue to proliferate and are being used for an increasing variety of purposes, the privacy risks raised by the full access of social networking sites over user data become uncomfortable. A decentralized social network would help alleviate this problem, but offering the functionalities of social networking sites is a distributed manner is a challenging problem. In this paper, we provide techniques to instantiate one of the core functionalities of social networks: discovery of paths between individuals. Our algorithm preserves the privacy of relationship information, and can operate offline during the path discovery phase. We simulate our algorithm on real social network topologies.

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments

PubMed Central

Nikfarjam, Azadeh; Gonzalez, Graciela H.

2011-01-01

Rapid growth of online health social networks has enabled patients to communicate more easily with each other. This way of exchange of opinions and experiences has provided a rich source of information about drugs and their effectiveness and more importantly, their possible adverse reactions. We developed a system to automatically extract mentions of Adverse Drug Reactions (ADRs) from user reviews about drugs in social network websites by mining a set of language patterns. The system applied association rule mining on a set of annotated comments to extract the underlying patterns of colloquial expressions about adverse effects. The patterns were tested on a set of unseen comments to evaluate their performance. We reached to precision of 70.01% and recall of 66.32% and F-measure of 67.96%. PMID:22195162

Emergent Learning and Interactive Media Artworks: Parameters of Interaction for Novice Groups

ERIC Educational Resources Information Center

Kawka, Marta; Larkin, Kevin; Danaher, P. A.

2011-01-01

Emergent learning describes learning that occurs when participants interact and distribute knowledge, where learning is self-directed, and where the learning destination of the participants is largely unpredictable (Williams, Karousou, & Mackness, 2011). These notions of learning arise from the topologies of social networks and can be applied to…

Reality Is Our Laboratory: Communities of Practice in Applied Computer Science

ERIC Educational Resources Information Center

Rohde, M.; Klamma, R.; Jarke, M.; Wulf, V.

2007-01-01

The present paper presents a longitudinal study of the course "High-tech Entrepreneurship and New Media." The course design is based on socio-cultural theories of learning and considers the role of social capital in entrepreneurial networks. By integrating student teams into the communities of practice of local start-ups, we offer…

Making the Most of "External" Group Members in Blended and Online Environments

ERIC Educational Resources Information Center

Hernández-Nanclares, Núria; García-Muñiz, Ana S.; Rienties, Bart

2017-01-01

Although the importance of boundary spanning in blended and online learning is widely acknowledged, most educational research has ignored whether and how students learn from others outside their assigned group. One potential approach for understanding cross-boundary knowledge sharing is Social Network Analysis (SNA). In this article, we apply four…

Applying Constructionist Principles to Online Teacher Professional Development

ERIC Educational Resources Information Center

Ostashewski, Nathaniel; Moisey, Susan; Reid, Doug

2011-01-01

This report explores the first iteration of a teacher professional development courselet grounded in constructionist theory and activities. This online teacher professional development (oTPD) courselet provided opportunities for teachers to engage in just-in-time, ongoing TPD within a social networking site for educators. The topic of the oTPD was…

Design and Implementation of Marine Information System, and Analysis of Learners' Intention toward

ERIC Educational Resources Information Center

Pan, Yu-Jen; Kao, Jui-Chung; Yu, Te-Cheng

2016-01-01

The goal of this study is to conduct further research and discussion on applying the internet on marine education, utilizing existing technologies such as cloud service, social network, data collection analysis, etc. to construct a marine environment education information system. The content to be explored includes marine education information…

Researching Classroom Communications and Relations in the Light of Social Justice

ERIC Educational Resources Information Center

Montesano Montessori, Nicolina; Ponte, Petra

2012-01-01

This article discusses participative action research performed by a network consisting of researchers and student-teachers of a University of Applied Sciences and teachers and pupils of four primary schools in the Netherlands. The research took place in the context of the research group "Behaviour and Research in the Educational Praxis".…

Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

Social disadvantage and borderline personality disorder: A study of social networks.

PubMed

Beeney, Joseph E; Hallquist, Michael N; Clifton, Allan D; Lazarus, Sophie A; Pilkonis, Paul A

2018-01-01

Examining differences in social integration, social support, and relationship characteristics in social networks may be critical for understanding the character and costs of the social difficulties experienced of borderline personality disorder (BPD). We conducted an ego-based (self-reported, individual) social network analysis of 142 participants recruited from clinical and community sources. Each participant listed the 30 most significant people (called alters) in their social network, then rated each alter in terms of amount of contact, social support, attachment strength and negative interactions. In addition, measures of social integration were determined using participant's report of the connection between people in their networks. BPD was associated with poorer social support, more frequent negative interactions, and less social integration. Examination of alter-by-BPD interactions indicated that whereas participants with low BPD symptoms had close relationships with people with high centrality within their networks, participants with high BPD symptoms had their closest relationships with people less central to their networks. The results suggest that individuals with BPD are at a social disadvantage: Those with whom they are most closely linked (including romantic partners) are less socially connected (i.e., less central) within their social network. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Smoking in school-aged adolescents: design of a social network survey in six European countries.

PubMed

Lorant, Vincent; Soto, Victoria Eugenia; Alves, Joana; Federico, Bruno; Kinnunen, Jaana; Kuipers, Mirte; Moor, Irene; Perelman, Julian; Richter, Matthias; Rimpelä, Arja; Robert, Pierre-Olivier; Roscillo, Gaetano; Kunst, Anton

2015-03-21

In Western countries, smoking accounts for a large share of socio-economic inequalities in health. As smoking initiation occurs around the age of 13, it is likely that school context and social networks at school play a role in the origin of such inequalities. So far, there has been little generic explanation of how social ties at school contribute to socio-economic inequalities in smoking. The SILNE (Smoking Inequalities - Learning from Natural Experiments) survey was designed to test the hypothesis that a combination of peer effect, homophilous social ties, and school context may explain how smoking inequalities are magnified at school - a theory known as network-induced inequality. In this paper, the survey theory and design are presented. The social network survey was carried out in 2013 in six medium-sized European cities with average incomes similar to the national average: Namur (Belgium), Tampere (Finland), Hannover (Germany), Latina (Italy), Amersfoort (The Netherlands), and Coimbra (Portugal). In each city, 6 to 8 schools were selected in a stratified sampling procedure. In each school, two grades in secondary education, corresponding to 14-16-year-olds, were selected. All adolescents in these two grades were invited to participate in the survey. Social ties were reported using the roster approach, in which each adolescent had to nominate up to 5 friends from a directory. The survey collected information from 11,015 adolescents in 50 schools, out of a total of 13,870 registered adolescents, yielding a participation rate of 79%. The SILNE survey yielded 57,094 social ties, 86.7% of which referred to friends who also participated in the survey. The SILNE survey was designed to measure the association between adolescents' social ties at school, their socio-economic background, and their smoking behaviour. Two difficulties were encountered, however: legal privacy constraints made it impossible to apply the same parental consent procedure in all countries, leading to somewhat lower participation rates in two cities: Hannover and Latina. It was also difficult to match the 6 cities in terms of both age and type of education. The SILNE survey provided a comparable database for the study of smoking inequalities across European cities from a social network perspective.

Knowledge exchange in the UK CLAHRCs.

PubMed

Racko, Girts

2018-04-09

Purpose The purpose of this paper is to examine how knowledge exchange between academics and clinicians in Collaborations for Leadership in Applied Health Research and Care (CLAHRCs) is influenced by their social position based on their symbolic and social capitals, that is, their personal professional status and connections to high-status professional peers, knowledge brokers, and unfamiliar professional peers. Design/methodology/approach Using an online survey, the author triangulates the cross-sectional measurement of the effects of academic and clinicians' social position in the initial and later phases of CLAHRCs with the longitudinal measurement of these effects over a two-year period. Findings First, academics and clinicians with a higher personal professional status are more likely to develop joint networks and decision making both in the early and later phases of a CLAHRC. Second, academics and clinicians who are more connected to higher status occupational peers are more likely to develop joint networks in the early phase of a knowledge exchange partnership but are less likely to become engaged in joint networks over time. Third, involvement of knowledge brokers in the networks of academics and clinicians is likely to facilitate their inter-professional networking only in the later partnership phase. Practical implications Academics and clinicians' capitals have a distinctive influence on knowledge exchange in the early and later phases of CLAHRCs and on a change in knowledge exchange over a two-year period. Originality/value Prior research on CLAHRCs has examined how knowledge exchange between academics and clinicians can be encouraged by the creation of shared governance mechanisms. The author advances this research by highlighting the role of their social position in facilitating knowledge exchange.

A Social Network Family-Focused Intervention to Promote Smoking Cessation in Chinese and Vietnamese American Male Smokers: A Feasibility Study.

PubMed

Tsoh, Janice Y; Burke, Nancy J; Gildengorin, Ginny; Wong, Ching; Le, Khanh; Nguyen, Anthony; Chan, Joanne L; Sun, Angela; McPhee, Stephen J; Nguyen, Tung T

2015-08-01

Smoking prevalence is high among limited English-proficient Chinese and Vietnamese American men, who are frequently unmotivated to quit and who underutilize smoking cessation resources. This study applied lay health worker outreach to leverage peer and family networks to promote smoking cessation among these men. We integrated qualitative formative research findings and Social Network Theory to develop a social-network family-focused intervention. In a pilot single-group trial, 15 lay health workers recruited 96 dyads (N = 192, 75% Vietnamese) of Chinese or Vietnamese male daily smokers and their family members and delivered the intervention consisting of two small group education sessions and two individual telephone calls over 2 months. At baseline, 42% of smokers were at precontemplation. At 3 months following the initiation of the intervention, 7-day and 30-day point prevalence smoking abstinence rates as reported by smokers and independently corroborated by family members were 30% and 24%, respectively. Utilization of smoking cessation resources (medication, quitline, physician's advice) increased from 2% to 60% (P < .001). Findings showed high acceptability of the intervention as it facilitated learning about tobacco-related health risks and cessation resources, and communications between smokers and their families. This novel social network family-focused intervention to promote smoking cessation among Chinese and Vietnamese smokers appears to be acceptable, feasible, and potentially efficacious. Findings warrant evaluation of long-term efficacy of the intervention in a larger scale randomized controlled trial. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

The ART of Social Networking: How SART member clinics are connecting with patients online

PubMed Central

OMURTAG, Kenan; JIMENEZ, Patricia T.; RATTS, Valerie; ODEM, Randall; COOPER, Amber R.

2013-01-01

Objective To study and describe the use of social networking websites among SART member clinics Design Cross-sectional study Setting University Based Practice Patients Not Applicable Interventions Not Applicable Main Outcome Measure Prevalence of social networking websites among SART member clinics and evaluation of content, volume and location (i.e mandated state, region) using multivariate regression analysis Results 384 SART registered clinics and 1,382 social networking posts were evaluated. Of the clinics, 96% have a website and 30% link to a social networking website. The majority of clinics (89%) with social networking websites were affiliated with non-academic centers. Social networking posts mostly provide information (31%) and/or advertise (28%), while the remaining offer support (19%) or are irrelevant (17%) to the target audience. Only 5% of posts involved patients requesting information. Clinic volume correlates with the presence of a clinic website and a social networking website (p<0.001). Conclusion Almost all SART member clinics have a website. Nearly one-third of these clinics host a social networking website like Facebook, Twitter and/or a Web-log (“blog”). Larger volume clinics commonly host social networking websites. These sites provide new ways to communicate with patients, but clinics should maintain policies on the incorporation of social networks into practice. PMID:22088209

Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

DTIC Science & Technology

2011-03-10

more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...results give overviews on social interactions on a popular social network site . As each twitter account has different characteristics based on...the public and individuals post their private stories on their blogs and share their interests using social network sites . On the other hand, people

Psychology and social networks: a dynamic network theory perspective.

PubMed

Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

2014-04-01

Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Social network changes and life events across the life span: a meta-analysis.

PubMed

Wrzus, Cornelia; Hänel, Martha; Wagner, Jenny; Neyer, Franz J

2013-01-01

For researchers and practitioners interested in social relationships, the question remains as to how large social networks typically are, and how their size and composition change across adulthood. On the basis of predictions of socioemotional selectivity theory and social convoy theory, we conducted a meta-analysis on age-related social network changes and the effects of life events on social networks using 277 studies with 177,635 participants from adolescence to old age. Cross-sectional as well as longitudinal studies consistently showed that (a) the global social network increased up until young adulthood and then decreased steadily, (b) both the personal network and the friendship network decreased throughout adulthood, (c) the family network was stable in size from adolescence to old age, and (d) other networks with coworkers or neighbors were important only in specific age ranges. Studies focusing on life events that occur at specific ages, such as transition to parenthood, job entry, or widowhood, demonstrated network changes similar to such age-related network changes. Moderator analyses detected that the type of network assessment affected the reported size of global, personal, and family networks. Period effects on network sizes occurred for personal and friendship networks, which have decreased in size over the last 35 years. Together the findings are consistent with the view that a portion of normative, age-related social network changes are due to normative, age-related life events. We discuss how these patterns of normative social network development inform research in social, evolutionary, cultural, and personality psychology. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

A Qualitative Study of the Formation and Composition of Social Networks Among Homeless Youth

PubMed Central

Tyler, Kimberly A.; Melander, Lisa A.

2011-01-01

Although social networks are essential for explaining protective and risk factors among homeless youth, little is known about the formation and composition of these groups. In this study, we utilized 19 in-depth interviews with homeless youth to investigate their social network formation, role relationships, housing status, and network member functions. Our findings reveal that the formation of these networks occurred in different ways including meeting network members through others or in specific social situations. The majority of social network members were currently housed and provided various functions including instrumental and social support and protection. Responses from participants provide valuable insight into the formation of social networks and potentially explain their subsequent involvement in risky behaviors. PMID:22121330

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.

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 medicine, feminism and the politics of population: From transnational knowledge networks to national social movements in Brazil and Mexico.

PubMed

de la Dehesa, Rafael

2018-02-28

This article examines the role of national actors articulated with an explicitly counter-hegemonic transnational knowledge network (TKN) mobilising around social medicine in policy debates on population control and family planning. It focuses primarily on Brazil, using Mexico as a shadow case to highlight salient points of contrast. In doing so, it makes two contributions to larger debates about TKNs. First, it highlights the plural and contested nature of the knowledge production they enact, underscoring contestation around a global reproductive regime that consolidated around family planning. Second, it underscores how the position and relative influence of actors articulated with TKNs is shaped by political and institutional contexts at the national level, producing variable opportunities for the mobilisation of applied knowledge. Reflecting its advocates' embeddedness in larger opposition movements to authoritarian states, social medicine had a greater influence on these debates in Brazil, where synergies with a resurgent feminist movement reinforced a shared insistence on comprehensive women's healthcare and increased the salience of sterilisation abuse on the political agenda.

A friend request from dear old dad: associations between parent-child social networking and adolescent outcomes.

PubMed

Coyne, Sarah M; Padilla-Walker, Laura M; Day, Randal D; Harper, James; Stockdale, Laura

2014-01-01

This study examined the relationship between parent-child social networking, connection, and outcomes for adolescents. Participants (491 adolescents and their parents) completed a number of questionnaires on social networking use, feelings of connection, and behavioral outcomes. Social networking with parents was associated with increased connection between parents and adolescents. Feelings of connection then mediated the relationship between social networking with parents and behavioral outcomes, including higher prosocial behavior and lower relational aggression and internalizing behavior. Conversely, adolescent social networking use without parents was associated with negative outcomes, such as increased relational aggression, internalizing behaviors, delinquency, and decreased feelings of connection. These results indicate that although high levels of social networking use may be problematic for some individuals, social networking with parents may potentially strengthen parent-child relationships and then lead to positive outcomes for adolescents.

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

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

PubMed

Hao, Chun; Liu, Hongjie

2015-06-01

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. 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. 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. 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. © The Author(s) 2014.

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

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation

PubMed Central

Kwak, Doyeon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks. PMID:28542367

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

PubMed

Kwak, Doyeon; Kim, Wonjoon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

Online access and motivation of tutors of health professions higher education.

PubMed

Monaco, Federico; Sarli, Leopoldo; Guasconi, Massimo; Alfieri, Emanuela

2016-11-22

The case study of PUNTOZERO as an open web lab for activities, research and support to 5 Master's courses for the health professions is described. A virtual learning environment integrated in a much wider network including social networks and open resources was experimented on for five Master's Courses for the health professions at the University of Parma. A social learning approach might be applied by the engagement of motivated and skilled tutors. This is not only needed for the improvement and integration of the digital and collaborative dimension in higher education, but it aims to introduce issues and biases of emerging e-health and online networking dimensions for future healthcare professionals. Elements of e-readiness to train tutors and improve their digital skills and e-moderation approaches are evident. This emerged during an online and asynchronous interview with two tutors out of the four that were involved, by the use of a wiki where interviewer and informants could both read and add contents and comments.

Fast Katz and Commuters: Efficient Estimation of Social Relatedness in Large Networks

NASA Astrophysics Data System (ADS)

Esfandiar, Pooya; Bonchi, Francesco; Gleich, David F.; Greif, Chen; Lakshmanan, Laks V. S.; On, Byung-Won

Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topological measures including the Katz score and the commute time. Existing approaches typically approximate all pairwise relationships simultaneously. In this paper, we are interested in computing: the score for a single pair of nodes, and the top-k nodes with the best scores from a given source node. For the pairwise problem, we apply an iterative algorithm that computes upper and lower bounds for the measures we seek. This algorithm exploits a relationship between the Lanczos process and a quadrature rule. For the top-k problem, we propose an algorithm that only accesses a small portion of the graph and is related to techniques used in personalized PageRank computing. To test the scalability and accuracy of our algorithms we experiment with three real-world networks and find that these algorithms run in milliseconds to seconds without any preprocessing.

Recent Themes in Social Networking Service Research.

PubMed

Liu, John S; Ho, Mei Hsiu-Ching; Lu, Louis Y Y

2017-01-01

The body of literature addressing the phenomenon related to social networking services (SNSs) has grown rather fast recently. Through a systematic and quantitative approach, this study identifies the recent SNS research themes, which are the issues discussed by a coherent and growing subset of this literature. A set of academic articles retrieved from the Web of Science database is used as the basis for uncovering the recent themes. We begin the analysis by constructing a citation network which is further separated into groups after applying a widely used clustering method. The resulting clusters all consist of articles coherent in citation relationships. This study suggests eight fast growing recent themes. They span widely encompassing politics, romantic relationships, public relations, journalism, and health. Among them, four focus their issues largely on Twitter, three on Facebook, and one generally on both. While discussions on traditional issues in SNSs such as personality, motivations, self-disclosure, narcissism, etc. continue to lead the pack, the proliferation of the highlighted recent themes in the near future is very likely to happen.

Fast katz and commuters : efficient estimation of social relatedness in large networks.

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

On, Byung-Won; Lakshmanan, Laks V. S.; Greif, Chen

Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topological measures including the Katz score and the commute time. Existing approaches typically approximate all pairwise relationships simultaneously. In this paper, we are interested in computing: the score for a single pair of nodes, and the top-k nodes with the best scores from a given source node. For the pairwise problem, we apply an iterative algorithm that computes upper and lower bounds for the measures we seek. This algorithm exploits a relationship between the Lanczos process and amore » quadrature rule. For the top-k problem, we propose an algorithm that only accesses a small portion of the graph and is related to techniques used in personalized PageRank computing. To test the scalability and accuracy of our algorithms we experiment with three real-world networks and find that these algorithms run in milliseconds to seconds without any preprocessing.« less

Recent Themes in Social Networking Service Research

PubMed Central

Liu, John S.; Ho, Mei Hsiu-Ching; Lu, Louis Y. Y.

2017-01-01

The body of literature addressing the phenomenon related to social networking services (SNSs) has grown rather fast recently. Through a systematic and quantitative approach, this study identifies the recent SNS research themes, which are the issues discussed by a coherent and growing subset of this literature. A set of academic articles retrieved from the Web of Science database is used as the basis for uncovering the recent themes. We begin the analysis by constructing a citation network which is further separated into groups after applying a widely used clustering method. The resulting clusters all consist of articles coherent in citation relationships. This study suggests eight fast growing recent themes. They span widely encompassing politics, romantic relationships, public relations, journalism, and health. Among them, four focus their issues largely on Twitter, three on Facebook, and one generally on both. While discussions on traditional issues in SNSs such as personality, motivations, self-disclosure, narcissism, etc. continue to lead the pack, the proliferation of the highlighted recent themes in the near future is very likely to happen. PMID:28107541

A Methodology to Develop Entrepreneurial Networks: The Tech Ecosystem of Six African Cities

DTIC Science & Technology

2014-11-01

Information Center. Greve, A. and Salaff, J. W. (2003), Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice, 28: 1–22. doi...methodology enables us to accurately measure social capital and circumvents the massive effort of mapping an individual’s social network before...locating the social resources in it. 15. SUBJECT TERMS Network Analysis, Economic Networks, Network Topology, Network Classification 16. SECURITY

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

Youm, Yoosik; Laumann, Edward O; Ferraro, Kenneth F; Waite, Linda J; Kim, Hyeon Chang; Park, Yeong-Ran; Chu, Sang Hui; Joo, Won-Tak; Lee, Jin A

2014-09-14

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. 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. 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. 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.

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

Social networks in cardiovascular disease management.

PubMed

Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

2010-12-01

Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

SOCIAL CAPITAL AND HEALTH CARE ACCESS: A SYSTEMATIC REVIEW

PubMed Central

Derose, Kathryn Pitkin; Varda, Danielle M.

2017-01-01

A growing interest in community-level characteristics such as social capital and their relationship to healthcare access is evident. To assess the rigor with which this construct has been empirically applied in research on healthcare access, we conducted a systematic review. A total of 2396 abstracts were reviewed, with 21 ultimately meeting our criteria of examining some measure of social capital and its effects on healthcare access. Our review found a lack of congruence in how social capital was measured and interpreted and a general inconsistency in findings, which made it difficult to draw firm conclusions about the effects of social capital on healthcare access. Insights from the social network literature can help improve the conceptual and measurement problems. We recommend that future work distinguish between bonding, bridging, and linking social capital and their sources and benefits, and that perhaps three dimensions of social capital actually exist –cognitive, behavioral, and structural. PMID:19174538

[Psychometric properties of a Multidimensional Scale of Social Expression to assess social skills in the Internet context].

PubMed

Carballo, José L; Pérez-Jover, Ma Virtudes; Espada, José P; Orgilés, Mireia; Piqueras, José Antonio

2012-02-01

The increase in the use of New Technologies in social relationships could be generating a new paradigm in social skills. Valid and reliable instruments to assess these changes are needed. The aim of this study is to analyze the psychometric properties of the Multidimensional Scale of Social Expression (EMES) in the assessment of social skills on the Internet and Social Networks. A total of 413 college students from the province of Alicante participated on this study. The scale was applied according to two contexts: Real and Internet/Virtual. High internal consistency was shown. The 12-factor structure found for the Virtual Context scale is similar to that of the original study. The scale had shown to be a good predictor of hours of Internet use. In conclusion, EMES-C is useful for assessing real context and Internet context social skills.

Control Theoretic Modeling for Uncertain Cultural Attitudes and Unknown Adversarial Intent

DTIC Science & Technology

2009-02-01

Constructive computational tools. 15. SUBJECT TERMS social learning, social networks , multiagent systems, game theory 16. SECURITY CLASSIFICATION OF: a...over- reactionary behaviors; 3) analysis of rational social learning in networks : analysis of belief propagation in social networks in various...general methodology as a predictive device for social network formation and for communication network formation with constraints on the lengths of

Brain connectivity dynamics during social interaction reflect social network structure

PubMed Central

Schmälzle, Ralf; Brook O’Donnell, Matthew; Garcia, Javier O.; Cascio, Christopher N.; Bayer, Joseph; Vettel, Jean M.

2017-01-01

Social ties are crucial for humans. Disruption of ties through social exclusion has a marked effect on our thoughts and feelings; however, such effects can be tempered by broader social network resources. Here, we use fMRI data acquired from 80 male adolescents to investigate how social exclusion modulates functional connectivity within and across brain networks involved in social pain and understanding the mental states of others (i.e., mentalizing). Furthermore, using objectively logged friendship network data, we examine how individual variability in brain reactivity to social exclusion relates to the density of participants’ friendship networks, an important aspect of social network structure. We find increased connectivity within a set of regions previously identified as a mentalizing system during exclusion relative to inclusion. These results are consistent across the regions of interest as well as a whole-brain analysis. Next, examining how social network characteristics are associated with task-based connectivity dynamics, we find that participants who showed greater changes in connectivity within the mentalizing system when socially excluded by peers had less dense friendship networks. This work provides insight to understand how distributed brain systems respond to social and emotional challenges and how such brain dynamics might vary based on broader social network characteristics. PMID:28465434

The association between social network relationships and depressive symptoms among older Americans: what matters most?

PubMed

Litwin, Howard

2011-08-01

Although social network relationships are linked to mental health in late life, it is still unclear whether it is the structure of social networks or their perceived quality that matters. The current study regressed a dichotomous 8-item version of the Center for Epidemiological Studies Depression Scale (CESD-8) score on measures of social network relationships among Americans, aged 65-85 years, from the first wave of the National Social Life, Health and Aging Project. The network indicators included a structural variable - social network type - and a series of relationship quality indicators: perceived positive and negative ties with family, friends and spouse/ partner. Multivariate logistic regression analyses controlled for age, gender, education, income, race/ethnicity, religious affiliation, functional health and physical health. The perceived social network quality variables were unrelated to the presence of a high level of depressive symptoms, but social network type maintained an association with this mental health outcome even after controlling for confounders. Respondents embedded in resourceful social network types in terms of social capital--"diverse," "friend" and "congregant" networks--reported less presence of depressive symptoms, to varying degrees. The results show that the structure of the network seems to matter more than the perceived quality of the ties as an indicator of depressive symptoms. Moreover, the composite network type variable stands out in capturing the differences in mental state. The construct of network type should be incorporated in mental health screening among older people who reside in the community. One's social network type can be an important initial indicator that one is at risk.

Talking the talk, walking the walk: social network norms, communication patterns, and condom use among the male partners of female sex workers in La Romana, Dominican Republic.

PubMed

Barrington, Clare; Latkin, Carl; Sweat, Michael D; Moreno, Luis; Ellen, Jonathan; Kerrigan, Deanna

2009-06-01

Male partners of female sex workers are rarely targeted by HIV prevention interventions in the commercial sex industry, despite recognition of their central role and power in condom use negotiation. Social networks offer a naturally existing social structure to increase male participation in preventing HIV. The purpose of this study was to explore the relationship between social network norms and condom use among male partners of female sex workers in La Romana, Dominican Republic. Male partners (N =318) were recruited from 36 sex establishments to participate in a personal network survey. Measures of social network norms included 1) perceived condom use by male social network members and 2) encouragement to use condoms from social network members. Other social network characteristics included composition, density, social support, and communication. The primary behavioral outcome was consistent condom use by male partners with their most recent female sex worker partner during the last 3 months. In general, men reported small, dense networks with high levels of communication about condoms and consistent condom use. Multivariate logistic regression revealed consistent condom use was significantly more likely among male partners who perceived that some or all of their male social network members used condoms consistently. Perceived condom use was, in turn, significantly associated with dense networks, expressing dislike for condoms, and encouragement to use condoms from social network members. Findings suggest that the tight social networks of male partners may help to explain the high level of condom use and could provide an entry point for HIV prevention efforts with men. Such efforts should tap into existing social dynamics and patterns of communication to promote pro-condom norms and reduce HIV-related vulnerability among men and their sexual partners.

Professional social networking.

PubMed

Rowley, Robert D

2014-12-01

We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

Link prediction in multiplex online social networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Link prediction in multiplex online social networks.

PubMed

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

A social network typology and sexual risk-taking among men who have sex with men in Cape Town and Port Elizabeth, South Africa

PubMed Central

de Voux, Alex; Baral, Stefan; Bekker, Linda-Gail; Beyrer, Chris; Phaswana-Mafuya, Nancy; Siegler, Aaron; Sullivan, Patrick; Winskell, Kate; Stephenson, Rob

2016-01-01

Despite the high prevalence of HIV among men who have sex with men in South Africa, very little is known about their lived realities, including their social and sexual networks. Given the influence of social network structure on sexual risk behaviours, a better understanding of the social contexts of men who have sex with men is essential for informing the design of HIV programming and messaging. This study explored social network connectivity, an understudied network attribute, examining self-reported connectivity between friends, family and sex partners. Data were collected in Cape Town and Port Elizabeth, South Africa from 78 men who have sex with men who participated in in-depth interviews which included a social network mapping component. Five social network types emerged from the content analysis of these social network maps based on the level of connectivity between family, friends and sex partners, and ranged from disconnected to densely connected networks. The ways in which participants reported sexual risk-taking differed across the five network types revealing diversity in social network profiles. HIV programming and messaging for this population can greatly benefit from recognising the diversity in lived realities and social connections between men who have sex with men. PMID:26569376

A social network typology and sexual risk-taking among men who have sex with men in Cape Town and Port Elizabeth, South Africa.

PubMed

de Voux, Alex; Baral, Stefan D; Bekker, Linda-Gail; Beyrer, Chris; Phaswana-Mafuya, Nancy; Siegler, Aaron J; Sullivan, Patrick S; Winskell, Kate; Stephenson, Rob

2016-01-01

Despite the high prevalence of HIV among men who have sex with men in South Africa, very little is known about their lived realities, including their social and sexual networks. Given the influence of social network structure on sexual risk behaviours, a better understanding of the social contexts of men who have sex with men is essential for informing the design of HIV programming and messaging. This study explored social network connectivity, an understudied network attribute, examining self-reported connectivity between friends, family and sex partners. Data were collected in Cape Town and Port Elizabeth, South Africa, from 78 men who have sex with men who participated in in-depth interviews that included a social network mapping component. Five social network types emerged from the content analysis of these social network maps based on the level of connectivity between family, friends and sex partners, and ranged from disconnected to densely connected networks. The ways in which participants reported sexual risk-taking differed across the five network types, revealing diversity in social network profiles. HIV programming and messaging for this population can greatly benefit from recognising the diversity in lived realities and social connections between men who have sex with men.

Young adults with mental health conditions and social networking websites: seeking tools to build community.

PubMed

Gowen, Kris; Deschaine, Matthew; Gruttadara, Darcy; Markey, Dana

2012-01-01

This study examined ways that young adults with mental illnesses (1) currently use social networking; and (2) how they would like to use a social networking site tailored for them. The authors examined differences between those with mental health conditions and those without. An online survey was administered by the National Alliance on Mental Illness (NAMI) to 274 participants; of those, 207 reported being between 18 and 24 years old. The survey included questions about current social networking use, the key resources respondents believed young adults living with mental illness need, and the essential components that should be included in a social networking site specifically tailored to young adults living with mental illness. Pearson Chi-square analyses examined the differences between those who reported having a mental illness and those who did not. Results indicate that almost all (94%) participants with mental illnesses currently use social networking sites. Individuals living with a mental illness are more likely than those not living with a mental illness to report engaging in various social networking activities that promote connectivity and making online friends. Individuals living with mental illnesses are also more likely to report wanting resources on independent living skills and overcoming social isolation available on a social networking site. Young adults living with mental illnesses are currently using social networking sites and express high interest in a social networking site specifically tailored to their population with specific tools designed to decrease social isolation and help them live more independently. These results indicate that practitioners should themselves be aware of the different social networking sites frequented by their young adult clients, ask clients about their use of social networking, and encourage safe and responsible online behaviors.

“I Don’t Know What Fun Is”: Examining the Intersection of Social Capital, Social Networks, and Social Recovery

PubMed Central

Boeri, Miriam; Gardner, Megan; Gerken, Erin; Ross, Melissa; Wheeler, Jack

2016-01-01

Purpose The purpose of this paper is to understand how people with problematic drug use access positive social capital. Social capital is defined as relations that provide valuable resources to individuals through participation in social networks. People with low socioeconomic status remain at a disadvantage for acquiring positive social capital, a component of recovery capital. The concept of social recovery emphasises the relational processes of recovery. Design/methodology/approach In-depth life history data were collected from 29 individuals who used heroin, cocaine, crack, or methamphetamine for at least five years, have less than a high school education, and unstable employment and housing. Qualitative data were coded for social networks accessed throughout the life course, distinguished by bonding, bridging and linking social capital. Findings Social networks included drug treatment programs; non-drug-using family and friends; religious/spiritual groups; workplace networks, and social clubs/activities. Bonding and/or bridging social capital were acquired through treatment, family and friends, religious/spiritual groups, workplaces, and social clubs. Linking social capital was not acquired through any social networks available, and many barriers to accessing mainstream social networks were found. Limitations This is a small study conducted in the US. Social implications A greater focus on social recovery is needed to achieve sustained recovery for individuals lacking access to and engagement in mainstream social networks. Practical implications Social recovery is proposed as an analytical tool as well as for developing prevention, intervention, and treatment strategies. PMID:27668008

Social Networking Sites as Virtual Communities of Practice: A Mixed Method Study

ERIC Educational Resources Information Center

Davis, Lorretta J.

2010-01-01

Membership in social networking sites is increasing rapidly. Social networking sites serve many purposes including networking, communication, recruitment, and sharing knowledge. Social networking sites, public or private, may be hosted on applications such as Facebook and LinkedIn. As individuals begin to follow and participate in social…

Social disclosure about lymphoedema symptoms: A qualitative study among Japanese breast cancer survivors.

PubMed

Tsuchiya, Miyako; Horn, Sandra; Ingham, Roger

2015-01-01

Disclosing illness-related problems is the first step in help-seeking. The aim of this qualitative study was to explore Japanese breast cancer (BC) survivors' decision-making about disclosure of lymphoedema symptoms to people in their social networks. A total of ten women participated in group discussions in Japan. A dual analytic approach, thematic analysis and conceptual analysis, was applied to the transcripts. Two themes (perceived responsibility of social roles within the family and unsupportive reactions to BC from others) affected participants' decision-making. Support programs for Japanese BC survivors who feel unable to disclose lymphoedema symptoms to family members are suggested.

Online social networking technologies, HIV knowledge, and sexual risk and testing behaviors among homeless youth.

PubMed

Young, Sean D; Rice, Eric

2011-02-01

This study evaluates associations between online social networking and sexual health behaviors among homeless youth in Los Angeles. We analyzed survey data from 201 homeless youth accessing services at a Los Angeles agency. Multivariate (regression and logistic) models assessed whether use of (and topics discussed on) online social networking technologies affect HIV knowledge, sexual risk behaviors, and testing for sexually transmitted infections (STIs). One set of results suggests that using online social networks for partner seeking (compared to not using the networks for seeking partners) is associated with increased sexual risk behaviors. Supporting data suggest that (1) using online social networks to talk about safe sex is associated with an increased likelihood of having met a recent sex partner online, and (2) having online sex partners and talking to friends on online social networks about drugs and partying is associated with increased exchange sex. However, results also suggest that online social network usage is associated with increased knowledge and HIV/STI prevention among homeless youth: (1) using online social networks to talk about love and safe sex is associated with increased knowledge about HIV, (2) using the networks to talk about love is associated with decreased exchange sex, and (3) merely being a member of an online social network is associated with increased likelihood of having previously tested for STIs. Taken together, this study suggests that online social networking and the topics discussed on these networks can potentially increase and decrease sexual risk behaviors depending on how the networks are used. Developing sexual health services and interventions on online social networks could reduce sexual risk behaviors.

The ART of social networking: how SART member clinics are connecting with patients online.

PubMed

Omurtag, Kenan; Jimenez, Patricia T; Ratts, Valerie; Odem, Randall; Cooper, Amber R

2012-01-01

To study and describe the use of social networking websites among Society for Assisted Reproductive Technology (SART) member clinics. Cross-sectional study. University-based practice. Not applicable. Not applicable. Prevalence of social networking websites among SART member clinics and evaluation of content, volume, and location (i.e., mandated state, region) using multivariate regression analysis. A total of 384 SART-registered clinics and 1,382 social networking posts were evaluated. Of the clinics, 96% had a website and 30% linked to a social networking website. The majority of clinics (89%) with social networking websites were affiliated with nonacademic centers. Social networking posts mostly provided information (31%) and/or advertising (28%), and the remaining offered support (19%) or were irrelevant (17%) to the target audience. Only 5% of posts involved patients requesting information. Clinic volume correlated with the presence of a clinic website and a social networking website. Almost all SART member clinics have a website. Nearly one-third of these clinics host a social networking website such as Facebook, Twitter, and/or a blog. Large-volume clinics commonly host social networking websites. These sites provide new ways to communicate with patients, but clinics should maintain policies on the incorporation of social networks into practice. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

The Longitudinal Effect of Self-Monitoring and Locus of Control on Social Network Position in Friendship Networks

DTIC Science & Technology

2006-03-01

equally essential to examine the antecedents that bring a person to a particular network location. The previous body of knowledge in social networks...Locus of Control on Social Network Position in Friendship Networks THESIS Gary J. Moore, Captain, USAF AFIT/GEM/ENV/06M-11 DEPARTMENT OF THE AIR...THE LONGITUDINAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON SOCIAL NETWORK POSITION IN FRIENDSHIP NETWORKS THESIS Presented to the

Towards Trust-based Cognitive Networks: A Survey of Trust Management for Mobile Ad Hoc Networks

DTIC Science & Technology

2009-06-01

of trust. First, social trust refers to properties derived from social relationships . Examples of social networks are strong social ... relationships such as colleagues or relatives or loose social relationships such as school alumni or friends with common interests [44]. Social trust may...also use social relationships in evaluating the trust metric among group members by employing the concept of social networks. Yu et al. [44] define

Masculinity, Educational Achievement and Social Status: A Social Network Analysis

ERIC Educational Resources Information Center

Lusher, Dean

2011-01-01

This study utilises a quantitative case study social network approach to explore the connection between masculinity and scholastic achievement in two secondary, all-boys schools in Australia. In both schools two social networks representing social status are explored: the "friendship" network as a measure of status that includes…

Social Network Methods for the Educational and Psychological Sciences

ERIC Educational Resources Information Center

Sweet, Tracy M.

2016-01-01

Social networks are especially applicable in educational and psychological studies involving social interactions. A social network is defined as a specific relationship among a group of individuals. Social networks arise in a variety of situations such as friendships among children, collaboration and advice seeking among teachers, and coauthorship…

The Application of Social Network Analysis to Team Sports

ERIC Educational Resources Information Center

Lusher, Dean; Robins, Garry; Kremer, Peter

2010-01-01

This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…

A Social Network Approach to Understanding an Insurgency

DTIC Science & Technology

2007-07-01

and a framework for testing theories regarding struc- tured social relationships.6 Equally relevant is the understanding of a social network approach...A Social Network Approach to Understanding an Insurgency BRIAN REED The study of networks, interactions, and relationships has a long history...characteristics of social network analysis is often counter-intuitive to traditional military thinking, rooted in the efficiency of a hierarchy that

"I Don't Know What Fun Is": Examining the Intersection of Social Capital, Social Networks, and Social Recovery.

PubMed

Boeri, Miriam; Gardner, Megan; Gerken, Erin; Ross, Melissa; Wheeler, Jack

The purpose of this paper is to understand how people with problematic drug use access positive social capital. Social capital is defined as relations that provide valuable resources to individuals through participation in social networks. People with low socioeconomic status remain at a disadvantage for acquiring positive social capital, a component of recovery capital. The concept of social recovery emphasises the relational processes of recovery. In-depth life history data were collected from 29 individuals who used heroin, cocaine, crack, or methamphetamine for at least five years, have less than a high school education, and unstable employment and housing. Qualitative data were coded for social networks accessed throughout the life course, distinguished by bonding, bridging and linking social capital. Social networks included drug treatment programs; non-drug-using family and friends; religious/spiritual groups; workplace networks, and social clubs/activities. Bonding and/or bridging social capital were acquired through treatment, family and friends, religious/spiritual groups, workplaces, and social clubs. Linking social capital was not acquired through any social networks available, and many barriers to accessing mainstream social networks were found. This is a small study conducted in the US. A greater focus on social recovery is needed to achieve sustained recovery for individuals lacking access to and engagement in mainstream social networks. Social recovery is proposed as an analytical tool as well as for developing prevention, intervention, and treatment strategies.

Measuring Social Networks for Medical Research in Lower-Income Settings

PubMed Central

Kelly, Laura; Patel, Shivani A.; Narayan, K. M. Venkat; Prabhakaran, Dorairaj; Cunningham, Solveig A.

2014-01-01

Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies. PMID:25153127

Social Capital in an Outdoor Recreation Context

NASA Astrophysics Data System (ADS)

Mann, Marilynne; Leahy, Jessica

2010-02-01

This study examined social capital development in three all-terrain vehicles (ATV) clubs in Maine using an adapted version of Lin’s (2001) social capital theory model. The structural components of social capital identified included collective assets and individual assets in the form of normative behavior and trust relationships. Also identified were counter-norms for individual ATV riders identified as having divergent norms from club members. The second component of social capital is access to and mobilization of network contacts and resources. Access networks in the context of the ATV clubs studied were identified as community and landowner relations while mobilization of resources was existent in club membership attempts toward self-governance and efforts of the statewide “umbrella” organization. Instrumental outcomes benefit society and expressive outcomes benefit the individual. Both types of returns are present in the data suggesting that ATV clubs are creating social capital. This is important information to clubs who desire to market themselves, improve their reputations, and enhance their volunteer association. It is of further interest to state governments who fund clubs through trail grants as proof that a return on investment is being realized. Theoretical and applied implications for these and other types of recreation-based volunteer associations (e.g., clubs, friends groups, advocacy groups) are presented.

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.

Changing Social Networks Among Homeless Individuals: A Prospective Evaluation of a Job- and Life-Skills Training Program.

PubMed

Gray, Heather M; Shaffer, Paige M; Nelson, Sarah E; Shaffer, Howard J

2016-10-01

Social networks play important roles in mental and physical health among the general population. Building healthier social networks might contribute to the development of self-sufficiency among people struggling to overcome homelessness and substance use disorders. In this study of homeless adults completing a job- and life-skills program (i.e., the Moving Ahead Program at St. Francis House, Boston), we prospectively examined changes in social network quality, size, and composition. Among the sample of participants (n = 150), we observed positive changes in social network quality over time. However, social network size and composition did not change among the full sample. The subset of participants who reported abstaining from alcohol during the months before starting the program reported healthy changes in their social networks; specifically, while completing the program, they re-structured their social networks such that fewer members of their network used alcohol to intoxication. We discuss practical implications of these findings.

Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks

PubMed Central

Piraveenan, Mahendra; Prokopenko, Mikhail; Hossain, Liaquat

2013-01-01

A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns) because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks. PMID:23349699

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

NASA Astrophysics Data System (ADS)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Social networks and links to isolation and loneliness among elderly HCBS clients.

PubMed

Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

2016-01-01

The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

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

PubMed

Siette, Joyce; Gulea, Claudia; Priebe, Stefan

2015-01-01

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. To identify instruments assessing social networks in studies of patients with psychotic disorders and explore their properties. A systematic search of electronic databases was conducted to identify studies that used a measure of social networks in patients with psychotic disorders. 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. 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.

Collaborative search in electronic health records.

PubMed

Zheng, Kai; Mei, Qiaozhu; Hanauer, David A

2011-05-01

A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a 'collaborative search' feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.

Collaborative search in electronic health records

PubMed Central

Mei, Qiaozhu; Hanauer, David A

2011-01-01

Objective A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a ‘collaborative search’ feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. Design The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. Results The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Conclusion Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare. PMID:21486887

The association between neighborhood social capital and self-reported dentate status in elderly Japanese--the Ohsaki Cohort 2006 Study.

PubMed

Aida, J; Kuriyama, S; Ohmori-Matsuda, K; Hozawa, A; Osaka, K; Tsuji, I

2011-06-01

Little is known about the influence of social capital on dental health. The aim of the present cross-sectional study was to determine the association between neighborhood social capital, individual social networks and social support and the number of remaining teeth in elderly Japanese. In December 2006, self-administered questionnaires were sent to 31,237 eligible community-dwelling individuals (response rate: 73.9%). Included in the analysis were 21,736 participants. Five neighborhood social capital variables were calculated from individual civic networks, sports and hobby networks, volunteer networks, friendship networks and social support variables. We used multilevel logistic regression models to estimate the odds ratio (OR) of having 20 or more teeth according to neighborhood social capital variables with adjustment for sex, age, individual social networks and social support, educational attainment, neighborhood educational level, dental health behavior, smoking status, history of diabetes and self-rated health. The average age of the participants was 74.9 (standard deviation; 6.6) years, and 28.5% of them had 20 or more teeth. In the univariate multilevel model, there were statistically significant associations between neighborhood sports and hobby networks, friendship networks and self-reported dentate status. In the multivariable multilevel model, compared with participants living in lowest friendship network neighborhoods, those living in highest friendship network neighborhoods had an OR 1.17 (95% confidence interval, 1.04-1.30) times higher for having 20 or more teeth. There is a significant association between one network aspect of neighborhood social capital and individual dentate status regardless of individual social networks and social support. © 2010 John Wiley & Sons A/S.

Subjective well-being associated with size of social network and social support of elderly.

PubMed

Wang, Xingmin

2016-06-01

The current study examined the impact of size of social network on subjective well-being of elderly, mainly focused on confirmation of the mediator role of perceived social support. The results revealed that both size of social network and perceived social support were significantly correlated with subjective well-being. Structural equation modeling indicated that perceived social support partially mediated size of social network to subjective well-being. The final model also revealed significant both paths from size of social network to subjective well-being through perceived social support. The findings extended prior researches and provided valuable evidence on how to promote mental health of the elderly. © The Author(s) 2014.

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

PubMed

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

2016-04-01

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. 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. 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. Although friends are part of Latina breast cancer survivors' social networks, spouses and children may provide greater support for healthy eating than friends. 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.

Social networks, migration, and HIV testing among Latinos in a new immigrant destination: Insights from a qualitative study.

PubMed

Barrington, Clare; Gandhi, Anisha; Gill, Adrienne; Villa Torres, Laura; Brietzke, Maria Priscila; Hightow-Weidman, Lisa

2017-12-03

Latinos in the U.S. are disproportionately affected by HIV and are more likely than non-Latinos to present with a late diagnosis, which delays engagement in HIV care and treatment. Social networks may provide normative influence and social support for HIV testing, but a contextualised understanding of networks is needed in order to maximise these social resources. We conducted qualitative interviews with foreign-born Latino men and transgender women (n = 17) in a new immigrant destination to explore their social networks. Most participants described having smaller social networks after migrating. Networks included both local and transnational ties, but most participants had few close ties. Contextual factors including stigma and geographic dispersion limited the re-construction of networks with close ties after migration. HIV testing was not a common topic of discussion with social network ties. Efforts to improve early uptake of HIV testing among Latino immigrants may benefit from engaging with social networks, but such efforts need to address how the context in which networks operate enables access to testing.

Methods for inferring health-related social networks among coworkers from online communication patterns.

PubMed

Matthews, Luke J; DeWan, Peter; Rula, Elizabeth Y

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network.

Methods for Inferring Health-Related Social Networks among Coworkers from Online Communication Patterns

PubMed Central

Matthews, Luke J.; DeWan, Peter; Rula, Elizabeth Y.

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network. PMID:23418436

Loneliness and social isolation among young and late middle-age adults: Associations with personal networks and social participation.

PubMed

Child, Stephanie T; Lawton, Leora

2017-11-24

Associations between social networks and loneliness or social isolation are well established among older adults. Yet, limited research examines personal networks and participation on perceived loneliness and social isolation as distinct experiences among younger adults. Accordingly, we explore relationships among objective and subjective measures of personal networks with loneliness and isolation, comparing a younger and older cohort. The UC Berkeley Social Networks Study offers unique cohort data on young (21-30 years old, n = 472) and late middle-age adults' (50-70 years old, n = 637) personal network characteristics, social participation, network satisfaction, relationship status, and days lonely and isolated via online survey or in-person interview. Negative binomial regression models were used to examine associations between social network characteristics, loneliness, and isolation by age group. Young adults reported twice as many days lonely and isolated than late middle-age adults, despite, paradoxically, having larger networks. For young adults, informal social participation and weekly religious attendance were associated with fewer days isolated. Among late middle-age adults, number of close kin and relationship status were associated with loneliness. Network satisfaction was associated with fewer days lonely or isolated among both age groups. Distinct network characteristics were associated with either loneliness or isolation for each cohort, suggesting network factors are independently associated with each outcome, and may fluctuate over time. Network satisfaction was associated with either loneliness or isolation among both cohorts, suggesting perceptions of social networks may be equally important as objective measures, and remain salient for loneliness and isolation throughout the life course.

An Introduction to Social Network Data Analytics

NASA Astrophysics Data System (ADS)

Aggarwal, Charu C.

The advent of online social networks has been one of the most exciting events in this decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have become increasingly popular. In addition, a number of multimedia networks such as Flickr have also seen an increasing level of popularity in recent years. Many such social networks are extremely rich in content, and they typically contain a tremendous amount of content and linkage data which can be leveraged for analysis. The linkage data is essentially the graph structure of the social network and the communications between entities; whereas the content data contains the text, images and other multimedia data in the network. The richness of this network provides unprecedented opportunities for data analytics in the context of social networks. This book provides a data-centric view of online social networks; a topic which has been missing from much of the literature. This chapter provides an overview of the key topics in this field, and their coverage in this book.

A generational comparison of social networking site use: the influence of age and social identity.

PubMed

Barker, Valerie

2012-01-01

An online survey (N=256) compared social networking site (SNS) use among younger (millennial: 18-29) and older (baby-boomer: 41-64) subscribers focusing on the influence of collective self-esteem and group identity on motives for SNS use. Younger participants reported higher positive collective self-esteem, social networking site use for peer communication, and social compensation. Regardless of age, participants reporting high collective self-esteem and group identity were more likely to use social networking sites for peer communication and social identity gratifications, while those reporting negative collective self-esteem were more likely to use social networking sites for social compensation. The theoretical implications of the strong relationship between social identity gratifications and social compensation are discussed.

Social Media: Strategic Asset or Operational Vulnerability?

DTIC Science & Technology

2012-05-04

Marine Corps message indicated that social networking sites “are particularly high risk due to information exposure, user generated content, and...Immediate Ban of Internet Social Networking Sites on Marine Corps Enterprise Network NIPRNET,” U.S. Marine Corps, accessed April 3, 2012, http... networking sites via the DoD’s unclassified computer network. The memorandum provided guidance on official use of social networking sites as well

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 support differentially moderates the impact of neuroticism and extraversion on mental wellbeing among community-dwelling older adults.

PubMed

McHugh, J E; Lawlor, B A

2012-10-01

Personality affects psychological wellbeing, and social support networks may mediate this effect. This may be particularly pertinent in later life, when social structures change significantly, and can lead to a decline in psychological wellbeing. To examine, in an older population, whether the relationships between neuroticism and extraversion and mental wellbeing are moderated by available social support networks. We gathered information from 536 community-dwelling older adults, regarding personality, social support networks, depressive symptomatology, anxiety and perceived stress, as well as controlling for age and gender. Neuroticism and extraversion interacted with social support networks to determine psychological wellbeing (depression, stress and anxiety). High scores on the social support networks measure appear to be protective against the deleterious effects of high scores on the neuroticism scale on psychological wellbeing. Meanwhile, individuals high in extraversion appear to require large social support networks in order to maintain psychological wellbeing. Large familial and friendship social support networks are associated with good psychological wellbeing. To optimise psychological wellbeing in older adults, improving social support networks may be differentially effective for different personality types.

Who gets evicted? Assessing individual, neighborhood, and network factors.

PubMed

Desmond, Matthew; Gershenson, Carl

2017-02-01

The prevalence and consequences of eviction have transformed the lived experience of urban poverty in America, yet little is known about why some families avoid eviction while others do not. Applying discrete hazard models to a unique dataset of renters, this study empirically evaluates individual, neighborhood, and social network characteristics that explain disparities in displacement from housing. Family size, job loss, neighborhood crime and eviction rates, and network disadvantage are identified as significant and robust predictors of eviction, net of missed rental payments and other relevant factors. This study advances urban sociology and inequality research and informs policy interventions designed to prevent eviction and stem its consequences. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

International Scholarship Graduates Influencing Social and Economic Development at Home: The Role of Alumni Networks in Georgia and Moldova

ERIC Educational Resources Information Center

Campbell, Anne C.

2016-01-01

Many students from low- and middle-income countries seek scholarship support to pursue higher education overseas. Often scholarship programs mandate that recipients "give back" to their home countries following their studies so scholars "apply" their experiences to aid their countries of origin. In this comparative qualitative…

Measuring Interactions among Research Grant Recipients through Social Network Analysis: Insights into Evaluating and Improving Research Collaborations

ERIC Educational Resources Information Center

Barron, Gary; Scarlett-Ferguson, Heather; Aspen, Cathy

2015-01-01

Alberta Health Services (AHS) was awarded a grant from the Alberta Ministry of Human Services to promote applied mental health research within areas of interest to the Ministry. The grant funded the "Collaborative Research Grant Initiative: Mental Wellness in Seniors and Persons with Disabilities" (CRGI), designed to collaboratively…

Comparing the Social Knowledge Construction Behavioral Patterns of Problem-Based Online Asynchronous Discussion in E/M-Learning Environments

ERIC Educational Resources Information Center

Lan, Yu-Feng; Tsai, Pei-Wei; Yang, Shih-Hsien; Hung, Chun-Ling

2012-01-01

In recent years, researchers have conducted various studies on applying wireless networking technology and mobile devices in education settings. However, research on behavioral patterns in learners' online asynchronous discussions with mobile devices is limited. The purposes of this study are to develop a mobile learning system, mobile interactive…

Optimal Network for Patients with Severe Mental Illness: A Social Network Analysis.

PubMed

Lorant, Vincent; Nazroo, James; Nicaise, Pablo

2017-11-01

It is still unclear what the optimal structure of mental health care networks should be. We examine whether certain types of network structure have been associated with improved continuity of care and greater social integration. A social network survey was carried out, covering 954 patients across 19 mental health networks in Belgium in 2014. We found continuity of care to be associated with large, centralized, and homophilous networks, whereas social integration was associated with smaller, centralized, and heterophilous networks. Two important goals of mental health service provision, continuity of care and social integration, are associated with different types of network. Further research is needed to ascertain the direction of this association.