Investigation of Spatial Data with Open Source Social Network Analysis and Geographic Information Systems Applications

NASA Astrophysics Data System (ADS)

Sabah, L.; Şimşek, M.

2017-11-01

Social networks are the real social experience of individuals in the online environment. In this environment, people use symbolic gestures and mimics, sharing thoughts and content. Social network analysis is the visualization of complex and large quantities of data to ensure that the overall picture appears. It is the understanding, development, quantitative and qualitative analysis of the relations in the social networks of Graph theory. Social networks are expressed in the form of nodes and edges. Nodes are people/organizations, and edges are relationships between nodes. Relations are directional, non-directional, weighted, and weightless. The purpose of this study is to examine the effects of social networks on the evaluation of person data with spatial coordinates. For this, the cluster size and the effect on the geographical area of the circle where the placements of the individual are influenced by the frequently used placeholder feature in the social networks have been studied.

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.

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

ERIC Educational Resources Information Center

Grunspan, Daniel Z.; Wiggins, Benjamin L.; Goodreau, Steven M.

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA)…

Semantic Networks and Social Networks

ERIC Educational Resources Information Center

Downes, Stephen

2005-01-01

Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

Disclosing Sexual Assault Within Social Networks: A Mixed-Method Investigation.

PubMed

Dworkin, Emily R; Pittenger, Samantha L; Allen, Nicole E

2016-03-01

Most survivors of sexual assault disclose their experiences within their social networks, and these disclosure decisions can have important implications for their entry into formal systems and well-being, but no research has directly examined these networks as a strategy to understand disclosure decisions. Using a mixed-method approach that combined survey data, social network analysis, and interview data, we investigate whom, among potential informal responders in the social networks of college students who have experienced sexual assault, survivors contact regarding their assault, and how survivors narrate the role of networks in their decisions about whom to contact. Quantitative results suggest that characteristics of survivors, their social networks, and members of these networks are associated with disclosure decisions. Using data from social network analysis, we identified that survivors tended to disclose to a smaller proportion of their network when many network members had relationships with each other or when the network had more subgroups. Our qualitative analysis helps to contextualize these findings. © Society for Community Research and Action 2016.

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

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

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

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.

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

Comparing Social Network Analysis of Posts with Counting of Posts as a Measurement of Learners' Participation in Facebook Discussions

ERIC Educational Resources Information Center

Lee, Hye Yeon; Lee, Hyeon Woo

2016-01-01

With the currently growing interest in social network services, many college courses use social network services as platforms for discussions, and a number of studies have been conducted on the use of social network analysis to measure students' participation in online discussions. This study aims to demonstrate the difference between counting…

A Social Network Analysis of Teaching and Research Collaboration in a Teachers' Virtual Learning Community

ERIC Educational Resources Information Center

Lin, Xiaofan; Hu, Xiaoyong; Hu, Qintai; Liu, Zhichun

2016-01-01

Analysing the structure of a social network can help us understand the key factors influencing interaction and collaboration in a virtual learning community (VLC). Here, we describe the mechanisms used in social network analysis (SNA) to analyse the social network structure of a VLC for teachers and discuss the relationship between face-to-face…

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…

Social Insects: A Model System for Network Dynamics

NASA Astrophysics Data System (ADS)

Charbonneau, Daniel; Blonder, Benjamin; Dornhaus, Anna

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

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.

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.…

Enabling Community Through Social Media

PubMed Central

Haythornthwaite, Caroline

2013-01-01

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

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

PubMed

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

2012-05-01

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

African American Extended Family and Church-Based Social Network Typologies.

PubMed

Nguyen, Ann W; Chatters, Linda M; Taylor, Robert Joseph

2016-12-01

We examined social network typologies among African American adults and their sociodemographic correlates. Network types were derived from indicators of the family and church networks. Latent class analysis was based on a nationally representative sample of African Americans from the National Survey of American Life. Results indicated four distinct network types: ambivalent, optimal, family centered, and strained. These four types were distinguished by (a) degree of social integration, (b) network composition, and (c) level of negative interactions. In a departure from previous work, a network type composed solely of nonkin was not identified, which may reflect racial differences in social network typologies. Further, the analysis indicated that network types varied by sociodemographic characteristics. Social network typologies have several promising practice implications, as they can inform the development of prevention and intervention programs.

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…

75 FR 48369 - Notice of Intent To Seek Approval To Establish an Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-10

... INFORMATION: Title of Collection: A Social Network Analysis of the National Science Foundation's Research and... Office of Management and Budget (OMB) for review and approval. A Social Network Analysis of the National... programs. The primary objectives of the study are to conduct a social network analysis of the REESE and DR...

Fluid Centrality: A Social Network Analysis of Social-Technical Relations in Computer-Mediated Communication

ERIC Educational Resources Information Center

Enriquez, Judith Guevarra

2010-01-01

In this article, centrality is explored as a measure of computer-mediated communication (CMC) in networked learning. Centrality measure is quite common in performing social network analysis (SNA) and in analysing social cohesion, strength of ties and influence in CMC, and computer-supported collaborative learning research. It argues that measuring…

In Search of Practitioner-Based Social Capital: A Social Network Analysis Tool for Understanding and Facilitating Teacher Collaboration in a US-Based STEM Professional Development Program

ERIC Educational Resources Information Center

Baker-Doyle, Kira J.; Yoon, Susan A.

2011-01-01

This paper presents the first in a series of studies on the informal advice networks of a community of teachers in an in-service professional development program. The aim of the research was to use Social Network Analysis as a methodological tool to reveal the social networks developed by the teachers, and to examine whether these networks…

Egocentric Social Network Analysis of Pathological Gambling

PubMed Central

Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.

2012-01-01

Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

Egocentric social network analysis of pathological gambling.

PubMed

Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

2013-03-01

To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

Static, Dynamic and Semantic Dimensions: Towards a Multidisciplinary Approach of Social Networks Analysis

NASA Astrophysics Data System (ADS)

Thovex, Christophe; Trichet, Francky

The objective of our work is to extend static and dynamic models of Social Networks Analysis (SNA), by taking conceptual aspects of enterprises and institutions social graph into account. The originality of our multidisciplinary work is to introduce abstract notions of electro-physic to define new measures in SNA, for new decision-making functions dedicated to Human Resource Management (HRM). This paper introduces a multidimensional system and new measures: (1) a tension measure for social network analysis, (2) an electrodynamic, predictive and semantic system for recommendations on social graphs evolutions and (3) a reactance measure used to evaluate the individual stress at work of the members of a social network.

Forensic analysis of social networking application on iOS devices

NASA Astrophysics Data System (ADS)

Zhang, Shuhui; Wang, Lianhai

2013-12-01

The increased use of social networking application on iPhone and iPad make these devices a goldmine for forensic investigators. Besides, QQ, Wechat, Sina Weibo and skype applications are very popular in China and didn't draw attention to researchers. These social networking applications are used not only on computers, but also mobile phones and tablets. This paper focuses on conducting forensic analysis on these four social networking applications on iPhone and iPad devices. The tests consisted of installing the social networking applications on each device, conducting common user activities through each application and correlation analysis with other activities. Advices to the forensic investigators are also given. It could help the investigators to describe the crime behavior and reconstruct the crime venue.

Social network types among older Korean adults: Associations with subjective health.

PubMed

Sohn, Sung Yun; Joo, Won-Tak; Kim, Woo Jung; Kim, Se Joo; Youm, Yoosik; Kim, Hyeon Chang; Park, Yeong-Ran; Lee, Eun

2017-01-01

With population aging now a global phenomenon, the health of older adults is becoming an increasingly important issue. Because the Korean population is aging at an unprecedented rate, preparing for public health problems associated with old age is particularly salient in this country. As the physical and mental health of older adults is related to their social relationships, investigating the social networks of older adults and their relationship to health status is important for establishing public health policies. The aims of this study were to identify social network types among older adults in South Korea and to examine the relationship of these social network types with self-rated health and depression. Data from the Korean Social Life, Health, and Aging Project were analyzed. Model-based clustering using finite normal mixture modeling was conducted to identify the social network types based on ten criterion variables of social relationships and activities: marital status, number of children, number of close relatives, number of friends, frequency of attendance at religious services, attendance at organized group meetings, in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality. Multivariate regression analysis was conducted to examine associations between the identified social network types and self-rated health and depression. The model-based clustering analysis revealed that social networks clustered into five types: diverse, family, congregant, congregant-restricted, and restricted. Diverse or family social network types were significantly associated with more favorable subjective mental health, whereas the restricted network type was significantly associated with poorer ratings of mental and physical health. In addition, our analysis identified unique social network types related to religious activities. In summary, we developed a comprehensive social network typology for older Korean adults. Copyright © 2016 Elsevier Ltd. All rights reserved.

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).

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

Introduction to Social Network Analysis

NASA Astrophysics Data System (ADS)

Zaphiris, Panayiotis; Ang, Chee Siang

Social Network analysis focuses on patterns of relations between and among people, organizations, states, etc. It aims to describe networks of relations as fully as possible, identify prominent patterns in such networks, trace the flow of information through them, and discover what effects these relations and networks have on people and organizations. Social network analysis offers a very promising potential for analyzing human-human interactions in online communities (discussion boards, newsgroups, virtual organizations). This Tutorial provides an overview of this analytic technique and demonstrates how it can be used in Human Computer Interaction (HCI) research and practice, focusing especially on Computer Mediated Communication (CMC). This topic acquires particular importance these days, with the increasing popularity of social networking websites (e.g., youtube, myspace, MMORPGs etc.) and the research interest in studying them.

Mobilizing Homeless Youth for HIV Prevention: A Social Network Analysis of the Acceptability of a Face-to-Face and Online Social Networking Intervention

ERIC Educational Resources Information Center

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Adhikari, Anamika Barman; Milburn, Norweeta G.

2012-01-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth. Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F…

Community evolution mining and analysis in social network

NASA Astrophysics Data System (ADS)

Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

2017-03-01

With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education

ERIC Educational Resources Information Center

Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav

2016-01-01

Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

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

Structural and functional social network attributes moderate the association of self-rated health with mental health in midlife and older adults.

PubMed

Windsor, Tim D; Rioseco, Pilar; Fiori, Katherine L; Curtis, Rachel G; Booth, Heather

2016-01-01

Social relationships are multifaceted, and different social network components can operate via different processes to influence well-being. This study examined associations of social network structure and relationship quality (positive and negative social exchanges) with mental health in midlife and older adults. The focus was on both direct associations of network structure and relationship quality with mental health, and whether these social network attributes moderated the association of self-rated health (SRH) with mental health. Analyses were based on survey data provided by 2001 (Mean age = 65, SD = 8.07) midlife and older adults. We used Latent Class Analysis (LCA) to classify participants into network types based on network structure (partner status, network size, contact frequency, and activity engagement), and used continuous measures of positive and negative social exchanges to operationalize relationship quality. Regression analysis was used to test moderation. LCA revealed network types generally consistent with those reported in previous studies. Participants in more diverse networks reported better mental health than those categorized into a restricted network type after adjustment for age, sex, education, and employment status. Analysis of moderation indicated that those with poorer SRH were less likely to report poorer mental health if they were classified into more diverse networks. A similar moderation effect was also evident for positive exchanges. The findings suggest that both quantity and quality of social relationships can play a role in buffering against the negative implications of physical health decline for mental health.

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.

The Social Networks of Small Arms Proliferation: Mapping an Aviation Enabled Supply Chain

DTIC Science & Technology

2007-12-01

each of the discrete arms 248 Wouter de Nooy, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social...303 Wouter de Nooy, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social Network Analysis with Pajek, 101. 304 Ibid., 21. 93 entity. The data...305 Wouter de Nooy, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social Network Analysis with Pajek, 101. 306 Linton C. Freeman, "Graphical

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

ERIC Educational Resources Information Center

Thornton, Teresa; Leahy, Jessica

2012-01-01

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,…

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

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

Social Network Analysis to Evaluate an Interdisciplinary Research Center

ERIC Educational Resources Information Center

Aboelela, Sally W.; Merrill, Jacqueline A.; Carley, Kathleen M.; Larson, Elaine

2007-01-01

We sought to examine the growth of an interdisciplinary center using social network analysis techniques. Specific aims were to examine the patterns of growth and interdisciplinary connectedness of the Center and to identify the social network characteristics of its productive members. The setting for this study was The Center for Interdisciplinary…

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

PubMed

Valente, Thomas W; Pitts, Stephanie R

2017-03-20

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

Social network analysis for program implementation.

PubMed

Valente, Thomas W; Palinkas, Lawrence A; Czaja, Sara; Chu, Kar-Hai; Brown, C Hendricks

2015-01-01

This paper introduces the use of social network analysis theory and tools for implementation research. The social network perspective is useful for understanding, monitoring, influencing, or evaluating the implementation process when programs, policies, practices, or principles are designed and scaled up or adapted to different settings. We briefly describe common barriers to implementation success and relate them to the social networks of implementation stakeholders. We introduce a few simple measures commonly used in social network analysis and discuss how these measures can be used in program implementation. Using the four stage model of program implementation (exploration, adoption, implementation, and sustainment) proposed by Aarons and colleagues [1] and our experience in developing multi-sector partnerships involving community leaders, organizations, practitioners, and researchers, we show how network measures can be used at each stage to monitor, intervene, and improve the implementation process. Examples are provided to illustrate these concepts. We conclude with expected benefits and challenges associated with this approach.

Social Network Analysis for Program Implementation

PubMed Central

Valente, Thomas W.; Palinkas, Lawrence A.; Czaja, Sara; Chu, Kar-Hai; Brown, C. Hendricks

2015-01-01

This paper introduces the use of social network analysis theory and tools for implementation research. The social network perspective is useful for understanding, monitoring, influencing, or evaluating the implementation process when programs, policies, practices, or principles are designed and scaled up or adapted to different settings. We briefly describe common barriers to implementation success and relate them to the social networks of implementation stakeholders. We introduce a few simple measures commonly used in social network analysis and discuss how these measures can be used in program implementation. Using the four stage model of program implementation (exploration, adoption, implementation, and sustainment) proposed by Aarons and colleagues [1] and our experience in developing multi-sector partnerships involving community leaders, organizations, practitioners, and researchers, we show how network measures can be used at each stage to monitor, intervene, and improve the implementation process. Examples are provided to illustrate these concepts. We conclude with expected benefits and challenges associated with this approach. PMID:26110842

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention.

PubMed

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G

2012-04-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future.

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention

PubMed Central

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G.

2012-01-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future. PMID:22247453

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.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

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.

75 FR 9158 - Proposed Information Collection; Comment Request; Identification of Northeast Regional Ocean...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-01

... Collection; Comment Request; Identification of Northeast Regional Ocean Council Information Network Using Social Network Analysis AGENCY: National Oceanic and Atmospheric Administration (NOAA). ACTION: Notice... in many capacities. A social network analysis will serve to identify the network of people working on...

Automated Run-Time Mission and Dialog Generation

DTIC Science & Technology

2007-03-01

Processing, Social Network Analysis, Simulation, Automated Scenario Generation 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified...9 D. SOCIAL NETWORKS...13 B. MISSION AND DIALOG GENERATION.................................................13 C. SOCIAL NETWORKS

Narcissism and Social Networking Behavior: A Meta-Analysis.

PubMed

Gnambs, Timo; Appel, Markus

2018-04-01

The increasing popularity of social networking sites (SNS) such as Facebook and Twitter has given rise to speculations that the intensity of using these platforms is associated with narcissistic tendencies. However, recent research on this issue has been all but conclusive. We present a three-level, random effects meta-analysis including 289 effect sizes from 57 studies (total N = 25,631) on the association between trait narcissism and social networking behavior. The meta-analysis identified a small to moderate effect of ρ = .17 (τ = .11), 95% CI [.13, .21], for grandiose narcissism that replicated across different social networking platforms, respondent characteristics, and time. Moderator analyses revealed pronounced cultural differences, with stronger associations in power-distant cultures. Moreover, social networking behaviors geared toward self-presentation and the number of SNS friends exhibited stronger effects than usage durations. Overall, the study not only supported but also refined the notion of a relationship between engaging in social networking sites and narcissistic personality traits. © 2017 Wiley Periodicals, Inc.

Social Network Analysis: A New Methodology for Counseling Research.

ERIC Educational Resources Information Center

Koehly, Laura M.; Shivy, Victoria A.

1998-01-01

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

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).

Searching social networks for subgraph patterns

NASA Astrophysics Data System (ADS)

Ogaard, Kirk; Kase, Sue; Roy, Heather; Nagi, Rakesh; Sambhoos, Kedar; Sudit, Moises

2013-06-01

Software tools for Social Network Analysis (SNA) are being developed which support various types of analysis of social networks extracted from social media websites (e.g., Twitter). Once extracted and stored in a database such social networks are amenable to analysis by SNA software. This data analysis often involves searching for occurrences of various subgraph patterns (i.e., graphical representations of entities and relationships). The authors have developed the Graph Matching Toolkit (GMT) which provides an intuitive Graphical User Interface (GUI) for a heuristic graph matching algorithm called the Truncated Search Tree (TruST) algorithm. GMT is a visual interface for graph matching algorithms processing large social networks. GMT enables an analyst to draw a subgraph pattern by using a mouse to select categories and labels for nodes and links from drop-down menus. GMT then executes the TruST algorithm to find the top five occurrences of the subgraph pattern within the social network stored in the database. GMT was tested using a simulated counter-insurgency dataset consisting of cellular phone communications within a populated area of operations in Iraq. The results indicated GMT (when executing the TruST graph matching algorithm) is a time-efficient approach to searching large social networks. GMT's visual interface to a graph matching algorithm enables intelligence analysts to quickly analyze and summarize the large amounts of data necessary to produce actionable intelligence.

Data Acquisition and Preparation for Social Network Analysis Based on Email: Lessons Learned

DTIC Science & Technology

2009-06-01

Mrvar , A., and Batagelj , V. (2005), Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences series). Cambridge, New...visualization of large networks. This program was developed by Vladimir Batagelj and Andrej Mrvar of the University of Ljubljana in Slovenia. Pajek evolved...theory, presumes Wasserman & Faust as foundation Amazon: 55% purchase rate among viewers 5. de Nooy, W., Mrvar , A., and Batagelj , V. (2005

Lessons from social network analyses for behavioral medicine.

PubMed

Rosenquist, James N

2011-03-01

This study presents an overview of the rapidly expanding field of social network analysis, with an emphasis placed on work relevant to behavioral health clinicians and researchers. I outline how social network analysis is a distinct empirical methodology within the social sciences that has the potential to deepen our understanding of how mental health and addiction are influenced by social environmental factors. Whereas there have been a number of recent studies in the mental health literature that discuss social influences on mental illness and addiction, and a number of studies looking at how social networks influence health and behaviors, there are still relatively few studies that combine the two. Those that have suggest that mood symptoms as well as alcohol consumption are clustered within, and may travel along, social networks. Social networks appear to have an important influence on a variety of mental health conditions. This avenue of research has the potential to influence both clinical practice and public policy.

Analysing Health Professionals' Learning Interactions in an Online Social Network: A Longitudinal Study.

PubMed

Li, Xin; Verspoor, Karin; Gray, Kathleen; Barnett, Stephen

2016-01-01

This paper summarises a longitudinal analysis of learning interactions occurring over three years among health professionals in an online social network. The study employs the techniques of Social Network Analysis (SNA) and statistical modeling to identify the changes in patterns of interaction over time and test associated structural network effects. SNA results indicate overall low participation in the network, although some participants became active over time and even led discussions. In particular, the analysis has shown that a change of lead contributor results in a change in learning interaction and network structure. The analysis of structural network effects demonstrates that the interaction dynamics slow down over time, indicating that interactions in the network are more stable. The health professionals may be reluctant to share knowledge and collaborate in groups but were interested in building personal learning networks or simply seeking information.

Improving Family Forest Knowledge Transfer through Social Network Analysis

ERIC Educational Resources Information Center

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

2012-01-01

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

A Network Optimization Approach for Improving Organizational Design

DTIC Science & Technology

2004-01-01

functions, Dynamic Network Analysis, Social Network Analysis Abstract Organizations are frequently designed and redesigned, often in...links between sites on the web. Hence a change in any one of the four networks in which people are involved can potentially result in a cascade of...in terms of a set of networks that open the possibility of using all networks (both social and dynamic network measures) as indicators of potential

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

Exploring the Peer Interaction Effects on Learning Achievement in a Social Learning Platform Based on Social Network Analysis

ERIC Educational Resources Information Center

Lin, Yu-Tzu; Chen, Ming-Puu; Chang, Chia-Hu; Chang, Pu-Chen

2017-01-01

The benefits of social learning have been recognized by existing research. To explore knowledge distribution in social learning and its effects on learning achievement, we developed a social learning platform and explored students' behaviors of peer interactions by the proposed algorithms based on social network analysis. An empirical study was…

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

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

A social network analysis of alcohol-impaired drivers in Maryland : an egocentric approach.

DOT National Transportation Integrated Search

2011-04-01

This study examined the personal, household, and social structural attributes of alcoholimpaired : drivers in Maryland. The study used an egocentric approach of social network : analysis. This approach concentrated on specific actors (alcohol-impaire...

Perspectives on Social Network Analysis for Observational Scientific Data

NASA Astrophysics Data System (ADS)

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

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

The Influence of Social Networking Sites on High School Students' Social and Academic Development

ERIC Educational Resources Information Center

Ahn, June

2010-01-01

This dissertation examines the effects of social network sites on youth social and academic development. First, I provide a critical analysis of the extant research literature surrounding social network sites and youth. I merge scholarly thought in the areas of Internet studies, digital divides, social capital theory, psychological well-being,…

Social Network Changes and Life Events across the Life Span: A Meta-Analysis

ERIC Educational Resources Information Center

Wrzus, Cornelia; Hanel, 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…

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.

Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review

ERIC Educational Resources Information Center

Cela, Karina L.; Sicilia, Miguel Ángel; Sánchez, Salvador

2015-01-01

E-learning occupies an increasingly prominent place in education. It provides the learner with a rich virtual network where he or she can exchange ideas and information and create synergies through interactions with other members of the network, whether fellow learners or teachers. Social network analysis (SNA) has proven extremely powerful at…

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

DTIC Science & Technology

2017-11-29

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

Optimization Techniques for Analysis of Biological and Social Networks

DTIC Science & Technology

2012-03-28

analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms , test and fine...alternative mathematical programming formulations, their theoretical analysis, the development of exact algorithms , and heuristics. Originally, clusters...systematic fashion under a unifying theoretical and algorithmic framework. Optimization, Complex Networks, Social Network Analysis, Computational

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 Mourning: A Comparative Approach.

ERIC Educational Resources Information Center

Rubin, Nissan

1990-01-01

Suggests using social network theory to explain varieties of mourning behavior in different societies. Compares participation in funeral ceremonies of members of different social circles in American society and Israeli kibbutz. Concludes that results demonstrated validity of concepts deriving from social network analysis in study of bereavement,…

The effect of excluding juveniles on apparent adult olive baboons (Papio anubis) social networks

PubMed Central

Fedurek, Piotr; Lehmann, Julia

2017-01-01

In recent years there has been much interest in investigating the social structure of group living animals using social network analysis. Many studies so far have focused on the social networks of adults, often excluding younger, immature group members. This potentially may lead to a biased view of group social structure as multiple recent studies have shown that younger group members can significantly contribute to group structure. As proof of the concept, we address this issue by investigating social network structure with and without juveniles in wild olive baboons (Papio anubis) at Gashaka Gumti National Park, Nigeria. Two social networks including all independently moving individuals (i.e., excluding dependent juveniles) were created based on aggressive and grooming behaviour. We used knockout simulations based on the random removal of individuals from the network in order to investigate to what extent the exclusion of juveniles affects the resulting network structure and our interpretation of age-sex specific social roles. We found that juvenile social patterns differed from those of adults and that the exclusion of juveniles from the network significantly altered the resulting overall network structure. Moreover, the removal of juveniles from the network affected individuals in specific age-sex classes differently: for example, including juveniles in the grooming network increased network centrality of adult females while decreasing centrality of adult males. These results suggest that excluding juveniles from the analysis may not only result in a distorted picture of the overall social structure but also may mask some of the social roles of individuals belonging to different age-sex classes. PMID:28323851

The effect of excluding juveniles on apparent adult olive baboons (Papio anubis) social networks.

PubMed

Fedurek, Piotr; Lehmann, Julia

2017-01-01

In recent years there has been much interest in investigating the social structure of group living animals using social network analysis. Many studies so far have focused on the social networks of adults, often excluding younger, immature group members. This potentially may lead to a biased view of group social structure as multiple recent studies have shown that younger group members can significantly contribute to group structure. As proof of the concept, we address this issue by investigating social network structure with and without juveniles in wild olive baboons (Papio anubis) at Gashaka Gumti National Park, Nigeria. Two social networks including all independently moving individuals (i.e., excluding dependent juveniles) were created based on aggressive and grooming behaviour. We used knockout simulations based on the random removal of individuals from the network in order to investigate to what extent the exclusion of juveniles affects the resulting network structure and our interpretation of age-sex specific social roles. We found that juvenile social patterns differed from those of adults and that the exclusion of juveniles from the network significantly altered the resulting overall network structure. Moreover, the removal of juveniles from the network affected individuals in specific age-sex classes differently: for example, including juveniles in the grooming network increased network centrality of adult females while decreasing centrality of adult males. These results suggest that excluding juveniles from the analysis may not only result in a distorted picture of the overall social structure but also may mask some of the social roles of individuals belonging to different age-sex classes.

Google matrix analysis of directed networks

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

Predicting and controlling infectious disease epidemics using temporal networks

PubMed Central

Holme, Petter

2013-01-01

Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments. PMID:23513178

Predicting and controlling infectious disease epidemics using temporal networks.

PubMed

Masuda, Naoki; Holme, Petter

2013-01-01

Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments.

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

PubMed

Shen, Zeqian; Ma, Kwan-Liu; Eliassi-Rad, Tina

2006-01-01

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

Investigating Student Communities with Network Analysis of Interactions in a Physics Learning Center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; O'Brien, George

2009-11-01

We describe our initial efforts at implementing social network analysis to visualize and quantify student interactions in Florida International University's Physics Learning Center. Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at FIU. Our implementation of a research and learning community, embedded within a course reform effort, has led to increased recruitment and retention of physics majors. Finn and Rock [1997] link the academic and social integration of students to increased rates of retention. To identify these interactions, we have initiated an investigation that utilizes social network analysis to identify primary community participants. Community interactions are then characterized through the network's density and connectivity, shedding light on learning communities and participation. Preliminary results, further research questions, and future directions utilizing social network analysis are presented.

Transfer of Training: Adding Insight through Social Network Analysis

ERIC Educational Resources Information Center

Van den Bossche, Piet; Segers, Mien

2013-01-01

This article reviews studies which apply a social network perspective to examine transfer of training. The theory behind social networks focuses on the interpersonal mechanisms and social structures that exist among interacting units such as people within an organization. A premise of this perspective is that individual's behaviors and outcomes…

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

ERIC Educational Resources Information Center

Lee, Moosung

2014-01-01

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

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.

Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction

PubMed Central

Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

2012-01-01

Social interactions are a very important component in people’s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links’ weights are a measure of the “influence” a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network. PMID:22438733

Nursing teams: behind the charts.

PubMed

Bae, Sung-Heui; Farasat, Alireza; Nikolaev, Alex; Seo, Jin Young; Foltz-Ramos, Kelly; Fabry, Donna; Castner, Jessica

2017-07-01

To examine the nature and characteristics of both received and provided mutual support in a social network within an acute care hospital unit. Current evidence regarding the social network in the health care workforce reveals the nature of social ties. Most studies of social network-related support that measured the characteristics of social support used self-reported perception from workers receiving support. There is a gap in studies that focus on back-up behaviour. The evaluation included a social network analysis of a nursing unit employing 54 staff members. A 12 item electronic survey was administered. Descriptive statistics were calculated using the Statistical Package for the Social Sciences. Social network analyses were carried out using ucinet, r 3.2.3 and gephi. Based on the study findings, as providers of mutual support the nursing staff claimed to give their peers more help than these peers gave them credit for. Those who worked overtime provided more mutual support. Mutual support is a key teamwork characteristic, essential to quality and safety in hospital nursing teams that can be evaluated using social network analysis. Because of a discrepancy regarding receiving and providing help, examining both receiver and provider networks is a superior approach to understanding mutual support. © 2017 John Wiley & Sons Ltd.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

#LancerHealth: Using Twitter and Instagram as a tool in a campus wide health promotion initiative

PubMed Central

Santarossa, Sara; Woodruff, Sarah J.

2018-01-01

The present study aimed to explore using popular technology that people already have/use as a health promotion tool, in a campus wide social media health promotion initiative, entitled #LancerHealth. During a two-week period the university community was asked to share photos on Twitter and Instagram of What does being healthy on campus look like to you?, while tagging the image with #LancerHealth. All publically tagged media was collected using the Netlytic software and analysed. Text analysis (N=234 records, Twitter; N=141 records, Instagram) revealed that the majority of the conversation was positive and focused on health and the university. Social network analysis, based on five network properties, showed a small network with little interaction. Lastly, photo coding analysis (N=71 unique image) indicated that the majority of the shared images were of physical activity (52%) and on campus (80%). Further research into this area is warranted. Significance for public healthAs digital media continues to become a popular tool among both public health organizations and those in academia, it is important to understand how, why, and which platforms individuals are using in regards to their health. This campus wide, social media health promotion initiative found that people will use popular social networking sites like Twitter and Instagram to share their healthy behaviours. Online social networks, created through social networking sites, can play a role in social diffusion of public health information and health behaviours. In this study, however, social network analysis revealed that there needs to be influential and highly connected individuals sharing information to generate social diffusion. This study can help guide future public health research in the area of social media and its potential influence on health promotion. PMID:29780763

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

PubMed Central

Wiggins, Benjamin L.; Goodreau, Steven M.

2014-01-01

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

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.

Harvesting Ego-Network Data from Facebook: Using the CEMAP Facebook Profile in ORA

DTIC Science & Technology

2009-02-02

Keywords: Facebook , CEMAP, social network , ORA, dynamic network analysis Abstract...The Facebook social networking site (www.facebook.com) has become a popular phenomenon over the past five years. By its nature, Facebook has...tableset. The Facebook tableset is the CEMAP abstraction of the various levels of technology to harvest the social network data, via the Facebook developer

Counting on Kin: Social Networks, Social Support, and Child Health Status

ERIC Educational Resources Information Center

Kana'iaupuni, Shawn Malia; Donato, Katharine M.; Thompson-Colon, Theresa; Stainback, Melissa

2005-01-01

This article presents the results of new data collection in Mexico about the relationship between child well-being and social networks. Two research questions guide the analysis. First, under what conditions do networks generate greater (lesser) support? Second, what kinds of networks are associated with healthier children? We explore the health…

The Changing Nature of Suicide Attacks: A Social Network Perspective

ERIC Educational Resources Information Center

Pedahzur, Ami; Perliger, Arie

2006-01-01

To comprehend the developments underlying the suicide attacks of recent years, we suggest that the organizational approach, which until recently was used to explain this phenomenon, should be complemented with a social network perspective. By employing a social network analysis of Palestinian suicide networks, the authors found that, in contrast…

Social Capital, Self-Esteem, and Use of Online Social Network Sites: A Longitudinal Analysis

ERIC Educational Resources Information Center

Steinfield, Charles; Ellison, Nicole B.; Lampe, Cliff

2008-01-01

A longitudinal analysis of panel data from users of a popular online social network site, Facebook, investigated the relationship between intensity of Facebook use, measures of psychological well-being, and bridging social capital. Two surveys conducted a year apart at a large U.S. university, complemented with in-depth interviews with 18 Facebook…

The neural representation of social networks.

PubMed

Weaverdyck, Miriam E; Parkinson, Carolyn

2018-05-24

The computational demands associated with navigating large, complexly bonded social groups are thought to have significantly shaped human brain evolution. Yet, research on social network representation and cognitive neuroscience have progressed largely independently. Thus, little is known about how the human brain encodes the structure of the social networks in which it is embedded. This review highlights recent work seeking to bridge this gap in understanding. While the majority of research linking social network analysis and neuroimaging has focused on relating neuroanatomy to social network size, researchers have begun to define the neural architecture that encodes social network structure, cognitive and behavioral consequences of encoding this information, and individual differences in how people represent the structure of their social world. Copyright © 2018 Elsevier Ltd. All rights reserved.

Using Social Network Measures in Wildlife Disease Ecology, Epidemiology, and Management

PubMed Central

Silk, Matthew J.; Croft, Darren P.; Delahay, Richard J.; Hodgson, David J.; Boots, Mike; Weber, Nicola; McDonald, Robbie A.

2017-01-01

Abstract Contact networks, behavioral interactions, and shared use of space can all have important implications for the spread of disease in animals. Social networks enable the quantification of complex patterns of interactions; therefore, network analysis is becoming increasingly widespread in the study of infectious disease in animals, including wildlife. We present an introductory guide to using social-network-analytical approaches in wildlife disease ecology, epidemiology, and management. We focus on providing detailed practical guidance for the use of basic descriptive network measures by suggesting the research questions to which each technique is best suited and detailing the software available for each. We also discuss how using network approaches can be used beyond the study of social contacts and across a range of spatial and temporal scales. Finally, we integrate these approaches to examine how network analysis can be used to inform the implementation and monitoring of effective disease management strategies. PMID:28596616

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.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Network Analysis in Comparative Social Sciences

ERIC Educational Resources Information Center

Vera, Eugenia Roldan; Schupp, Thomas

2006-01-01

This essay describes the pertinence of Social Network Analysis (SNA) for the social sciences in general, and discusses its methodological and conceptual implications for comparative research in particular. The authors first present a basic summary of the theoretical and methodological assumptions of SNA, followed by a succinct overview of its…

Leveraging Social Networks To Enhance Innovation

DTIC Science & Technology

This thesis explores the Department of the Navy’s innovation initiatives to determine how to leverage social networks to enhance innovation inside...the Navy. Using the results of a social network analysis that mapped and measured the informal Navy Innovation Network, and examining how other military...branches and industry pursue innovation , this qualitative research seeks to identify gaps and redundancies in the current Navy Innovation Network

Differential reward responses during competition against in- and out-of-network others.

PubMed

Fareri, Dominic S; Delgado, Mauricio R

2014-04-01

Social interactions occur within a variety of different contexts--cooperative/competitive--and often involve members of our social network. Here, we investigated whether social network modulated the value placed on positive outcomes during a competitive context. Eighteen human participants played a simple card-guessing game with three different competitors: a close friend (in-network), a confederate (out-of-network) and a random number generator (non-social condition) while undergoing functional magnetic resonance imaging. Neuroimaging results at the time of outcome receipt demonstrated a significant main effect of competitor across multiple regions of medial prefrontal cortex, with Blood Oxygen Level Dependent (BOLD) responses strongest when competing against one's friend compared with all other conditions. Striatal BOLD responses demonstrated a more general sensitivity to positive compared with negative monetary outcomes, which an exploratory analysis revealed to be stronger when interacting with social, compared with non-social, competitors. Interestingly, a Granger causality analysis indicated directed influences sent from an medial prefrontal cortex (mPFC) region, which shows social network differentiation of outcomes, and the ventral striatum bilaterally. Our results suggest that when competing against others of varying degrees of social network, mPFC differentially values these outcomes, perhaps treating in-network outcomes as more informative, leaving the striatum to more general value computations.

Differential reward responses during competition against in- and out-of-network others

PubMed Central

Fareri, Dominic S.

2014-01-01

Social interactions occur within a variety of different contexts––cooperative/competitive––and often involve members of our social network. Here, we investigated whether social network modulated the value placed on positive outcomes during a competitive context. Eighteen human participants played a simple card-guessing game with three different competitors: a close friend (in-network), a confederate (out-of-network) and a random number generator (non-social condition) while undergoing functional magnetic resonance imaging. Neuroimaging results at the time of outcome receipt demonstrated a significant main effect of competitor across multiple regions of medial prefrontal cortex, with Blood Oxygen Level Dependent (BOLD) responses strongest when competing against one’s friend compared with all other conditions. Striatal BOLD responses demonstrated a more general sensitivity to positive compared with negative monetary outcomes, which an exploratory analysis revealed to be stronger when interacting with social, compared with non-social, competitors. Interestingly, a Granger causality analysis indicated directed influences sent from an medial prefrontal cortex (mPFC) region, which shows social network differentiation of outcomes, and the ventral striatum bilaterally. Our results suggest that when competing against others of varying degrees of social network, mPFC differentially values these outcomes, perhaps treating in-network outcomes as more informative, leaving the striatum to more general value computations. PMID:23314007

Investigating student communities with network analysis of interactions in a physics learning center

NASA Astrophysics Data System (ADS)

Brewe, Eric; Kramer, Laird; Sawtelle, Vashti

2012-06-01

Developing a sense of community among students is one of the three pillars of an overall reform effort to increase participation in physics, and the sciences more broadly, at Florida International University. The emergence of a research and learning community, embedded within a course reform effort, has contributed to increased recruitment and retention of physics majors. We utilize social network analysis to quantify interactions in Florida International University’s Physics Learning Center (PLC) that support the development of academic and social integration. The tools of social network analysis allow us to visualize and quantify student interactions and characterize the roles of students within a social network. After providing a brief introduction to social network analysis, we use sequential multiple regression modeling to evaluate factors that contribute to participation in the learning community. Results of the sequential multiple regression indicate that the PLC learning community is an equitable environment as we find that gender and ethnicity are not significant predictors of participation in the PLC. We find that providing students space for collaboration provides a vital element in the formation of a supportive learning community.

[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.

Diversity of social ties in scientific collaboration networks

NASA Astrophysics Data System (ADS)

Shi, Quan; Xu, Bo; Xu, Xiaomin; Xiao, Yanghua; Wang, Wei; Wang, Hengshan

2011-11-01

Diversity is one of the important perspectives to characterize behaviors of individuals in social networks. It is intuitively believed that diversity of social ties accounts for competition advantage and idea innovation. However, quantitative evidences in a real large social network can be rarely found in the previous research. Thanks to the availability of scientific publication records on WWW; now we can construct a large scientific collaboration network, which provides us a chance to gain insight into the diversity of relationships in a real social network through statistical analysis. In this article, we dedicate our efforts to perform empirical analysis on a scientific collaboration network extracted from DBLP, an online bibliographic database in computer science, in a systematical way, finding the following: distributions of diversity indices tend to decay in an exponential or Gaussian way; diversity indices are not trivially correlated to existing vertex importance measures; authors of diverse social ties tend to connect to each other and these authors are generally more competitive than others.

Empirical analysis of online social networks in the age of Web 2.0

NASA Astrophysics Data System (ADS)

Fu, Feng; Liu, Lianghuan; Wang, Long

2008-01-01

Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

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

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

PubMed

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

2016-04-30

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

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

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

PubMed

Bray, Bethany C; Smith, Rachel A; Piper, Megan E; Roberts, Linda J; Baker, Timothy B

2016-12-01

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. 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. 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. 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. 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. © The Author 2016. 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.

Social power and opinion formation in complex networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2013-02-01

In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts-Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts-Strogatz networks could not significantly change the consensus profile.

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…

Fractal Inequality: A Social Network Analysis of Global and Regional International Student Mobility

ERIC Educational Resources Information Center

Macrander, Ashley

2017-01-01

Literature on global international student mobility (ISM) highlights the uneven nature of student flows--from the developing to the developed world--however, studies have yet to address whether this pattern is replicated within expanding regional networks. Utilizing social network analysis, UNESCO ISM data, and World Bank income classifications,…

Multiplex network analysis of employee performance and employee social relationships

NASA Astrophysics Data System (ADS)

Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene

2018-01-01

In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.

An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media.

PubMed

Wyllie, Jessica; Lucas, Benjamin; Carlson, Jamie; Kitchens, Brent; Kozary, Ben; Zaki, Mohamed

2016-01-01

Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed.

An Examination of Not-For-Profit Stakeholder Networks for Relationship Management: A Small-Scale Analysis on Social Media

PubMed Central

Carlson, Jamie; Kitchens, Brent; Kozary, Ben; Zaki, Mohamed

2016-01-01

Using a small-scale descriptive network analysis approach, this study highlights the importance of stakeholder networks for identifying valuable stakeholders and the management of existing stakeholders in the context of mental health not-for-profit services. We extract network data from the social media brand pages of three health service organizations from the U.S., U.K., and Australia, to visually map networks of 579 social media brand pages (represented by nodes), connected by 5,600 edges. This network data is analyzed using a collection of popular graph analysis techniques to assess the differences in the way each of the service organizations manage stakeholder networks. We also compare node meta-information against basic topology measures to emphasize the importance of effectively managing relationships with stakeholders who have large external audiences. Implications and future research directions are also discussed. PMID:27711236

Social traits, social networks and evolutionary biology.

PubMed

Fisher, D N; McAdam, A G

2017-12-01

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

Exploring Classroom Interaction with Dynamic Social Network Analysis

ERIC Educational Resources Information Center

Bokhove, Christian

2018-01-01

This article reports on an exploratory project in which technology and dynamic social network analysis (SNA) are used for modelling classroom interaction. SNA focuses on the links between social actors, draws on graphic imagery to reveal and display the patterning of those links, and develops mathematical and computational models to describe and…

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…

Ties that Bind: A Social Network Approach To Understanding Student Integration and Persistence.

ERIC Educational Resources Information Center

Thomas, Scott L.

2000-01-01

This study used a social network paradigm to examine college student integration of 329 college freshmen at a private liberal arts college. Analysis of the structural aspects of students' on-campus associations found differential effects of various social network characteristics on student commitment and persistence. (DB)

Social Networks, Communication Styles, and Learning Performance in a CSCL Community

ERIC Educational Resources Information Center

Cho, Hichang; Gay, Geri; Davidson, Barry; Ingraffea, Anthony

2007-01-01

The aim of this study is to empirically investigate the relationships between communication styles, social networks, and learning performance in a computer-supported collaborative learning (CSCL) community. Using social network analysis (SNA) and longitudinal survey data, we analyzed how 31 distributed learners developed collaborative learning…

Academics and Social Networking Sites: Benefits, Problems and Tensions in Professional Engagement with Online Networking

ERIC Educational Resources Information Center

Jordan, Katy; Weller, Martin

2018-01-01

The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a…

The Effect of Social Network Diagrams on a Virtual Network of Practice: A Korean Case

ERIC Educational Resources Information Center

Jo, Il-Hyun

2009-01-01

This study investigates the effect of the presentation of social network diagrams on virtual team members' interaction behavior via e-mail. E-mail transaction data from 22 software developers in a Korean IT company was analyzed and depicted as diagrams by social network analysis (SNA), and presented to the members as an intervention. Results…

Using Social Network Theory to Influence the Development of State and Local Primary Prevention Capacity-Building Teams

ERIC Educational Resources Information Center

Cook-Craig, Patricia G.

2010-01-01

This article examines the role that social network theory and social network analysis has played in assessing and developing effective primary prevention networks across a southeastern state. In 2004 the state began an effort to develop a strategic plan for the primary prevention of violence working with local communities across the state. The…

Social Media as a Communication Support for Persons with Mild Acquired Cognitive Impairment: A Social Network Analysis Study.

PubMed

Eghdam, Aboozar; Hamidi, Ulrika; Bartfai, Aniko; Koch, Sabine

2017-01-01

This study was conducted as a social network analysis of a Facebook group for Swedish speaking persons (1310 members) with perceived brain fatigue after an illness or injury to the brain to address the lack of research examining social media and the potential value of on-line support for persons with mild acquired cognitive impairment.

Determining Open Education Related Social Media Usage Trends in Turkey Using a Holistic Social Network Analysis

ERIC Educational Resources Information Center

Firat, Mehmet; Altinpulluk, Hakan; Kilinç, Hakan; Büyük, Köksal

2017-01-01

The aim of this study is to reveal Open Education related social media usage in Turkey through social network analyses. To this end, the most widely used social media network in Turkey, Facebook, was chosen. All the pages and groups created on Facebook related to Open Education were found. A total of 207 groups and 521 pages were accessed and…

[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.

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).

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.

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.

Battle of Narratives

DTIC Science & Technology

2012-06-01

18 De Nooy, Wouter, Andrej Mrvar , and Vladimir Batagelj , Exploratory Social Network Analysis with Pajek (New York: Cambridge University Press, 2005... Mrvar , and Vladimir Batagelj . Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press, 2005. Democratic National...Review 54(1):33-48; Brian Uzzi. 1996 . "The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect

Privacy Breach Analysis in Social Networks

NASA Astrophysics Data System (ADS)

Nagle, Frank

This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

Time Spent on Social Network Sites and Psychological Well-Being: A Meta-Analysis.

PubMed

Huang, Chiungjung

2017-06-01

This meta-analysis examines the relationship between time spent on social networking sites and psychological well-being factors, namely self-esteem, life satisfaction, loneliness, and depression. Sixty-one studies consisting of 67 independent samples involving 19,652 participants were identified. The mean correlation between time spent on social networking sites and psychological well-being was low at r = -0.07. The correlations between time spent on social networking sites and positive indicators (self-esteem and life satisfaction) were close to 0, whereas those between time spent on social networking sites and negative indicators (depression and loneliness) were weak. The effects of publication outlet, site on which users spent time, scale of time spent, and participant age and gender were not significant. As most included studies used student samples, future research should be conducted to examine this relationship for adults.

Attentional networks and visuospatial working memory capacity in social anxiety.

PubMed

Moriya, Jun

2018-02-01

Social anxiety is associated with attentional bias and working memory for emotional stimuli; however, the ways in which social anxiety affects cognitive functions involving non-emotional stimuli remains unclear. The present study focused on the role of attentional networks (i.e. alerting, orienting, and executive control networks) and visuospatial working memory capacity (WMC) for non-emotional stimuli in the context of social anxiety. One hundred and seventeen undergraduates completed questionnaires on social anxiety. They then performed an attentional network test and a change detection task to measure visuospatial WMC. Orienting network and visuospatial WMC were positively correlated with social anxiety. A multiple regression analysis showed significant positive associations of alerting, orienting, and visuospatial WMC with social anxiety. Alerting, orienting networks, and high visuospatial WMC for non-emotional stimuli may predict degree of social anxiety.

Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis.

PubMed

Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

2015-06-19

Social media is becoming a new battlefield for tobacco "wars". Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users and broader influence, and reveal the shortage of social media resources in global tobacco control. It is found that the user interaction in the pro-tobacco group is more active, and user-generated content for tobacco promotion is more successful in obtaining user attention. Furthermore, we construct three tobacco-related social networks and investigate the topological patterns of these tobacco-related social networks. We find that the size of the pro-tobacco network overwhelms the others, which suggests a huge number of users are exposed to the pro-tobacco content. These results indicate that the gap between tobacco promotion and tobacco control is widening and tobacco control may be losing ground to tobacco promotion in social media.

Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis

PubMed Central

Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

2015-01-01

Social media is becoming a new battlefield for tobacco “wars”. Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users and broader influence, and reveal the shortage of social media resources in global tobacco control. It is found that the user interaction in the pro-tobacco group is more active, and user-generated content for tobacco promotion is more successful in obtaining user attention. Furthermore, we construct three tobacco-related social networks and investigate the topological patterns of these tobacco-related social networks. We find that the size of the pro-tobacco network overwhelms the others, which suggests a huge number of users are exposed to the pro-tobacco content. These results indicate that the gap between tobacco promotion and tobacco control is widening and tobacco control may be losing ground to tobacco promotion in social media. PMID:26091553

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

Qualitative analysis of social network influences on quitting smoking among individuals with serious mental illness.

PubMed

Aschbrenner, Kelly A; Naslund, John A; Gill, Lydia; Hughes, Terence; O'Malley, Alistair J; Bartels, Stephen J; Brunette, Mary F

2017-07-04

The prevalence of cigarette smoking among adults with serious mental illness (SMI) remains high in the United States despite the availability of effective smoking cessation treatment. Identifying social influences on smoking and smoking cessation may help enhance intervention strategies to help smokers with SMI quit. The objective of this qualitative study was to explore social network influences on efforts to quit smoking among adults with SMI enrolled in a cessation treatment program. Participants were 41 individuals with SMI enrolled in a Medicaid Demonstration Project of smoking cessation at community mental health centers. A convenience sampling strategy was used to recruit participants for social network interviews exploring the influence of family, friends, peers, and significant others on quitting smoking. A team-based analysis of qualitative data involved descriptive coding, grouping coded data into categories, and identifying themes across the data. Social barriers to quitting smoking included pro-smoking social norms, attitudes, and behaviors of social network members, and negative interactions with network members, either specific to smoking or that triggered smoking. Social facilitators to quitting included quitting with network members, having cessation role models, and social support for quitting from network members. Similar to the general population, social factors appear to influence efforts to quit smoking among individuals with SMI enrolled in cessation treatment. Interventions that leverage positive social influences on smoking cessation have the potential to enhance strategies to help individuals with SMI quit smoking.

An agent-based model of centralized institutions, social network technology, and revolution.

PubMed

Makowsky, Michael D; Rubin, Jared

2013-01-01

This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.

Social Network Data Validity: The Example of the Social Network of Caregivers of Older Persons with Alzheimer-Type Dementia

ERIC Educational Resources Information Center

Carpentier, Normand

2007-01-01

This article offers reflection on the validity of relational data such as used in social network analysis. Ongoing research on the transformation of the support network of caregivers of persons with an Alzheimer-type disease provides the data to fuel the debate on the validity of participant report. More specifically, we sought to understand the…

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

PubMed

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

2012-01-01

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

Integration of Spatial and Social Network Analysis in Disease Transmission Studies

PubMed Central

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

2013-01-01

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

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.

Social networks of older adults living with HIV in Finland.

PubMed

Nobre, Nuno Ribeiro; Kylmä, Jari; Kirsi, Tapio; Pereira, Marco

2016-01-01

The aim of this study was to explore the social networks of older adults living with HIV. Interviews were conducted with nine individuals aged 50 or older living with HIV in Helsinki, Finland. Analysis of transcripts was analysed by inductive qualitative content analysis. Results indicated that these participants' networks tended to be large, including those both aware and unaware of the participants' health status. Analysis identified three main themes: large multifaceted social networks, importance of a support group, and downsizing of social networks. Support received appeared to be of great importance in coping with their health condition, especially since the time of diagnosis. Friends and family were the primary source of informal support. The majority of participants relied mostly on friends, some of whom were HIV-positive. Formal support came primarily from the HIV organisation's support group. In this study group, non-disclosure did not impact participants' well-being. In years to come, social networks of older adults living with HIV may shrink due to personal reasons other than HIV-disclosure. What is of primary importance is that healthcare professionals become knowledgeable about psychosocial issues of older adults living with HIV, identifying latent problems and developing adequate interventions in the early stages of the disease; this would help prevent social isolation and foster successful ageing with HIV.

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.

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2018-02-06

Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information about students' and teachers' interactions that can be valuable in guiding teachers, improve students' engagement, and contribute to learning analytics insights.

Using Social Network Methods to Study School Leadership

ERIC Educational Resources Information Center

Pitts, Virginia M.; Spillane, James P.

2009-01-01

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

Social Network Implications of Normative School Transitions in Non-Urban School Districts

ERIC Educational Resources Information Center

Temkin, Deborah A.; Gest, Scott D.; Osgood, D. Wayne; Feinberg, Mark; Moody, James

2018-01-01

This article expands research on normative school transitions (NSTs) from elementary to middle school or middle to high school by examining the extent to which they disrupt structures of friendship networks. Social network analysis is used to quantify aspects of connectedness likely relevant to student experiences of social support. Data were…

Mediation Effects of Internet Addiction on Shame and Social Networking

ERIC Educational Resources Information Center

Dogan, Ugur; Kaya, Sinem

2016-01-01

A survey of 488 college students was conducted in Turkey to investigate the relationship between social network usage, shame and Internet addiction. It was hypothesized that a relationship between shame and social network usage was mediated by Internet addiction. First of all, according to simple regression analysis, it was found that shame…

Systematic Review of Social Network Analysis in Adolescent Cigarette Smoking Behavior

ERIC Educational Resources Information Center

Seo, Dong-Chul; Huang, Yan

2012-01-01

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

Social Network and the Maternal Role Satisfaction of Formerly-Married Mothers.

ERIC Educational Resources Information Center

Bowen, Gary Lee

1982-01-01

Used secondary analysis of interviews conducted with 119 formerly-married mothers to test the hypothesis that the milieu provided by a women's social network predicts satisfaction with the demands of the maternal role. Strength of social network was not found to be significantly associated with maternal role satisfaction. (Author)

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

Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

PubMed Central

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

2018-01-01

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

Physical activity, social network type, and depressive symptoms in late life: an analysis of data from the National Social Life, Health and Aging Project.

PubMed

Litwin, Howard

2012-01-01

To clarify whether physical activity among older Americans is associated with depressive symptoms, beyond the effects of social network type, physical health, and sociodemographic characteristics. The analysis used data from a sub-sample, aged 65–85, from the National Social Life, Health and Aging Project (N=1349). Hierarchical regressions examined the respective effects of selected network types and extent of engagement in physical activity on depressive symptoms, controlling for physical health and sociodemographic background. The findings showed that physical activity was correlated inversely with late life depressive symptoms. However, when interaction terms for the selected social network types and the extent of physical activity were also considered, the main effect of social network on depressive symptoms increased, while that of physical activity was eliminated. The results show that older American adults embedded in family network types are at risk of limited physical activity. However, interventions aimed to increase their engagement in physical activity might help to reduce depressive symptoms within this group.

Social Networking Analysis: One of the First Steps in Net-Centric Operations

DTIC Science & Technology

2005-01-01

came to form part of current management thought and is transforming the ways of thinking about social relationships in management and leadership in...about social relationships and leadership in government and commercial organizations. This paper will highlight how network analysis has become...relevant to management studies, how it is transforming how we study social relationships , how it can be used to understand how actors interact (especially

Social network analysis of duplicative prescriptions: One-month analysis of medical facilities in Japan.

PubMed

Takahashi, Yoshimitsu; Ishizaki, Tatsuro; Nakayama, Takeo; Kawachi, Ichiro

2016-03-01

Duplicative prescriptions refer to situations in which patients receive medications for the same condition from two or more sources. Health officials in Japan have expressed concern about medical "waste" resulting from this practices. We sought to conduct descriptive analysis of duplicative prescriptions using social network analysis and to report their prevalence across ages. We analyzed a health insurance claims database including 1.24 million people from December 2012. Through social network analysis, we examined the duplicative prescription networks, representing each medical facility as nodes, and individual prescriptions for patients as edges. The prevalence of duplicative prescription for any drug class was strongly correlated with its frequency of prescription (r=0.90). Among patients aged 0-19, cough and colds drugs showed the highest prevalence of duplicative prescriptions (10.8%). Among people aged 65 and over, antihypertensive drugs had the highest frequency of prescriptions, but the prevalence of duplicative prescriptions was low (0.2-0.3%). Social network analysis revealed clusters of facilities connected via duplicative prescriptions, e.g., psychotropic drugs showed clustering due to a few patients receiving drugs from 10 or more facilities. Overall, the prevalence of duplicative prescriptions was quite low - less than 10% - although the extent of the problem varied by drug class and age group. Our approach illustrates the potential utility of using a social network approach to understand these practices. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Social network type and morale in old age.

PubMed

Litwin, H

2001-08-01

The aim of this research was to derive network types among an elderly population and to examine the relationship of network type to morale. Secondary analysis of data compiled by the Israeli Central Bureau of Statistics (n = 2,079) was employed, and network types were derived through K-means cluster analysis. Respondents' morale scores were regressed on network types, controlling for background and health variables. Five network types were derived. Respondents in diverse or friends networks reported the highest morale; those in exclusively family or restricted networks had the lowest. Multivariate regression analysis underscored that certain network types were second among the study variables in predicting respondents' morale, preceded only by disability level (Adjusted R(2) =.41). Classification of network types allows consideration of the interpersonal environments of older people in relation to outcomes of interest. The relative effects on morale of elective versus obligated social ties, evident in the current analysis, is a case in point.

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.

The Personal Social Networks of Resettled Bhutanese Refugees During Pregnancy in the United States: A Social Network Analysis.

PubMed

M Kingsbury, Diana; P Bhatta, Madhav; Castellani, Brian; Khanal, Aruna; Jefferis, Eric; S Hallam, Jeffery

2018-04-25

Women comprise 50% of the refugee population, 25% of whom are of reproductive age. Female refugees are at risk for experiencing significant hardships associated with the refugee experience, including after resettlement. For refugee women, the strength of their personal social networks can play an important role in mitigating the stress of resettlement and can be an influential source of support during specific health events, such as pregnancy. A personal social network analysis was conducted among 45 resettled Bhutanese refugee women who had given birth within the past 2 years in the Akron Metropolitan Area of Northeast Ohio. Data were collected using in-depth interviews conducted in Nepali over a 6-month period in 2016. Size, demographic characteristics of ties, frequency of communication, length of relationship, and strength of connection were the social network measures used to describe the personal networks of participants. A qualitative analysis was also conducted to assess what matters were commonly discussed within networks and how supportive participants perceived their networks to be. Overall, participants reported an average of 3 close personal connections during their pregnancy. The networks were comprised primarily of female family members whom the participant knew prior to resettlement in the U.S. Participants reported their networks as "very close" and perceived their connections to be supportive of them during their pregnancies. These results may be used to guide future research, as well as public health programming, that seeks to improve the pregnancy experiences of resettled refugee women.

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

PubMed

Patterson, Megan S; Go Odson, Patricia

2018-04-13

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

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.

A social network-informed latent class analysis of patterns of substance use, sexual behavior, and mental health: Social Network Study III, Winnipeg, Manitoba, Canada.

PubMed

Hopfer, Suellen; Tan, Xianming; Wylie, John L

2014-05-01

We assessed whether a meaningful set of latent risk profiles could be identified in an inner-city population through individual and network characteristics of substance use, sexual behaviors, and mental health status. Data came from 600 participants in Social Network Study III, conducted in 2009 in Winnipeg, Manitoba, Canada. We used latent class analysis (LCA) to identify risk profiles and, with covariates, to identify predictors of class. A 4-class model of risk profiles fit the data best: (1) solitary users reported polydrug use at the individual level, but low probabilities of substance use or concurrent sexual partners with network members; (2) social-all-substance users reported polydrug use at the individual and network levels; (3) social-noninjection drug users reported less likelihood of injection drug and solvent use; (4) low-risk users reported low probabilities across substances. Unstable housing, preadolescent substance use, age, and hepatitis C status predicted risk profiles. Incorporation of social network variables into LCA can distinguish important subgroups with varying patterns of risk behaviors that can lead to sexually transmitted and bloodborne infections.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

An Estimate and Score Algorithm for Simultaneous Parameter Estimation and Reconstruction of Incomplete Data on Social Networks

DTIC Science & Technology

2013-01-12

www.security-informatics.com/content/2/1/1 References 1. SM Radilm, C Flint, GE Tita , Spatializing Social Networks: Using Social Network Analysis to...http://www.tandfonline.com/doi/ abs/10.1080/00045600903550428 2. G Tita , S Radil, Spatializing the social networks of gangs to explore patterns of...violence. Journal of Quantitative Criminology. 27, 1–25 (2011) 3. G Tita , JK Riley, G Ridgeway, AF Abrahamse, P Greenwood, Reducing Gun Violence

Spectrum-Based and Collaborative Network Topology Analysis and Visualization

ERIC Educational Resources Information Center

Hu, Xianlin

2013-01-01

Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying network topology is very important to network analysis. In this dissertation, we study networks by…

An Analysis of Density and Degree-Centrality According to the Social Networking Structure Formed in an Online Learning Environment

ERIC Educational Resources Information Center

Ergün, Esin; Usluel, Yasemin Koçak

2016-01-01

In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a…

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

ERIC Educational Resources Information Center

Firdausiah Mansur, Andi Besse; Yusof, Norazah

2013-01-01

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

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

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.

Neighborhood adversity, ethnic diversity, and weak social cohesion and social networks predict high rates of maternal depressive symptoms: a critical realist ecological study in South Western Sydney, Australia.

PubMed

Eastwood, John Graeme; Kemp, Lynn Ann; Jalaludin, Bin Badrudin; Phung, Hai Ngoc

2013-01-01

The aim of the study reported here is to explore ecological covariate and latent variable associations with perinatal depressive symptoms in South Western Sydney for the purpose of informing subsequent theory generation of perinatal context, depression, and the developmental origins of health and disease. Mothers (n = 15,389) delivering in 2002 and 2003 were assessed at two to three weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale (EPDS)> 9 and > 12. Aggregated EPDS > 9 was analyzed for 101 suburbs. Suburb-level variables were drawn from the 2001 Australian Census, New South Wales Crime Statistics, and aggregated individual-level risk factors. Analysis included exploratory factor analysis, univariate and multivariate likelihood, and Bayesian linear regression with conditional autoregressive components. The exploratory factor analysis identified six factors: neighborhood adversity, social cohesion, health behaviors, housing quality, social services, and support networks. Variables associated with neighborhood adversity, social cohesion, social networks, and ethnic diversity were consistently associated with aggregated depressive symptoms. The findings support the theoretical proposition that neighborhood adversity causes maternal psychological distress and depression within the context of social buffers including social networks, social cohesion, and social services.

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.

Multiple contexts and adolescent body mass index: Schools, neighborhoods, and social networks.

PubMed

Evans, Clare R; Onnela, Jukka-Pekka; Williams, David R; Subramanian, S V

2016-08-01

Adolescent health and behaviors are influenced by multiple contexts, including schools, neighborhoods, and social networks, yet these contexts are rarely considered simultaneously. In this study we combine social network community detection analysis and cross-classified multilevel modeling in order to compare the contributions of each of these three contexts to the total variation in adolescent body mass index (BMI). Wave 1 of the National Longitudinal Study of Adolescent to Adult Health is used, and for robustness we conduct the analysis in both the core sample (122 schools; N = 14,144) and a sub-set of the sample (16 schools; N = 3335), known as the saturated sample due to its completeness of neighborhood data. After adjusting for relevant covariates, we find that the school-level and neighborhood-level contributions to the variance are modest compared with the network community-level (σ(2)school = 0.069, σ(2)neighborhood = 0.144, σ(2)network = 0.463). These results are robust to two alternative algorithms for specifying network communities, and to analysis in the saturated sample. While this study does not determine whether network effects are attributable to social influence or selection, it does highlight the salience of adolescent social networks and indicates that they may be a promising context to address in the design of health promotion programs. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Researching Social Capital in Education: Some Conceptual Considerations Relating to the Contribution of Network Analysis

ERIC Educational Resources Information Center

Lee, Moosung

2010-01-01

This article discusses conceptual considerations for social capital research in education from a social network perspective. Specifically, the article raises three key conceptual issues that call for further elaboration of concepts of social capital: redefining potential resources as accessible but un-utilized sources of social capital;…

Parameterization of Keeling's network generation algorithm.

PubMed

Badham, Jennifer; Abbass, Hussein; Stocker, Rob

2008-09-01

Simulation is increasingly being used to examine epidemic behaviour and assess potential management options. The utility of the simulations rely on the ability to replicate those aspects of the social structure that are relevant to epidemic transmission. One approach is to generate networks with desired social properties. Recent research by Keeling and his colleagues has generated simulated networks with a range of properties, and examined the impact of these properties on epidemic processes occurring over the network. However, published work has included only limited analysis of the algorithm itself and the way in which the network properties are related to the algorithm parameters. This paper identifies some relationships between the algorithm parameters and selected network properties (mean degree, degree variation, clustering coefficient and assortativity). Our approach enables users of the algorithm to efficiently generate a network with given properties, thereby allowing realistic social networks to be used as the basis of epidemic simulations. Alternatively, the algorithm could be used to generate social networks with a range of property values, enabling analysis of the impact of these properties on epidemic behaviour.

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.

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.

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.

Exploring Peer Relationships, Friendships and Group Work Dynamics in Higher Education: Applying Social Network Analysis

ERIC Educational Resources Information Center

Mamas, Christoforos

2018-01-01

This study primarily applied social network analysis (SNA) to explore the relationship between friendships, peer social interactions and group work dynamics within a higher education undergraduate programme in England. A critical case study design was adopted so as to allow for an in-depth exploration of the students' voice. In doing so, the views…

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 network types and functional dependency in older adults in Mexico.

PubMed

Doubova Dubova, Svetlana Vladislavovna; Pérez-Cuevas, Ricardo; Espinosa-Alarcón, Patricia; Flores-Hernández, Sergio

2010-02-27

Social networks play a key role in caring for older adults. A better understanding of the characteristics of different social networks types (TSNs) in a given community provides useful information for designing policies to care for this age group. Therefore this study has three objectives: 1) To derive the TSNs among older adults affiliated with the Mexican Institute of Social Security; 2) To describe the main characteristics of the older adults in each TSN, including the instrumental and economic support they receive and their satisfaction with the network; 3) To determine the association between functional dependency and the type of social network. Secondary data analysis of the 2006 Survey of Autonomy and Dependency (N = 3,348). The TSNs were identified using the structural approach and cluster analysis. The association between functional dependency and the TSNs was evaluated with Poisson regression with robust variance analysis in which socio-demographic characteristics, lifestyle and medical history covariates were included. We identified five TSNs: diverse with community participation (12.1%), diverse without community participation (44.3%); widowed (32.0%); nonfriends-restricted (7.6%); nonfamily-restricted (4.0%). Older adults belonging to widowed and restricted networks showed a higher proportion of dependency, negative self-rated health and depression. Older adults with functional dependency more likely belonged to a widowed network (adjusted prevalence ratio 1.5; 95%CI: 1.1-2.1). The derived TSNs were similar to those described in developed countries. However, we identified the existence of a diverse network without community participation and a widowed network that have not been previously described. These TSNs and restricted networks represent a potential unmet need of social security affiliates.

The Mechanisms of Interpersonal Privacy in Social Networking Websites: A Study of Subconscious Processes, Social Network Analysis, and Fear of Social Exclusion

ERIC Educational Resources Information Center

Hammer, Bryan

2013-01-01

With increasing usage of social networking sites like Facebook there is a need to study privacy. Previous research has placed more emphasis on outcome-oriented contexts, such as e-commerce sites. In process-oriented contexts, like Facebook, privacy has become a source of conflict for users. The majority of architectural privacy (e.g. privacy…

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.

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

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

PubMed

Olofsson, Jenny; Padyab, Mojgan; Malmberg, Gunnar

2018-01-01

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

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

PubMed Central

Olofsson, Jenny; Malmberg, Gunnar

2018-01-01

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

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

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.

An Agent-Based Model of Centralized Institutions, Social Network Technology, and Revolution

PubMed Central

Makowsky, Michael D.; Rubin, Jared

2013-01-01

This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change. PMID:24278280

Investigating the Educational Value of Social Learning Networks: A Quantitative Analysis

ERIC Educational Resources Information Center

Dafoulas, Georgios; Shokri, Azam

2016-01-01

Purpose: The emergence of Education 2.0 enabled technology-enhanced learning, necessitating new pedagogical approaches, while e-learning has evolved into an instrumental pedagogy of collaboration through affordances of social media. Social learning networks and ubiquitous learning enabled individual and group learning through social engagement and…

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.

A multilevel path analysis of contact frequency between social network members

NASA Astrophysics Data System (ADS)

van den Berg, Pauline; Arentze, Theo; Timmermans, Harry

2012-04-01

Recently, there has been an increasing interest in the role of social networks in spatial-choice and travel behavior. It has been acknowledged that social activities and the travel for these activities can emerge from individuals' social networks and that social activities are responsible for an important portion of travel demand. The influence of information and communication technologies (ICT's) is also important in this respect. The purpose of the paper is to examine the effects of characteristics of egos and ego-alter relationships on the frequency of social interaction by different communication modes, using multilevel path analysis. The analyses are based on social network data collected in 2008 in the Eindhoven region in the Netherlands among 116 respondents. The results indicate a complementary relationship between contact frequencies by different modes. The contact frequencies of the different modes, especially face-to-face and telephone, can also be largely explained by the ego's personal characteristics and the type of relationship and the distance between ego and alter.

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

PubMed

Yoshihara, Chika; Shimizu, Shinji

2005-10-01

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

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

"I'll See You on IM, Text, or Call You": A Social Network Approach of Adolescents' Use of Communication Media

ERIC Educational Resources Information Center

Van Cleemput, Katrien

2010-01-01

This study explores some possibilities of social network analysis for studying adolescents' communication patterns. A full network analysis was conducted on third-grade high school students (15 year olds, 137 students) in Belgium. The results pointed out that face-to-face communication was still the most prominent way for information to flow…

Intelligence Collection Targeting and Interdiction of Dark Networks

DTIC Science & Technology

2014-06-01

2006): 346. 26 Wouter de Nooy, Andrej Mrvar , and Vladimir Batagelj . Exploratory Social Network Analysis with Pajek, 2nd ed. (Cambridge: Cambridge...Pittsburgh, PA: Carnegie Mellon University, 2013. de Nooy, Wouter, Andrej Mrvar , and Vladimir Batagelj . Exploratory Social Network Analysis with...al-Qaeda’s leaders had closely followed the April 1996 assassination of Dzhokhar Dudayev, the Chechen prime minister, who was killed by a Russian

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.

Having mentors and campus social networks moderates the impact of worries and video gaming on depressive symptoms: a moderated mediation analysis.

PubMed

Lee, Jong-Sun; Jeong, Bumseok

2014-05-05

Easy access to the internet has spawned a wealth of research to investigate the effects of its use on depression. However, one limitation of many previous studies is that they disregard the interactive mechanisms of risk and protective factors. The aim of the present study was to investigate a resilience model in the relationship between worry, daily internet video game playing, daily sleep duration, mentors, social networks and depression, using a moderated mediation analysis. 6068 Korean undergraduate and graduate students participated in this study. The participants completed a web-based mental health screening questionnaire including the Beck Depression Inventory (BDI) and information about number of worries, number of mentors, number of campus social networks, daily sleep duration, daily amount of internet video game playing and daily amount of internet searching on computer or smartphone. A moderated mediation analysis was carried out using the PROCESS macro which allowed the inclusion of mediators and moderator in the same model. The results showed that the daily amount of internet video game playing and daily sleep duration partially mediated the association between the number of worries and the severity of depression. In addition, the mediating effect of the daily amount of internet video game playing was moderated by both the number of mentors and the number of campus social networks. The current findings indicate that the negative impact of worry on depression through internet video game playing can be buffered when students seek to have a number of mentors and campus social networks. Interventions should therefore target individuals who have higher number of worries but seek only a few mentors or campus social networks. Social support via campus mentorship and social networks ameliorate the severity of depression in university students.

Visual social network analysis: effective approach to model complex human social, behaviour & culture.

PubMed

Ahram, Tareq Z; Karwowski, Waldemar

2012-01-01

The advent and adoption of internet-based social networking has significantly altered our daily lives. The educational community has taken notice of the positive aspects of social networking such as creation of blogs and to support groups of system designers going through the same challenges and difficulties. This paper introduces a social networking framework for collaborative education, design and modeling of the next generation of smarter products and services. Human behaviour modeling in social networking application aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter products throughout the total system lifecycle. Social networks blend self-directed learning and prescribed, existing information. The self-directed element creates interest within a learner and the ability to access existing information facilitates its transfer, and eventual retention of knowledge acquired.

Centrality Measures and Academic Achievement in Computerized Classroom Social Networks: An Empirical Investigation

ERIC Educational Resources Information Center

Reychav, Iris; Raban, Daphne Ruth; McHaney, Roger

2018-01-01

The current empirical study examines relationships between network measures and learning performance from a social network analysis perspective. We collected computerized, networking data to analyze how 401 junior high students connected to classroom peers using text- and video-based material on iPads. Following a period of computerized…

Potential benefits and harms of a peer support social network service on the internet for people with depressive tendencies: qualitative content analysis and social network analysis.

PubMed

Takahashi, Yoshimitsu; Uchida, Chiyoko; Miyaki, Koichi; Sakai, Michi; Shimbo, Takuro; Nakayama, Takeo

2009-07-23

Internet peer support groups for depression are becoming popular and could be affected by an increasing number of social network services (SNSs). However, little is known about participant characteristics, social relationships in SNSs, and the reasons for usage. In addition, the effects of SNS participation on people with depression are rather unknown. The aim was to explore the potential benefits and harms of an SNS for depression based on a concurrent triangulation design of mixed methods strategy, including qualitative content analysis and social network analysis. A cross-sectional Internet survey of participants, which involved the collection of SNS log files and a questionnaire, was conducted in an SNS for people with self-reported depressive tendencies in Japan in 2007. Quantitative data, which included user demographics, depressive state, and assessment of the SNS (positive vs not positive), were statistically analyzed. Descriptive contents of responses to open-ended questions concerning advantages and disadvantages of SNS participation were analyzed using the inductive approach of qualitative content analysis. Contents were organized into codes, concepts, categories, and a storyline based on the grounded theory approach. Social relationships, derived from data of "friends," were analyzed using social network analysis, in which network measures and the extent of interpersonal association were calculated based on the social network theory. Each analysis and integration of results were performed through a concurrent triangulation design of mixed methods strategy. There were 105 participants. Median age was 36 years, and 51% (36/71) were male. There were 37 valid respondents; their number of friends and frequency of accessing the SNS were significantly higher than for invalid/nonrespondents (P = .008 and P = .003). Among respondents, 90% (28/31) were mildly, moderately, or severely depressed. Assessment of the SNS was performed by determining the access frequency of the SNS and the number of friends. Qualitative content analysis indicated that user-selectable peer support could be passive, active, and/or interactive based on anonymity or ease of use, and there was the potential harm of a downward depressive spiral triggered by aggravated psychological burden. Social network analysis revealed that users communicated one-on-one with each other or in small groups (five people or less). A downward depressive spiral was related to friends who were moderately or severely depressed and friends with negative assessment of the SNS. An SNS for people with depressive tendencies provides various opportunities to obtain support that meets users' needs. To avoid a downward depressive spiral, we recommend that participants do not use SNSs when they feel that the SNS is not user-selectable, when they get egocentric comments, when friends have a negative assessment of the SNS, or when they have additional psychological burden.

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

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

EPA Science Inventory

Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing i...

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

EPA Science Inventory

Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing in...

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

PubMed

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

2014-05-30

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Social network of an internationally connected nurse leader.

PubMed

Benton, David

2016-03-01

Over the past decade, there has been a proliferation of social media sites offering the opportunity for colleagues to connect with each other locally, nationally and internationally. Meanwhile, nurses have been increasingly using social network analytical techniques to look at team functioning and communication pathways. This article uses the author's LinkedIn social network to illustrate how analysis can offer insights into the connections, and how the results can be used to professional advantage.

Examination of a Social-Networking Site Activities Scale (SNSAS) Using Rasch Analysis

ERIC Educational Resources Information Center

Alhaythami, Hassan; Karpinski, Aryn; Kirschner, Paul; Bolden, Edward

2017-01-01

This study examined the psychometric properties of a social-networking site (SNS) activities scale (SNSAS) using Rasch Analysis. Items were also examined with Rasch Principal Components Analysis (PCA) and Differential Item Functioning (DIF) across groups of university students (i.e., males and females from the United States [US] and Europe; N =…

Uncovering the Hidden Structure of Platoons: Formal and Emergent Leaders’ Perceptions of Organizational Networks

DTIC Science & Technology

2008-12-01

perceptions of formal and emergent leaders differ from those of non-leaders, and if so, how. We approach this topic through the lens of social network...analysis. 1.1 Social Networks The term “ social network” refers to a set of actors who are connected by a set of ties. Actors, often referred to as...the structure of any social system can be defined as a set of relations between all pairs of individuals who are members of the network (Krackhardt

An Analysis of the Differences between Student Age and Social Networking Utilization within a School of Business

ERIC Educational Resources Information Center

Zula, Ken; Yarrish, Karen K.; Pawelzik, Walter

2011-01-01

Social networking sites such as Facebook, LinkedIn, and Twitter are widely regarded as an exciting opportunity to communicate with friends, especially for college students. The overall response to social networking tends to be one of trust regarding a generation that, supposedly has many friends but little sense of privacy. Employers use social…

A Social Operational Model of Urban Adolescents' Tobacco and Substance Use: A Mediational Analysis

ERIC Educational Resources Information Center

Mason, Michael J.; Mennis, Jeremy; Schmidt, Christopher D.

2011-01-01

This study tested a mediation model of the relationship with tobacco use, social network quality (level of risk or protection in a network), and substance use (alcohol and/or illicit drugs) with a sample of 301 urban adolescents. It was theorized that social network quality would mediate the effect of tobacco use, accounting for PTSD symptoms and…

Network Analysis in Community Psychology: Looking Back, Looking Forward.

PubMed

Neal, Zachary P; Neal, Jennifer Watling

2017-09-01

Network analysis holds promise for community psychology given the field's aim to understand the interplay between individuals and their social contexts. Indeed, because network analysis focuses explicitly on patterns of relationships between actors, its theories and methods are inherently extra-individual in nature and particularly well suited to characterizing social contexts. But, to what extent has community psychology taken advantage of this network analysis as a tool for capturing context? To answer these questions, this study provides a review of the use network analysis in articles published in American Journal of Community Psychology. Looking back, we describe and summarize the ways that network analysis has been employed in community psychology research to understand the range of ways community psychologists have found the technique helpful. Looking forward and paying particular attention to analytic issues identified in past applications, we provide some recommendations drawn from the network analysis literature to facilitate future applications of network analysis in community psychology. © 2017 The Authors. American Journal of Community Psychology published by Wiley Periodicals, Inc. on behalf of Society for Community Research and Action.

Information seeking for making evidence-informed decisions: a social network analysis on the staff of a public health department in Canada.

PubMed

Yousefi-Nooraie, Reza; Dobbins, Maureen; Brouwers, Melissa; Wakefield, Patricia

2012-05-16

Social network analysis is an approach to study the interactions and exchange of resources among people. It can help understanding the underlying structural and behavioral complexities that influence the process of capacity building towards evidence-informed decision making. A social network analysis was conducted to understand if and how the staff of a public health department in Ontario turn to peers to get help incorporating research evidence into practice. The staff were invited to respond to an online questionnaire inquiring about information seeking behavior, identification of colleague expertise, and friendship status. Three networks were developed based on the 170 participants. Overall shape, key indices, the most central people and brokers, and their characteristics were identified. The network analysis showed a low density and localized information-seeking network. Inter-personal connections were mainly clustered by organizational divisions; and people tended to limit information-seeking connections to a handful of peers in their division. However, recognition of expertise and friendship networks showed more cross-divisional connections. Members of the office of the Medical Officer of Health were located at the heart of the department, bridging across divisions. A small group of professional consultants and middle managers were the most-central staff in the network, also connecting their divisions to the center of the information-seeking network. In each division, there were some locally central staff, mainly practitioners, who connected their neighboring peers; but they were not necessarily connected to other experts or managers. The methods of social network analysis were useful in providing a systems approach to understand how knowledge might flow in an organization. The findings of this study can be used to identify early adopters of knowledge translation interventions, forming Communities of Practice, and potential internal knowledge brokers.

Sense-making for intelligence analysis on social media data

NASA Astrophysics Data System (ADS)

Pritzkau, Albert

2016-05-01

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

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

PubMed

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

2010-07-01

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

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

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

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

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.

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...

How Relations are Built within a SNS World -- Social Network Analysis on Mixi --

NASA Astrophysics Data System (ADS)

Matsuo, Yutaka; Yasud, Yuki

Our purpose here is to (1) investigate the structure of the personal networks developed on mixi, a Japanese social networking service (SNS), and (2) to consider the governing mechanism which guides participants of a SNS to form an aggregate network. Our findings are as follows:the clustering coefficient of the network is as high as 0.33 while the characteristic path lenght is as low as 5.5. A network among central users (over 300 edges) consist of two cliques, which seems to be very fragile. Community-affiliation network suggests there are several easy-entry communities which later lead users to more high-entry, unique-theme communities. The analysis on connectedness within a community reveals the importance of real-world interaction. Lastly, we depict a probable image of the entire ecology on {\\\\em mixi} among users and communities, which contributes broadly to social systems on the Web.

Peer Influence on Academic Performance: A Social Network Analysis of Social-Emotional Intervention Effects.

PubMed

DeLay, Dawn; Zhang, Linlin; Hanish, Laura D; Miller, Cindy F; Fabes, Richard A; Martin, Carol Lynn; Kochel, Karen P; Updegraff, Kimberly A

2016-11-01

Longitudinal social network analysis (SNA) was used to examine how a social-emotional learning (SEL) intervention may be associated with peer socialization on academic performance. Fifth graders (N = 631; 48 % girls; 9 to 12 years) were recruited from six elementary schools. Intervention classrooms (14) received a relationship building intervention (RBI) and control classrooms (8) received elementary school as usual. At pre- and post-test, students nominated their friends, and teachers completed assessments of students' writing and math performance. The results of longitudinal SNA suggested that the RBI was associated with friend selection and peer influence within the classroom peer network. Friendship choices were significantly more diverse (i.e., less evidence of social segregation as a function of ethnicity and academic ability) in intervention compared to control classrooms, and peer influence on improved writing and math performance was observed in RBI but not control classrooms. The current findings provide initial evidence that SEL interventions may change social processes in a classroom peer network and may break down barriers of social segregation and improve academic performance.

Social Network Analysis of the Farabi Exchange Program: Student Mobility

ERIC Educational Resources Information Center

Ugurlu, Zeynep

2016-01-01

Problem Statement: Exchange programs offer communication channels created through student and instructor exchanges; a flow of information takes place through these channels. The Farabi Exchange Program (FEP) is a student and instructor exchange program between institutions of higher education. Through the use of social network analysis and…

Social Networks and High Healthcare Utilization: Building Resilience Through Analysis

DTIC Science & Technology

2016-09-01

of Social Network Analysis Patients Developing targeted intervention programs based on the individual’s needs may potentially help improve the...network structure is found in the patterns of interconnection that develop between nodes. It is this linking through common nodes, “the AB link shares...transitivity is responsible for the clustering of nodes that form “communities” of people based on geography, common interests, or other group

Social networks of patients with chronic skin lesions: nursing care.

PubMed

Bandeira, Luciana Alves; Santos, Maxuel Cruz Dos; Duarte, Êrica Rosalba Mallmann; Bandeira, Andrea Gonçalves; Riquinho, Deise Lisboa; Vieira, Letícia Becker

2018-01-01

To describe the social networks of patients with chronic skin damages. A qualitative study conducted through semi-structured interviews with nine subjects with chronic skin lesions from June 2016 to March 2017; we used the theoretical-methodological framework of Lia Sanicola's Social Network. The analysis of the relational maps revealed that the primary network was formed mainly by relatives and neighbors; its characteristics, such as: reduced size, low density and few exchanges/relationships, configures fragility in these links. The secondary network was essentially described by health services, and the nurse was cited as a linker in the therapeutic process. Faced with the fragility of the links and social isolation, the primary health care professionals are fundamental foundations for the construction of networks of social support and care for patients with chronic skin lesions.

Unprotected sex of homeless youth: results from a multilevel dyadic analysis of individual, social network, and relationship factors.

PubMed

Kennedy, David P; Tucker, Joan S; Green, Harold D; Golinelli, Daniela; Ewing, Brett

2012-10-01

Homeless youth have elevated risk of HIV through sexual behavior. This project investigates the multiple levels of influence on unprotected sex among homeless youth, including social network, individual, and partner level influences. Findings are based on analyses of an exploratory, semi-structured interview (n = 40) and a structured personal network interview (n = 240) with randomly selected homeless youth in Los Angeles. Previous social network studies of risky sex by homeless youth have collected limited social network data from non-random samples and have not distinguished sex partner influences from other network influences. The present analyses have identified significant associations with unprotected sex at multiple levels, including individual, partner, and, to a lesser extent, the social network. Analyses also distinguished between youth who did or did not want to use condoms when they had unprotected sex. Implications for social network based HIV risk interventions with homeless youth are discussed.

Unprotected Sex of Homeless Youth: Results from a Multilevel Analysis of Individual, Social Network, and Relationship Factors

PubMed Central

Kennedy, David P.; Tucker, Joan S.; Green, Harold D.; Golinelli, Daniela; Ewing, Brett

2012-01-01

Homeless youth have elevated risk of HIV through sexual behavior. This project investigates the multiple levels of influence on unprotected sex among homeless youth, including social network, individual, and partner level influences. Findings are based on analyses of an exploratory, semi-structured interview (n=40) and a structured personal network interview (n=240) with randomly selected homeless youth in Los Angeles. Previous social network studies of risky sex by homeless youth have collected limited social network data from non-random samples and have not distinguished sex partner influences from other network influences. The present analyses have identified significant associations with unprotected sex at multiple levels, including individual, partner, and, to a lesser extent, the social network. Analyses also distinguished between youth who wished they used condoms after having unprotected sex and youth who did not regret having unprotected sex. Implications for social network based HIV risk interventions with homeless youth are discussed. PMID:22610421

Disappearing acts: The social networks of formerly homeless individuals with co-occurring disorders

PubMed Central

Abrams, Courtney

2007-01-01

Studies of the social lives of men and women living with co-occurring disorders (substance abuse and serious mental illness) suggest that social networks critically influence recovery. In this paper, we examine some of the reasons that the social networks of individuals with co-occurring disorders are small, and the impact of small networks for this population. Using a social capital framework with cross-case analysis, we analyze 72 in-depth qualitative interviews with 39 formerly homeless mentally ill men and women who were substance abusers. All were participants in the New York Services Study (HYSS), a federally funded study of mentally ill adults in New York City. The patterns suggest that networks shrunk because 1) social network members died prematurely, 2) study participants withdrew or pushed others away, and 3) friends and family members faced so many obstacles of their own that they could not provide resources for the study participants. We suggest that as networks diminished, some participants responded by attempting to rebuild their networks, even if the networks provided negative social capital, and others isolated themselves socially to escape the pressures and disappointments of interaction. PMID:17706330

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

PubMed

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

2013-09-01

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

Geo-Spatial Social Network Analysis of Social Media to Mitigate Disasters

NASA Astrophysics Data System (ADS)

Carley, K. M.

2017-12-01

Understanding the spatial layout of human activity can afford a better understanding many phenomena - such as local cultural, the spread of ideas, and the scope of a disaster. Today, social media is one of the key sensors for acquiring information on socio-cultural activity, some with cues as to the geo-location. We ask, What can be learned by putting such data on maps? For example, are people who chat on line more likely to be near each other? Can Twitter data support disaster planning or early warning? In this talk, such issues are examined using data collected via Twitter and analyzed using ORA. ORA is a network analysis and visualization system. It supports not just social networks (who is interacting with whom), but also high dimensional networks with many types of nodes (e.g. people, organizations, resources, activities …) and relations, geo-spatial network analysis, dynamic network analysis, & geo-temporal analysis. Using ORA lessons learned from five case studies are considered: Arab Spring, Tsunami warning in Padang Indonesia, Twitter around Fukushima in Japan, Typhoon Haiyan (Yolanda), & regional conflict. Using Padang Indonesia data, we characterize the strengths and limitations of social media data to support disaster planning & early warning, identify at risk areas & issues of concern, and estimate where people are and which areas are impacted. Using Fukushima Japanese data, social media is used to estimate geo-spatial regularities in movement and communication that can inform disaster response and risk estimation. Using Arab Spring data, we find that the spread of bots & extremists varies by country and time, to the extent that using twitter to understand who is important or what ideas are critical can be compromised. Bots and extremists can exploit disaster messaging to create havoc and facilitate criminal activity e.g. human trafficking. Event discovery mechanisms support isolating geo-epi-centers for key events become crucial. Spatial inference enables improved country, and city identification. Geo-network analytics with and without these inferences reveal that explicitly geo-tagged data may not be representative and that improved location estimation provides better insight into the social condition. These results demonstrate the value of these technique to mitigate the social impact of disasters.

Candidate change agent identification among men at risk for HIV infection

PubMed Central

Schneider, John A.; McFadden, Rachel B.; Laumann, Edward O.; Kumar, SG Prem; Gandham, Sabitha R.; Oruganti, Ganesh

2012-01-01

Despite limited HIV prevention potency, peer-based programs have become one of the most often used HIV prevention approaches internationally. These programs demonstrate a need for greater specificity in peer change agent (PCA) recruitment and social network evaluation. In the present three-phase study based in India (2009–2010), we first explored the nature of friendship among truck-drivers, a group of men at high risk for HIV infection, in order to develop a thorough understanding of the social forces that contribute to and maintain their personal networks. This was accomplished in the first two study phases, through a combination of focus group discussions (n=5 groups), in-depth qualitative interviews (n=20), and personal network analyses (n=25) of truck-drivers to define friendship and deepen our understanding of friendship across geographic spaces. Measures collected in phases I and II included friend typologies, discussion topics, social network influences, advice-giving, and risk reduction. Outcomes were assessed through an iterative process of qualitative textual analysis and social network analysis. The networks of truck-drivers were found to comprise three typologies: close friends, parking lot friends, and other friends. From these data, we developed an algorithmic approach to the identification of a candidate PCA within a high-risk man’s personal network. In stage III we piloted field-use of this approach to identify and recruit PCAs, and further evaluated their potential for intervention through preliminary analysis of the PCA’s own personal networks. An instrument was developed to translate what social network theory and analysis has taught us about egocentric network dynamics into a real-world methodology for identifying intervention-appropriate peers within an individual’s personal network. Our approach can be tailored to the specifications of any high-risk population, and may serve to enhance current peer-based HIV interventions. PMID:22762951

Incorporating social impact on new product adoption in choice modeing: A case study in green vehicles

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

He, Lin; Wang, Mingxian; Chen, Wei

While discrete choice analysis is prevalent in capturing consumer preferences and describing their choice behaviors in product design, the traditional choice modeling approach assumes that each individual makes independent decisions, without considering the social impact. However, empirical studies show that choice is social - influenced by many factors beyond engineering performance of a product and consumer attributes. To alleviate this limitation, we propose a new choice modeling framework to capture the dynamic influence from social networks on consumer adoption of new products. By introducing social influence attributes into a choice utility function, social network simulation is integrated with the traditionalmore » discrete choice analysis in a three-stage process. Our study shows the need for considering social impact in forecasting new product adoption. Using hybrid electric vehicles as an example, our work illustrates the procedure of social network construction, social influence evaluation, and choice model estimation based on data from the National Household Travel Survey. Our study also demonstrates several interesting findings on the dynamic nature of new technology adoption and how social networks may influence hybrid electric vehicle adoption. (C) 2014 Elsevier Ltd. All rights reserved« less

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

Networking Matters: A Social Network Analysis of the Association of Program Directors of Internal Medicine.

PubMed

Warm, Eric; Arora, Vineet M; Chaudhry, Saima; Halvorsen, Andrew; Schauer, Daniel; Thomas, Kris; McDonald, Furman S

2018-03-22

Networking has positive effects on career development; however, personal characteristics of group members such as gender or diversity may foster or hinder member connectedness. Social network analysis explores interrelationships between people in groups by measuring the strength of connection between all possible pairs in a given network. Social network analysis has rarely been used to examine network connections among members in an academic medical society. This study seeks to ascertain the strength of connection between program directors in the Association of Program Directors in Internal Medicine (APDIM) and its Education Innovations Project subgroup and to examine possible associations between connectedness and characteristics of program directors and programs. We hypothesize that connectedness will be measurable within a large academic medical society and will vary significantly for program directors with certain measurable characteristics (e.g., age, gender, rank, location, burnout levels, desire to resign). APDIM program directors described levels of connectedness to one another on the 2012 APDIM survey. Using social network analysis, we ascertained program director connectedness by measuring out-degree centrality, in-degree centrality, and eigenvector centrality, all common measures of connectedness. Higher centrality was associated with completion of the APDIM survey, being in a university-based program, Educational Innovations Project participation, and higher academic rank. Centrality did not vary by gender; international medical graduate status; previous chief resident status; program region; or levels of reported program director burnout, callousness, or desire to resign. In this social network analysis of program directors within a large academic medical society, we found that connectedness was related to higher academic rank and certain program characteristics but not to other program director characteristics like gender or international medical graduate status. Further research is needed to optimize our understanding of connection in organizations such as these and to determine which strategies promote valuable connections.

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)…

The ‘Friendship Dynamics of Religion,’ or the ‘Religious Dynamics of Friendship’? A Social Network Analysis of Adolescents Who Attend Small Schools*

PubMed Central

Cheadle, Jacob E.; Schwadel, Philip

2012-01-01

Longitudinal social network data on adolescents in seven schools are analyzed to reach a new understanding about how the personal and interpersonal social dimensions of adolescent religion intertwine together in small school settings. We primarily address two issues relevant to the sociology of religion and sociology in general: (1) social selection as a source of religious homophily and (2) friend socialization of religion. Analysis results are consistent with Collins’ interaction ritual chain theory, which stresses the social dimensions of religion, since network-religion autocorrelations are relatively substantial in magnitude and both selection and socialization mechanisms play key roles in generating them. Results suggest that socialization plays a stronger role than social selection in four of six religious outcomes, and that more religious youth are more cliquish. Implications for our understanding of the social context of religion, religious homophily, and the ways we model religious influence, as well as limitations and considerations for future research, are discussed. PMID:23017927

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

ERIC Educational Resources Information Center

Velastegui, Pamela J.

2013-01-01

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

Geographies of an Online Social Network.

PubMed

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the "death of distance", physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected.

Geographies of an Online Social Network

PubMed Central

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the “death of distance”, physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected. PMID:26359668

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.

Friends, Depressive Symptoms, and Life Satisfaction Among Older Korean Americans.

PubMed

Roh, Soonhee; Lee, Yeon-Shim; Lee, Kyoung Hag; Shibusawa, Tazuko; Yoo, Grace J

2015-08-01

This study examined the interactive effects of social network support and depressive symptoms on life satisfaction among older Korean Americans (KAs). Using data from a sample of 200 elders in a large metropolitan area (M age = 72.50, SD = 5.15), hierarchical regression analysis was used to examine the interaction between social network support and depressive symptoms on life satisfaction among older KAs. After controlling for demographic variables, both social network support and depressive symptoms were identified as predictors for life satisfaction. Interaction effects indicated strong associations between higher social network support specifically from friends and lower depressive symptoms with higher levels of life satisfaction. Findings highlight the important role that friends play in terms of social network support for the mental health of older KAs, and the need for geriatric practitioners to monitor and assess the quality of social network support-including friendships-when working with older KAs.

Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

PubMed

VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

2014-03-01

Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in understanding transmission dynamics, even for environmentally transmitted microbes like E. coli. This study is the first to use microbial genetics to construct and analyse transmission networks in a wildlife population and highlights the potential utility of an approach integrating microbial genetics with network analysis. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Weak social networks and restless sleep interrelate through depressed mood among elderly.

PubMed

Cheng, Grand H-L; Malhotra, Rahul; Chan, Angelique; Østbye, Truls; Lo, June C

2018-06-04

Sleep disturbance is common in late life. While social interaction is a basic human concern, few studies have explored the linkage between interpersonal relationships and sleep disturbance. The present study examines the reciprocal associations between weak social networks outside the household and sleep disturbance in elderly, as well as the underlying mechanisms. We utilized data from a nationally representative longitudinal survey of community-dwelling elderly in Singapore (n = 1417; ≥ 60 years). Participants were assessed three times over 6 years (2009, 2011, 2015). Measures included strength of social networks outside the household, restless sleep (sleep disturbance), and the mediating variables of depressed mood, chronic diseases, and cognitive impairment. A cross-lagged mediation analysis was conducted. Bootstrapping results showed that weaker social networks were related to more restless sleep via more depressed mood. Also, restless sleep was negatively associated with social networks through depressed mood. The other mediators examined were not significant. Weak social networks and restless sleep reciprocally influence each other through depressed mood. Recognition of this interplay can inform efforts in improving elderly's sleep quality, social networks, and psychological well-being.

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

PubMed

Sayles, Jesse S; Baggio, Jacopo A

2017-03-07

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

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

PubMed

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

2014-11-17

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

Effect of households' social networks on lice infestation among vulnerable Mexican children: a qualitative comparative analysis.

PubMed

Ortega-Marín, Lydia; Márquez-Serrano, Margarita; Lara-López, Luz M; Moncada, Ligia I; Idrovo, Alvaro J

2013-10-01

The prevalence of pediculosis is high among elementary and secondary school children, which favors the belief that infestation occurs more often in schools than in homes. This study explored the role of households' social networks in the transmission of head lice. Seventeen school children and their social networks (n = 22) from Acatlipa (Morelos, Mexico) participated in a prospective observational study during school vacation. The hair of all the school children was washed with shampoo containing permethrin at the beginning of the study and the incidence of pediculosis (O) was evaluated at the beginning of the school term (follow-up at 1.5 months). The sets included in the qualitative comparative analysis were sex (S), length of hair (H), baseline diagnostic of pediculosis (I) and degree (D) and infestation index (N) obtained through the analysis of social networks. The prevalence of pediculosis was the same at the beginning and the end of follow-up (17.6%). The degree of the school children's networks ranged between 2 and 14. There were 8 configurations, the most frequent being F*i*d*n*h. The most parsimonious configuration associated with the incidence of pediculosis was F*I*d*H (female, previous infestation, low degree and long hair), with a coverage of 0.344 and a consistency of 0.941. Indicators of social networks made it possible to identify the role of households' social networks in the transmission of lice. Individual actions such as the use of shampoo containing insecticides are temporary and, therefore, structural actions should be favored.

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.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

DTIC Science & Technology

2016-06-22

this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi...exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation... email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between

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

On the Directionality Test of Peer Effects in Social Networks

ERIC Educational Resources Information Center

An, Weihua

2016-01-01

One interesting idea in social network analysis is the directionality test that utilizes the directions of social ties to help identify peer effects. The null hypothesis of the test is that if contextual factors are the only force that affects peer outcomes, the estimated peer effects should not differ, if the directions of social ties are…

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

PubMed Central

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

2014-01-01

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

Agonistic reciprocity is associated with reduced male reproductive success within haremic social networks

PubMed Central

Solomon-Lane, Tessa K.; Pradhan, Devaleena S.; Willis, Madelyne C.; Grober, Matthew S.

2015-01-01

While individual variation in social behaviour is ubiquitous and causes social groups to differ in structure, how these structural differences affect fitness remains largely unknown. We used social network analysis of replicate bluebanded goby (Lythrypnus dalli) harems to identify the reproductive correlates of social network structure. In stable groups, we quantified agonistic behaviour, reproduction and steroid hormones, which can both affect and respond to social/reproductive cues. We identified distinct, optimal social structures associated with different reproductive measures. Male hatching success (HS) was negatively associated with agonistic reciprocity, a network structure that describes whether subordinates ‘reciprocated’ agonism received from dominants. Egg laying was associated with the individual network positions of the male and dominant female. Thus, males face a trade-off between promoting structures that facilitate egg laying versus HS. Whether this reproductive conflict is avoidable remains to be determined. We also identified different social and/or reproductive roles for 11-ketotestosterone, 17β-oestradiol and cortisol, suggesting that specific neuroendocrine mechanisms may underlie connections between network structure and fitness. This is one of the first investigations of the reproductive and neuroendocrine correlates of social behaviour and network structure in replicate, naturalistic social groups and supports network structure as an important target for natural selection. PMID:26156769

Hierarchical Network Models for Education Research: Hierarchical Latent Space Models

ERIC Educational Resources Information Center

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

2013-01-01

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

Uncovering Influence through Social Network Analysis: The Role of Schools in Education for Sustainable Development

ERIC Educational Resources Information Center

Kolleck, Nina

2016-01-01

This paper examines the implementation of Education for Sustainable Development (ESD) in Germany and explores the possibilities of Social Network Analysis (SNA) for uncovering influential actors in educational policy innovation processes. From the theoretical perspective, an actor's influence is inferred from its relative position within…

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

ERIC Educational Resources Information Center

Luhrs, Cecilia; McAnally-Salas, Lewis

2016-01-01

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

Social Network Analysis: A Simple but Powerful Tool for Identifying Teacher Leaders

ERIC Educational Resources Information Center

Smith, P. Sean; Trygstad, Peggy J.; Hayes, Meredith L.

2018-01-01

Instructional teacher leadership is central to a vision of distributed leadership. However, identifying instructional teacher leaders can be a daunting task, particularly for administrators who find themselves either newly appointed or faced with high staff turnover. This article describes the use of social network analysis (SNA), a simple but…

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

ERIC Educational Resources Information Center

Zhang, Yan

2012-01-01

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

An Exploratory Case Study of PBIS Implementation Using Social Network Analysis

ERIC Educational Resources Information Center

Whitcomb, Sara A.; Woodland, Rebecca H.; Barry, Shannon K.

2017-01-01

An exploratory case study is presented in which social network analysis (SNA) was used to explore how school teaming structures influence the implementation of School-Wide Positive Behavioral Interventions and Supports (PBIS). The authors theorized that PBIS leadership teams that include members with connections to all other information-sharing…

Modelling the public opinion transmission on social networks under opinion leaders

NASA Astrophysics Data System (ADS)

Li, Zuozhi; Li, Meng; Ji, Wanwan

2017-06-01

In this paper, based on Social Network Analysis (SNA), the social network model of opinion leaders influencing the public opinion transmission is explored. The hot event, A Female Driver Was Beaten Due To Lane Change, has characteristics of individual short-term and non-government intervention, which is used to data extraction, and formed of the network structure on opinion leaders influencing the public opinion transmission. And the evolution mechanism are analyzed in the three evolutionary situations. Opinion leaders influence micro-blogging public opinion on social network evolution model shows that this type of network public opinion transmission is largely constrained by opinion leaders, so the opinion leaders behavior supervising on the spread of this public opinion is pivotal, and which has a guiding significance.

Modeling of information diffusion in Twitter-like social networks under information overload.

PubMed

Li, Pei; Li, Wei; Wang, Hui; Zhang, Xin

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations.

Modeling of Information Diffusion in Twitter-Like Social Networks under Information Overload

PubMed Central

Li, Wei

2014-01-01

Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations. PMID:24795541

"You've got a friend in me": can social networks mediate the relationship between mood and MCI?

PubMed

Yates, Jennifer A; Clare, Linda; Woods, Robert T

2017-07-13

Social networks can change with age, for reasons that are adaptive or unwanted. Social engagement is beneficial to both mental health and cognition, and represents a potentially modifiable factor. Consequently this study explored this association and assessed whether the relationship between mild cognitive impairment (MCI) and mood problems was mediated by social networks. This study includes an analysis of data from the Cognitive Function and Ageing Study Wales (CFAS Wales). CFAS Wales Phase 1 data were collected from 2010 to 2013 by conducting structured interviews with older people aged over 65 years of age living in urban and rural areas of Wales, and included questions that assessed cognitive functioning, mood, and social networks. Regression analyses were used to investigate the associations between individual variables and the mediating role of social networks. Having richer social networks was beneficial to both mood and cognition. Participants in the MCI category had weaker social networks than participants without cognitive impairment, whereas stronger social networks were associated with a decrease in the odds of experiencing mood problems, suggesting that they may offer a protective effect against anxiety and depression. Regression analyses revealed that social networks are a significant mediator of the relationship between MCI and mood problems. These findings are important, as mood problems are a risk factor for progression from MCI to dementia, so interventions that increase and strengthen social networks may have beneficial effects on slowing the progression of cognitive decline.

Social capital calculations in economic systems: Experimental study

NASA Astrophysics Data System (ADS)

Chepurov, E. G.; Berg, D. B.; Zvereva, O. M.; Nazarova, Yu. Yu.; Chekmarev, I. V.

2017-11-01

The paper describes the social capital study for a system where actors are engaged in an economic activity. The focus is on the analysis of communications structural parameters (transactions) between the actors. Comparison between transaction network graph structure and the structure of a random Bernoulli graph of the same dimension and density allows revealing specific structural features of the economic system under study. Structural analysis is based on SNA-methodology (SNA - Social Network Analysis). It is shown that structural parameter values of the graph formed by agent relationship links may well characterize different aspects of the social capital structure. The research advocates that it is useful to distinguish the difference between each agent social capital and the whole system social capital.

Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

Evaluating the Network: A Workflow for Tracking Twitter Interactions Using Social Networking Analysis

ERIC Educational Resources Information Center

Goodier, Sarah

2018-01-01

Networking plays an important role in research projects to build a community and audience around a research area. Using social media is popular in project communication as it provides the ability to engage with a group of followers daily. Such online networking tools provide the advantage of providing nearrealtime data, which can be used to…

Emergence, evolution and scaling of online social networks.

PubMed

Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

2014-01-01

Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

Fishing in the Amazonian forest: a gendered social network puzzle

PubMed Central

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

2016-01-01

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

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

PubMed

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

2017-01-01

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

Advantages of Social Network Analysis in Educational Research

ERIC Educational Resources Information Center

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

2015-01-01

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

Measuring Creative Potential: Using Social Network Analysis to Monitor a Learners' Creative Capacity

ERIC Educational Resources Information Center

Dawson, Shane; Tan, Jennifer Pei Ling; McWilliam, Erica

2011-01-01

Despite the burgeoning rhetoric from political, social and educational commentators regarding creativity and learning and teaching, there is a paucity of scalable and measurable examples of creativity-centric pedagogical practice. This paper makes an argument for the application of social network visualisations to inform and support…

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.

Combining network analysis with Cognitive Work Analysis: insights into social organisational and cooperation analysis.

PubMed

Houghton, Robert J; Baber, Chris; Stanton, Neville A; Jenkins, Daniel P; Revell, Kirsten

2015-01-01

Cognitive Work Analysis (CWA) allows complex, sociotechnical systems to be explored in terms of their potential configurations. However, CWA does not explicitly analyse the manner in which person-to-person communication is performed in these configurations. Consequently, the combination of CWA with Social Network Analysis provides a means by which CWA output can be analysed to consider communication structure. The approach is illustrated through a case study of a military planning team. The case study shows how actor-to-actor and actor-to-function mapping can be analysed, in terms of centrality, to produce metrics of system structure under different operating conditions. In this paper, a technique for building social network diagrams from CWA is demonstrated.The approach allows analysts to appreciate the potential impact of organisational structure on a command system.

Social networking strategies that aim to reduce obesity have achieved significant although modest results.

PubMed

Ashrafian, Hutan; Toma, Tania; Harling, Leanne; Kerr, Karen; Athanasiou, Thanos; Darzi, Ara

2014-09-01

The global epidemic of obesity continues to escalate. Obesity accounts for an increasing proportion of the international socioeconomic burden of noncommunicable disease. Online social networking services provide an effective medium through which information may be exchanged between obese and overweight patients and their health care providers, potentially contributing to superior weight-loss outcomes. We performed a systematic review and meta-analysis to assess the role of these services in modifying body mass index (BMI). Our analysis of twelve studies found that interventions using social networking services produced a modest but significant 0.64 percent reduction in BMI from baseline for the 941 people who participated in the studies' interventions. We recommend that social networking services that target obesity should be the subject of further clinical trials. Additionally, we recommend that policy makers adopt reforms that promote the use of anti-obesity social networking services, facilitate multistakeholder partnerships in such services, and create a supportive environment to confront obesity and its associated noncommunicable diseases. Project HOPE—The People-to-People Health Foundation, Inc.

The Impact of Drug Use in Social Networks of Patients with Substance Use and Bipolar Disorders

PubMed Central

McDonald, Leah J.; Griffin, Margaret L.; Kolodziej, Monika E.; Fitzmaurice, Garrett M.; Weiss, Roger D.

2011-01-01

In this exploratory analysis, we assessed the effect of drug use among social network members on recovery from drug dependence in patients with co-occurring bipolar disorder. Patients (n=57) enrolled in a group therapy study completed assessments over 15 months. Patients with 0–1 drug users in their social networks at intake had few days of drug use during treatment and follow-up, whereas those with ≥ 2 drug users had significantly more days of drug use. Multivariate analysis showed that patients who consistently named multiple drug users in their social networks had a marked increase in drug use over 15 months, while those who never or occasionally named multiple drug users had a small decline in drug use over time. Multiple drug users in social networks of treatment-seeking drug dependent patients with co-occurring bipolar disorder may indicate poor drug use outcomes; efforts to reduce the association with drug users may be useful. This clinical trial has been registered in a public trials registry at clinicaltrials.gov (identifier is NCT00227838). PMID:21314751

Incorporating social network effects into cost-effectiveness analysis: a methodological contribution with application to obesity prevention

PubMed Central

Konchak, Chad; Prasad, Kislaya

2012-01-01

Objectives To develop a methodology for integrating social networks into traditional cost-effectiveness analysis (CEA) studies. This will facilitate the economic evaluation of treatment policies in settings where health outcomes are subject to social influence. Design This is a simulation study based on a Markov model. The lifetime health histories of a cohort are simulated, and health outcomes compared, under alternative treatment policies. Transition probabilities depend on the health of others with whom there are shared social ties. Setting The methodology developed is shown to be applicable in any healthcare setting where social ties affect health outcomes. The example of obesity prevention is used for illustration under the assumption that weight changes are subject to social influence. Main outcome measures Incremental cost-effectiveness ratio (ICER). Results When social influence increases, treatment policies become more cost effective (have lower ICERs). The policy of only treating individuals who span multiple networks can be more cost effective than the policy of treating everyone. This occurs when the network is more fragmented. Conclusions (1) When network effects are accounted for, they result in very different values of incremental cost-effectiveness ratios (ICERs). (2) Treatment policies can be devised to take network structure into account. The integration makes it feasible to conduct a cost-benefit evaluation of such policies. PMID:23117559

Network Science Center Research Team’s Visit to Kampala, Uganda

DTIC Science & Technology

2013-07-01

Religious Leader • Someone in Social Network • Commercial Bank • White Collar Professional • Military Leader 18 | P a g e Network Science...relationship between the person under analysis and the people within the social network (Van Der Gaag & Snijders, 2004). 2 | P a g e Network...energetic and tech savvy. 3 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 Our team’s next data collection effort

A Preliminary Examination of the Relationship Between Social Networking Interactions, Internet Use, and Thwarted Belongingness.

PubMed

Moberg, Fallon B; Anestis, Michael D

2015-01-01

Joiner's (2005) interpersonal-psychological theory of suicide hypothesizes that suicidal desire develops in response to the joint presence of thwarted belongingness and perceived burdensomeness. To consider the potential influence of online interactions and behaviors on these outcomes. To address this, we administered an online protocol assessing suicidal desire and online interactions in a sample of 305 undergraduates (83.6% female). We hypothesized negative interactions on social networking sites and a preference for online social interactions would be associated with thwarted belongingness. We also conducted an exploratory analysis examining the associations between Internet usage and perceived burdensomeness. Higher levels of negative interactions on social networking sites, but no other variables, significantly predicted thwarted belongingness. Our exploratory analysis showed that none of our predictors were associated with perceived burdensomeness after accounting for demographics, depression, and thwarted belongingness. Our findings indicate that a general tendency to have negative interactions on social networking sites could possibly impact suicidal desire and that these effects are significant above and beyond depression symptoms. Furthermore, no other aspect of problematic Internet use significantly predicted our outcomes in multivariate analyses, indicating that social networking in particular may have a robust effect on thwarted belongingness.

Independence through social networks: bridging potential among older women and men.

PubMed

Cornwell, Benjamin

2011-11-01

Most studies of older adults' social networks focus on their access to dense networks that yield access to social support. This paper documents gender differences in the extent to which older adults maintain a related, but distinct, form of social capital-bridging potential, which involves serving as a tie between two unconnected parties and thus boosts independence and control of everyday social life. I use egocentric social network data from a national sample of 3,005 older adults--collected in 2005-2006 by the National Social Life, Health, and Aging Project--to compare older men's and women's network bridging potential using multivariate regression analysis. Older women are more likely than older men to have bridging potential in their networks-between both kin and non-kin contacts. These gender differences increase with age. Older women are also more likely to have network members who are not connected to or monopolized by their spouse or partner. Some, but not all, of these gender differences are due to the fact that older women have larger social networks and maintain more ties to people outside of the household. These findings raise important questions about the relational advantages older women have over older men, including greater autonomy, and contradict stereotypes about women having more closely knit, kin-centered networks than men.

A new similarity measure for link prediction based on local structures in social networks

NASA Astrophysics Data System (ADS)

Aghabozorgi, Farshad; Khayyambashi, Mohammad Reza

2018-07-01

Link prediction is a fundamental problem in social network analysis. There exist a variety of techniques for link prediction which applies the similarity measures to estimate proximity of vertices in the network. Complex networks like social networks contain structural units named network motifs. In this study, a newly developed similarity measure is proposed where these structural units are applied as the source of similarity estimation. This similarity measure is tested through a supervised learning experiment framework, where other similarity measures are compared with this similarity measure. The classification model trained with this similarity measure outperforms others of its kind.

The Private Lives of Minerals: Social Network Analysis Applied to Mineralogy and Petrology

NASA Astrophysics Data System (ADS)

Hazen, R. M.; Morrison, S. M.; Fox, P. A.; Golden, J. J.; Downs, R. T.; Eleish, A.; Prabhu, A.; Li, C.; Liu, C.

2016-12-01

Comprehensive databases of mineral species (rruff.info/ima) and their geographic localities and co-existing mineral assemblages (mindat.org) reveal patterns of mineral association and distribution that mimic social networks, as commonly applied to such varied topics as social media interactions, the spread of disease, terrorism networks, and research collaborations. Applying social network analysis (SNA) to common assemblages of rock-forming igneous and regional metamorphic mineral species, we find patterns of cohesion, segregation, density, and cliques that are similar to those of human social networks. These patterns highlight classic trends in lithologic evolution and are illustrated with sociograms, in which mineral species are the "nodes" and co-existing species form "links." Filters based on chemistry, age, structural group, and other parameters highlight visually both familiar and new aspects of mineralogy and petrology. We quantify sociograms with SNA metrics, including connectivity (based on the frequency of co-occurrence of mineral pairs), homophily (the extent to which co-existing mineral species share compositional and other characteristics), network closure (based on the degree of network interconnectivity), and segmentation (as revealed by isolated "cliques" of mineral species). Exploitation of large and growing mineral data resources with SNA offers promising avenues for discovering previously hidden trends in mineral diversity-distribution systematics, as well as providing new pedagogical approaches to teaching mineralogy and petrology.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

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

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.

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

PubMed

Grunspan, Daniel Z; Wiggins, Benjamin L; Goodreau, Steven M

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Network Analysis of an Emergent Massively Collaborative Creation on Video Sharing Website

NASA Astrophysics Data System (ADS)

Hamasaki, Masahiro; Takeda, Hideaki; Nishimura, Takuichi

The Web technology enables numerous people to collaborate in creation. We designate it as massively collaborative creation via the Web. As an example of massively collaborative creation, we particularly examine video development on Nico Nico Douga, which is a video sharing website that is popular in Japan. We specifically examine videos on Hatsune Miku, a version of a singing synthesizer application software that has inspired not only song creation but also songwriting, illustration, and video editing. As described herein, creators of interact to create new contents through their social network. In this paper, we analyzed the process of developing thousands of videos based on creators' social networks and investigate relationships among creation activity and social networks. The social network reveals interesting features. Creators generate large and sparse social networks including some centralized communities, and such centralized community's members shared special tags. Different categories of creators have different roles in evolving the network, e.g., songwriters gather more links than other categories, implying that they are triggers to network evolution.

Social network modulation of reward-related signals

PubMed Central

Fareri, Dominic S.; Niznikiewicz, Michael A.; Lee, Victoria K.; Delgado, Mauricio R.

2012-01-01

Everyday goals and experiences are often shared with others who may hold different places within our social networks. We investigated whether the experience of sharing a reward differs with respect to social network. Twenty human participants played a card guessing game for shared monetary outcomes with three partners: a computer, a confederate (out-of-network), and a friend (in-network). Participants subjectively rated the experience of sharing a reward more positively with their friend than the other partners. Neuroimaging results support participants’ subjective reports, as ventral striatal BOLD responses were more robust when sharing monetary gains with a friend, as compared to with the confederate or computer, suggesting a higher value for sharing with an in-network partner. Interestingly, ratings of social closeness co-varied with this activity, resulting in a significant partner × closeness interaction: exploratory analysis showed that only participants reporting higher levels of closeness demonstrated partner-related differences in striatal BOLD response. These results suggest that reward valuation in social contexts is sensitive to distinctions of social network, such that sharing positive experiences with in-network others may carry higher value. PMID:22745503

Social network analysis of children with autism spectrum disorder: Predictors of fragmentation and connectivity in elementary school classrooms

PubMed Central

Anderson, Ariana; Locke, Jill; Kretzmann, Mark; Kasari, Connie

2016-01-01

Although children with autism spectrum disorder are frequently included in mainstream classrooms, it is not known how their social networks change compared to typically developing children and whether the factors predictive of this change may be unique. This study identified and compared predictors of social connectivity of children with and without autism spectrum disorder using a social network analysis. Participants included 182 children with autism spectrum disorder and 152 children without autism spectrum disorder, aged 5–12 years in 152 general education K-5 classrooms. General linear models were used to compare how age, classroom size, gender, baseline connectivity, diagnosis, and intelligence quotient predicted changes in social connectivity (closeness). Gender and classroom size had a unique interaction in predicting final social connectivity and the change in connectivity for children with autism spectrum disorder; boys who were placed in larger classrooms showed increased social network fragmentation. This increased fragmentation for boys when placed in larger classrooms was not seen in typically developing boys. These results have implications regarding placement, intervention objectives, and ongoing school support that aimed to increase the social success of children with autism spectrum disorder in public schools. PMID:26567264

Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

PubMed Central

Zare-Farashbandi, Firoozeh; Geraei, Ehsan; Siamaki, Saba

2014-01-01

Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS) during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true. PMID:24672564

Having mentors and campus social networks moderates the impact of worries and video gaming on depressive symptoms: a moderated mediation analysis

PubMed Central

2014-01-01

Background Easy access to the internet has spawned a wealth of research to investigate the effects of its use on depression. However, one limitation of many previous studies is that they disregard the interactive mechanisms of risk and protective factors. The aim of the present study was to investigate a resilience model in the relationship between worry, daily internet video game playing, daily sleep duration, mentors, social networks and depression, using a moderated mediation analysis. Methods 6068 Korean undergraduate and graduate students participated in this study. The participants completed a web-based mental health screening questionnaire including the Beck Depression Inventory (BDI) and information about number of worries, number of mentors, number of campus social networks, daily sleep duration, daily amount of internet video game playing and daily amount of internet searching on computer or smartphone. A moderated mediation analysis was carried out using the PROCESS macro which allowed the inclusion of mediators and moderator in the same model. Results The results showed that the daily amount of internet video game playing and daily sleep duration partially mediated the association between the number of worries and the severity of depression. In addition, the mediating effect of the daily amount of internet video game playing was moderated by both the number of mentors and the number of campus social networks. Conclusions The current findings indicate that the negative impact of worry on depression through internet video game playing can be buffered when students seek to have a number of mentors and campus social networks. Interventions should therefore target individuals who have higher number of worries but seek only a few mentors or campus social networks. Social support via campus mentorship and social networks ameliorate the severity of depression in university students. PMID:24884864

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.

A Social Network Analysis of the National Materials Competency at Naval Air Systems Command

DTIC Science & Technology

2002-09-01

language held by individuals within the structure. (Lesser, 2000, p. 4) Bourdieu defines social capital as decomposable into two elements: first, the...The fundamental proposition of social capital theory is that the network ties provide access to resources and that social relations constitute...transferring knowledge are being identified as a central element of organizational advantage. Social capital theory provides a sounds basis for explaining

Reappraisal of Social Network Research in Educational Contexts.

ERIC Educational Resources Information Center

Scherer, Jacqueline

Three network studies in education are reviewed in order to assess the current "state of the art." New directions for developing social network analysis (SNA) in education, based upon experiences from a study of school-community relations in Pontiac, Michigan, are suggested. One concern for the future of SNA stems from the elevation of…

Network Financial Support and Conflict as Predictors of Depressive Symptoms among a Highly Disadvantaged Population

ERIC Educational Resources Information Center

Knowlton, Amy R.; Latkin, Carl A.

2007-01-01

The study examined multiple dimensions of social support as predictors of depressive symptoms among a highly vulnerable population. Social network analysis was used to assess perceived and enacted dimensions of support (emotional, financial, instrumental), network conflict, closeness, and composition. Participants were 393 current and former…

Understanding Groups in Outdoor Adventure Education through Social Network Analysis

ERIC Educational Resources Information Center

Jostad, Jeremy; Sibthorp, Jim; Paisley, Karen

2013-01-01

Relationships are a critical component to the experience of an outdoor adventure education (OAE) program, therefore, more fruitful ways of investigating groups is needed. Social network analysis (SNA) is an effective tool to study the relationship structure of small groups. This paper provides an explanation of SNA and shows how it was used by the…

Critical Social Network Analysis in Community Colleges: Peer Effects and Credit Attainment

ERIC Educational Resources Information Center

González Canché, Manuel S.; Rios-Aguilar, Cecilia

2014-01-01

This chapter discusses the importance of conducting critical social network analysis (CSNA) in higher education. To illustrate the benefits of CSNA, the authors use existing institutional data to examine peer effects in community colleges. The chapter ends with a discussion of the implications of using a CSNA approach to measure inequities in…

Cliques and Cohesion in a Clinical Psychology Graduate Cohort: A Longitudinal Social Network Analysis

ERIC Educational Resources Information Center

Kunze, Kimberley Annette

2013-01-01

To date, no published research has utilized social network analysis (SNA) to analyze graduate cohorts in clinical psychology. The purpose of this research is to determine how issues of likability among students correlate with other measures, such as disclosure, health, spiritual maturity, help in projects, familiarity, and ease of providing…

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.

Twitter=quitter? An analysis of Twitter quit smoking social networks.

PubMed

Prochaska, Judith J; Pechmann, Cornelia; Kim, Romina; Leonhardt, James M

2012-07-01

Widely popular, Twitter, a free social networking and micro-blogging service, offers potential for health promotion. This study examined the activity of Twitter quit smoking social network accounts. A cross-sectional analysis identified 153 activated Twitter quit smoking accounts dating back to 2007 and examined recent account activity for the month of August 2010. The accounts had a median of 155 followers and 82 total tweets per account; 49% of accounts had >100 tweets. Posted content was largely inconsistent with clinical guidelines; 48% linked to commercial sites for quitting smoking and 43% had tweets on e-cigarettes. In August 2010, 81 of the accounts (53%) were still active. Though popular for building quit smoking social networks, many of the Twitter accounts were no longer active, and tweet content was largely inconsistent with clinical guidelines. Future research is needed to examine the effectiveness of Twitter for supporting smoking cessation.

NetIntel: A Database for Manipulation of Rich Social Network Data

DTIC Science & Technology

2005-03-03

between entities in a social or organizational system. For most of its history , social network analysis has operated on a notion of a dataset - a clearly...and procedural), as well as stored procedure and trigger capabilities. For the current implementation, we have chosen PostgreSQL [1] database. Of the...data and easy-to-use facilities for export of data into analysis tools as well as online browsing and data entry. References [1] Postgresql

Complex social contagion makes networks more vulnerable to disease outbreaks.

PubMed

Campbell, Ellsworth; Salathé, Marcel

2013-01-01

Social network analysis is now widely used to investigate the dynamics of infectious disease spread. Vaccination dramatically disrupts disease transmission on a contact network, and indeed, high vaccination rates can potentially halt disease transmission altogether. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread across social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model health behavior and infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This dynamic variability results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

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

PubMed Central

Litwin, Howard; Shiovitz-Ezra, Sharon

2011-01-01

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

Social Network Behavior and Engagement Within a Smoking Cessation Facebook Page.

PubMed

Cole-Lewis, Heather; Perotte, Adler; Galica, Kasia; Dreyer, Lindy; Griffith, Christopher; Schwarz, Mary; Yun, Christopher; Patrick, Heather; Coa, Kisha; Augustson, Erik

2016-08-02

Social media platforms are increasingly being used to support individuals in behavior change attempts, including smoking cessation. Examining the interactions of participants in health-related social media groups can help inform our understanding of how these groups can best be leveraged to facilitate behavior change. The aim of this study was to analyze patterns of participation, self-reported smoking cessation length, and interactions within the National Cancer Institutes' Facebook community for smoking cessation support. Our sample consisted of approximately 4243 individuals who interacted (eg, posted, commented) on the public Smokefree Women Facebook page during the time of data collection. In Phase 1, social network visualizations and centrality measures were used to evaluate network structure and engagement. In Phase 2, an inductive, thematic qualitative content analysis was conducted with a subsample of 500 individuals, and correlational analysis was used to determine how participant engagement was associated with self-reported session length. Between February 2013 and March 2014, there were 875 posts and 4088 comments from approximately 4243 participants. Social network visualizations revealed the moderator's role in keeping the community together and distributing the most active participants. Correlation analyses suggest that engagement in the network was significantly inversely associated with cessation status (Spearman correlation coefficient = -0.14, P=.03, N=243). The content analysis of 1698 posts from 500 randomly selected participants identified the most frequent interactions in the community as providing support (43%, n=721) and announcing number of days smoke free (41%, n=689). These findings highlight the importance of the moderator for network engagement and provide helpful insights into the patterns and types of interactions participants are engaging in. This study adds knowledge of how the social network of a smoking cessation community behaves within the confines of a Facebook group.

Social Support: A Mixed Blessing for Women in Substance Abuse Treatment

PubMed Central

Tracy, Elizabeth M.; Munson, Michelle R.; Peterson, Lance T.; Floersch, Jerry E.

2010-01-01

Using a personal social network framework, this qualitative study sought to understand how women in substance abuse treatment describe their network members' supportive and unsupportive behaviors related to recovery. Eighty-six women were interviewed from residential and outpatient substance abuse treatment programs. Positive and negative aspects of women's social networks were assessed via open-ended questions. Analysis was guided by grounded theory techniques using three coders. The findings extend classic social support concepts such as emotional, tangible, and informational support. Practice implications are presented in light of the potential roles network members may play in substance use and recovery. PMID:20953326

The role of social support and social networks in health information-seeking behavior among Korean Americans: a qualitative study.

PubMed

Kim, Wonsun; Kreps, Gary L; Shin, Cha-Nam

2015-04-28

This study used social network theory to explore the role of social support and social networks in health information-seeking behavior among Korean American (KA) adults. A descriptive qualitative study using a web-based online survey was conducted from January 2013 to April 2013 in the U.S. The survey included open-ended questions about health information-seeking experiences in personal social networks and their importance in KA adults. Themes emerging from a constant comparative analysis of the narrative comments by 129 of the 202 respondents were analyzed. The sample consisted of 129 KA adults, 64.7% female, with a mean age of 33.2 (SD = 7.7). Friends, church members, and family members were the important network connections for KAs to obtain health information. KAs looked for a broad range of health information from social network members, from recommendations and reviews of hospitals/doctors to specific diseases or health conditions. These social networks were regarded as important for KAs because there were no language barriers, social network members had experiences similar to those of other KAs, they felt a sense of belonging with those in their networks, the network connections promoted increased understanding of different health care systems of the U.S. system, and communication with these network connections helped enhance feelings of being physically and mentally healthy. This study demonstrates the important role that social support and personal social networks perform in the dissemination of health information for a large ethnic population, KAs, who confront distinct cultural challenges when seeking health information in the U.S. Data from this study also illustrate the cultural factors that influence health information acquisition and access to social support for ethnic minorities. This study provides practical insights for professionals in health information services, namely, that social networks can be employed as a channel for disseminating health information to immigrants.

Information seeking for making evidence-informed decisions: a social network analysis on the staff of a public health department in Canada

PubMed Central

2012-01-01

Background Social network analysis is an approach to study the interactions and exchange of resources among people. It can help understanding the underlying structural and behavioral complexities that influence the process of capacity building towards evidence-informed decision making. A social network analysis was conducted to understand if and how the staff of a public health department in Ontario turn to peers to get help incorporating research evidence into practice. Methods The staff were invited to respond to an online questionnaire inquiring about information seeking behavior, identification of colleague expertise, and friendship status. Three networks were developed based on the 170 participants. Overall shape, key indices, the most central people and brokers, and their characteristics were identified. Results The network analysis showed a low density and localized information-seeking network. Inter-personal connections were mainly clustered by organizational divisions; and people tended to limit information-seeking connections to a handful of peers in their division. However, recognition of expertise and friendship networks showed more cross-divisional connections. Members of the office of the Medical Officer of Health were located at the heart of the department, bridging across divisions. A small group of professional consultants and middle managers were the most-central staff in the network, also connecting their divisions to the center of the information-seeking network. In each division, there were some locally central staff, mainly practitioners, who connected their neighboring peers; but they were not necessarily connected to other experts or managers. Conclusions The methods of social network analysis were useful in providing a systems approach to understand how knowledge might flow in an organization. The findings of this study can be used to identify early adopters of knowledge translation interventions, forming Communities of Practice, and potential internal knowledge brokers. PMID:22591757

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 'friendship dynamics of religion,' or the 'religious dynamics of friendship'? A social network analysis of adolescents who attend small schools.

PubMed

Cheadle, Jacob E; Schwadel, Philip

2012-09-01

Longitudinal social network data on adolescents in seven schools are analyzed to reach a new understanding about how the personal and interpersonal social dimensions of adolescent religion intertwine together in small school settings. We primarily address two issues relevant to the sociology of religion and sociology in general: (1) social selection as a source of religious homophily and (2) friend socialization of religion. Analysis results are consistent with Collins' interaction ritual chain theory, which stresses the social dimensions of religion, since network-religion autocorrelations are relatively substantial in magnitude and both selection and socialization mechanisms play key roles in generating them. Results suggest that socialization plays a stronger role than social selection in four of six religious outcomes, and that more religious youth are more cliquish. Implications for our understanding of the social context of religion, religious homophily, and the ways we model religious influence, as well as limitations and considerations for future research, are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

The importance of delineating networks by activity type in bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida.

PubMed

Gazda, Stefanie; Iyer, Swami; Killingback, Timothy; Connor, Richard; Brault, Solange

2015-03-01

Network analysis has proved to be a valuable tool for studying the behavioural patterns of complex social animals. Often such studies either do not distinguish between different behavioural states of the organisms or simply focus attention on a single behavioural state to the exclusion of all others. In either of these approaches it is impossible to ascertain how the behavioural patterns of individuals depend on the type of activity they are engaged in. Here we report on a network-based analysis of the behavioural associations in a population of bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida. We consider three distinct behavioural states-socializing, travelling and foraging-and analyse the association networks corresponding to each activity. Moreover, in constructing the different activity networks we do not simply record a spatial association between two individuals as being either present or absent, but rather quantify the degree of any association, thus allowing us to construct weighted networks describing each activity. The results of these weighted activity networks indicate that networks can reveal detailed patterns of bottlenose dolphins at the population level; dolphins socialize in large groups with preferential associations; travel in small groups with preferential associates; and spread out to forage in very small, weakly connected groups. There is some overlap in the socialize and travel networks but little overlap between the forage and other networks. This indicates that the social bonds maintained in other activities are less important as they forage on dispersed, solitary prey. The overall network, not sorted by activity, does not accurately represent any of these patterns.

The importance of delineating networks by activity type in bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida

PubMed Central

Gazda, Stefanie; Iyer, Swami; Killingback, Timothy; Connor, Richard; Brault, Solange

2015-01-01

Network analysis has proved to be a valuable tool for studying the behavioural patterns of complex social animals. Often such studies either do not distinguish between different behavioural states of the organisms or simply focus attention on a single behavioural state to the exclusion of all others. In either of these approaches it is impossible to ascertain how the behavioural patterns of individuals depend on the type of activity they are engaged in. Here we report on a network-based analysis of the behavioural associations in a population of bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida. We consider three distinct behavioural states—socializing, travelling and foraging—and analyse the association networks corresponding to each activity. Moreover, in constructing the different activity networks we do not simply record a spatial association between two individuals as being either present or absent, but rather quantify the degree of any association, thus allowing us to construct weighted networks describing each activity. The results of these weighted activity networks indicate that networks can reveal detailed patterns of bottlenose dolphins at the population level; dolphins socialize in large groups with preferential associations; travel in small groups with preferential associates; and spread out to forage in very small, weakly connected groups. There is some overlap in the socialize and travel networks but little overlap between the forage and other networks. This indicates that the social bonds maintained in other activities are less important as they forage on dispersed, solitary prey. The overall network, not sorted by activity, does not accurately represent any of these patterns. PMID:26064611

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.

"Us and them": a social network analysis of physicians' professional networks and their attitudes towards EBM.

PubMed

Mascia, Daniele; Cicchetti, Americo; Damiani, Gianfranco

2013-10-22

Extant research suggests that there is a strong social component to Evidence-Based Medicine (EBM) adoption since professional networks amongst physicians are strongly associated with their attitudes towards EBM. Despite this evidence, it is still unknown whether individual attitudes to use scientific evidence in clinical decision-making influence the position that physicians hold in their professional network. This paper explores how physicians' attitudes towards EBM is related to the network position they occupy within healthcare organizations. Data pertain to a sample of Italian physicians, whose professional network relationships, demographics and work-profile characteristics were collected. A social network analysis was performed to capture the structural importance of physicians in the collaboration network by the means of a core-periphery analysis and the computation of network centrality indicators. Then, regression analysis was used to test the association between the network position of individual clinicians and their attitudes towards EBM. Findings documented that the overall network structure is made up of a dense cohesive core of physicians and of less connected clinicians who occupy the periphery. A negative association between the physicians' attitudes towards EBM and the coreness they exhibited in the professional network was also found. Network centrality indicators confirmed these results documenting a negative association between physicians' propensity to use EBM and their structural importance in the professional network. Attitudes that physicians show towards EBM are related to the part (core or periphery) of the professional networks to which they belong as well as to their structural importance. By identifying virtuous attitudes and behaviors of professionals within their organizations, policymakers and executives may avoid marginalization and stimulate integration and continuity of care, both within and across the boundaries of healthcare providers.

The Art of Athlete Leadership: Identifying High-Quality Athlete Leadership at the Individual and Team Level Through Social Network Analysis.

PubMed

Fransen, Katrien; Van Puyenbroeck, Stef; Loughead, Todd M; Vanbeselaere, Norbert; De Cuyper, Bert; Vande Broek, Gert; Boen, Filip

2015-06-01

This research aimed to introduce social network analysis as a novel technique in sports teams to identify the attributes of high-quality athlete leadership, both at the individual and at the team level. Study 1 included 25 sports teams (N = 308 athletes) and focused on athletes' general leadership quality. Study 2 comprised 21 sports teams (N = 267 athletes) and focused on athletes' specific leadership quality as a task, motivational, social, and external leader. The extent to which athletes felt connected with their leader proved to be most predictive for athletes' perceptions of that leader's quality on each leadership role. Also at the team level, teams with higher athlete leadership quality were more strongly connected. We conclude that social network analysis constitutes a valuable tool to provide more insight in the attributes of high-quality leadership both at the individual and at the team level.

Exploiting the Use of Social Networking to Facilitate Collaboration in the Scientific Community

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

Coppock, Edrick G.

The goal of this project was to exploit social networking to facilitate scientific collaboration. The project objective was to research and identify scientific collaboration styles that are best served by social networking applications and to model the most effective social networking applications to substantiate how social networking can support scientific collaboration. To achieve this goal and objective, the project was to develop an understanding of the types of collaborations conducted by scientific researchers, through classification, data analysis and identification of unique collaboration requirements. Another technical objective in support of this goal was to understand the current state of technology inmore » collaboration tools. In order to test hypotheses about which social networking applications effectively support scientific collaboration the project was to create a prototype scientific collaboration system. The ultimate goal for testing the hypotheses and research of the project was to refine the prototype into a functional application that could effectively facilitate and grow collaboration within the U.S. Department of Energy (DOE) research community.« less

The influence of self-exempting beliefs and social networks on daily smoking: a mediation relationship explored.

PubMed

Yang, Xiaozhao Y; Kelly, Brian C; Yang, Tingzhong

2014-09-01

The decision to initiate, maintain, or quit cigarette smoking is structured by both social networks and health beliefs. Self-exempting beliefs affect people's decisions in favor of a behavior even when they recognize the harm associated with it. This study incorporated the literatures on social networks and self-exempting beliefs to study the problem of daily smoking by exploring their mediatory relationships and the mechanisms of how smoking behavior is developed and maintained. Specifically, this article hypothesizes that social networks affect daily smoking directly as well as indirectly by facilitating the formation of self-exempting beliefs. The sample comes from urban male residents in Hangzhou, China randomly selected and interviewed through multistage sampling in 2011. Using binary mediation analysis with logistic regression to test the hypotheses, the authors found that (a) daily smoking is associated with having smokers in several social network arenas and (b) self-exempting beliefs about smoking mediate the association between coworker network and daily smoking, but not for family network and friend network. The role of social network at work place in the creation and maintenance of self-exempting beliefs should be considered by policymakers, prevention experts, and interventionists.

Age and Gender Differences in Social Network Composition and Social Support Among Older Rural South Africans: Findings From the HAALSI Study.

PubMed

Harling, Guy; Morris, Katherine Ann; Manderson, Lenore; Perkins, Jessica M; Berkman, Lisa F

2018-03-26

Drawing on the "Health and Aging in Africa: A Longitudinal Study of an INDEPTH community in South Africa" (HAALSI) baseline survey, we present data on older adults' social networks and receipt of social support in rural South Africa. We examine how age and gender differences in social network characteristics matched with patterns predicted by theories of choice- and constraint-based network contraction in older adults. We used regression analysis on data for 5,059 South African adults aged 40 and older. Older respondents reported fewer important social contacts and less frequent communication than their middle-aged peers, largely due to fewer nonkin connections. Network size difference between older and younger respondents was greater for women than for men. These gender and age differences were explicable by much higher levels of widowhood among older women compared to younger women and older men. There was no evidence for employment-related network contraction or selective retention of emotionally supportive ties. Marriage-related structural constraints impacted on older women's social networks in rural South Africa, but did not explain choice-based network contraction. These findings suggest that many older women in rural Africa, a growing population, may have an unmet need for social support.

Modeling Temporal Variation in Social Network: An Evolutionary Web Graph Approach

NASA Astrophysics Data System (ADS)

Mitra, Susanta; Bagchi, Aditya

A social network is a social structure between actors (individuals, organization or other social entities) and indicates the ways in which they are connected through various social relationships like friendships, kinships, professional, academic etc. Usually, a social network represents a social community, like a club and its members or a city and its citizens etc. or a research group communicating over Internet. In seventies Leinhardt [1] first proposed the idea of representing a social community by a digraph. Later, this idea became popular among other research workers like, network designers, web-service application developers and e-learning modelers. It gave rise to a rapid proliferation of research work in the area of social network analysis. Some of the notable structural properties of a social network are connectedness between actors, reachability between a source and a target actor, reciprocity or pair-wise connection between actors with bi-directional links, centrality of actors or the important actors having high degree or more connections and finally the division of actors into sub-structures or cliques or strongly-connected components. The cycles present in a social network may even be nested [2, 3]. The formal definition of these structural properties will be provided in Sect. 8.2.1. The division of actors into cliques or sub-groups can be a very important factor for understanding a social structure, particularly the degree of cohesiveness in a community. The number, size, and connections among the sub-groups in a network are useful in understanding how the network, as a whole, is likely to behave.

From sparse to dense and from assortative to disassortative in online social networks

PubMed Central

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-01-01

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703

From sparse to dense and from assortative to disassortative in online social networks.

PubMed

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-05-06

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.

Social Networks and Health: Understanding the Nuances of Healthcare Access between Urban and Rural Populations.

PubMed

Amoah, Padmore Adusei; Edusei, Joseph; Amuzu, David

2018-05-13

Communities and individuals in many sub-Saharan African countries often face limited access to healthcare. Hence, many rely on social networks to enhance their chances for adequate health care. While this knowledge is well-established, little is known about the nuances of how different population groups activate these networks to improve access to healthcare. This paper examines how rural and urban dwellers in the Ashanti Region in Ghana distinctively and systematically activate their social networks to enhance access to healthcare. It uses a qualitative cross-sectional design, with in-depth interviews of 79 primary participants (28 urban and 51 rural residents) in addition to the views of eight community leaders and eight health personnel. It was discovered that both intimate and distanced social networks for healthcare are activated at different periods by rural and urban residents. Four main stages of social networks activation, comprising different individuals and groups were observed among rural and urban dwellers. Among both groups, physical proximity, privacy, trust and sense of fairness, socio-cultural meaning attached to health problems, and perceived knowledge and other resources (mainly money) held in specific networks inherently influenced social network activation. The paper posits that a critical analysis of social networks may help to tailor policy contents to individuals and groups with limited access to healthcare.

Social Networks and Adaptation to Environmental Change: The Case of Central Oregon's Fire-Prone Forest Landscape

NASA Astrophysics Data System (ADS)

Fischer, A.

2012-12-01

Social networks are the patterned interactions among individuals and organizations through which people refine their beliefs and values, negotiate meanings for things and develop behavioral intentions. The structure of social networks has bearing on how people communicate information, generate and retain knowledge, make decisions and act collectively. Thus, social network structure is important for how people perceive, shape and adapt to the environment. We investigated the relationship between social network structure and human adaptation to wildfire risk in the fire-prone forested landscape of Central Oregon. We conducted descriptive and non-parametric social network analysis on data gathered through interviews to 1) characterize the structure of the network of organizations involved in forest and wildfire issues and 2) determine whether network structure is associated with organizations' beliefs, values and behaviors regarding fire and forest management. Preliminary findings indicate that fire protection and forest-related organizations do not frequently communicate or cooperate, suggesting that opportunities for joint problem-solving, innovation and collective action are limited. Preliminary findings also suggest that organizations with diverse partners are more likely to hold adaptive beliefs about wildfire and work cooperatively. We discuss the implications of social network structure for adaptation to changing environmental conditions such as wildfire risk.

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

Naturalistic FMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception.

PubMed

Lahnakoski, Juha M; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

2012-01-01

Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

Social networks and environmental outcomes.

PubMed

Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

2016-06-07

Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

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.

A Survey of Models and Algorithms for Social Influence Analysis

NASA Astrophysics Data System (ADS)

Sun, Jimeng; Tang, Jie

Social influence is the behavioral change of a person because of the perceived relationship with other people, organizations and society in general. Social influence has been a widely accepted phenomenon in social networks for decades. Many applications have been built based around the implicit notation of social influence between people, such as marketing, advertisement and recommendations. With the exponential growth of online social network services such as Facebook and Twitter, social influence can for the first time be measured over a large population. In this chapter, we survey the research on social influence analysis with a focus on the computational aspects. First, we present statistical measurements related to social influence. Second, we describe the literature on social similarity and influences. Third, we present the research on social influence maximization which has many practical applications including marketing and advertisement.

Social networks and future direction for obesity research: A scoping review

PubMed Central

Nam, Soohyun; Redeker, Nancy; Whittemore, Robin

2014-01-01

Despite significant efforts to decrease obesity rates, the prevalence of obesity continues to increase in the United States. Obesity-risk behaviors—physical inactivity, unhealthy eating, and sleep deprivation—are intertwined during daily life and are difficult to improve in the current social environment. Studies show that social networks—the thick webs of social relations and interactions—influence various health outcomes, such as HIV risk behaviors, alcohol consumption, smoking, depression, and cardiovascular mortality; however, there is limited information on the influences of social networks on obesity and obesity-risk behaviors. Given the complexities of the bio-behavioral pathology of obesity, and the lack of clear evidence of effectiveness and sustainability of existing interventions that are usually focused on an individual approach, targeting change in an individual’s health behaviors or attitude may not take socio-contextual factors into account; there is a pressing need for a new perspective on this problem. In this review we evaluate the literature on social networks as a potential approach for obesity prevention and treatment: how social networks affect various health outcomes and present two major social network data analyses (i.e. egocentric and sociometric analysis); and discuss implications and future direction for obesity research using social networks. PMID:25982770

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.

Moving from theory to practice: A participatory social network mapping approach to address unmet need for family planning in Benin.

PubMed

Igras, Susan; Diakité, Mariam; Lundgren, Rebecka

2017-07-01

In West Africa, social factors influence whether couples with unmet need for family planning act on birth-spacing desires. Tékponon Jikuagou is testing a social network-based intervention to reduce social barriers by diffusing new ideas. Individuals and groups judged socially influential by their communities provide entrée to networks. A participatory social network mapping methodology was designed to identify these diffusion actors. Analysis of monitoring data, in-depth interviews, and evaluation reports assessed the methodology's acceptability to communities and staff and whether it produced valid, reliable data to identify influential individuals and groups who diffuse new ideas through their networks. Results indicated the methodology's acceptability. Communities were actively and equitably engaged. Staff appreciated its ability to yield timely, actionable information. The mapping methodology also provided valid and reliable information by enabling communities to identify highly connected and influential network actors. Consistent with social network theory, this methodology resulted in the selection of informal groups and individuals in both informal and formal positions. In-depth interview data suggest these actors were diffusing new ideas, further confirming their influence/connectivity. The participatory methodology generated insider knowledge of who has social influence, challenging commonly held assumptions. Collecting and displaying information fostered staff and community learning, laying groundwork for social change.

Social networks and future direction for obesity research: A scoping review.

PubMed

Nam, Soohyun; Redeker, Nancy; Whittemore, Robin

2015-01-01

Despite significant efforts to decrease obesity rates, the prevalence of obesity continues to increase in the United States. Obesity risk behaviors including physical inactivity, unhealthy eating, and sleep deprivation are intertwined during daily life and are difficult to improve in the current social environment. Studies show that social networks-the thick webs of social relations and interactions-influence various health outcomes, such as HIV risk behaviors, alcohol consumption, smoking, depression, and cardiovascular mortality; however, there is limited information on the influences of social networks on obesity and obesity risk behaviors. Given the complexities of the biobehavioral pathology of obesity and the lack of clear evidence of effectiveness and sustainability of existing interventions that are usually focused on an individual approach, targeting change in an individual's health behaviors or attitude may not take sociocontextual factors into account; there is a pressing need for a new perspective on this problem. In this review, we evaluate the literature on social networks as a potential approach for obesity prevention and treatment (i.e., how social networks affect various health outcomes), present two major social network data analyses (i.e., egocentric and sociometric analysis), and discuss implications and the future direction for obesity research using social networks. Copyright © 2015 Elsevier Inc. All rights reserved.

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

A systematic review and meta-analysis of trials of social network interventions in type 2 diabetes.

PubMed

Spencer-Bonilla, Gabriela; Ponce, Oscar J; Rodriguez-Gutierrez, Rene; Alvarez-Villalobos, Neri; Erwin, Patricia J; Larrea-Mantilla, Laura; Rogers, Anne; Montori, Victor M

2017-08-21

In the care of patients with type 2 diabetes, self-management is emphasised and studied while theory and observations suggest that patients also benefit from social support. We sought to assess the effect of social network interventions on social support, glycaemic control and quality of life in patients with type 2 diabetes. We searched Ovid MEDLINE, Ovid EBM Reviews, Cochrane Central Register of Controlled Trials, EMBASE, PsycINFO and CINAHL through April 2017 for randomised clinical trials (RCTs) of social network interventions in patients with type 2 diabetes. Reviewers working independently and in duplicate assessed eligibility and risk of bias, and extracted data from eligible RCTs. We pooled estimates using inverse variance random effects meta-analysis. We found 19 eligible RCTs enrolling 2319 participants. Social network interventions were commonly based on individual behaviour change rather than social or interpersonal theories of self-management, were educational, and sought to engage social network members for their knowledge and experience. Interventions improved social support (0.74 SD (95% CI 0.32 to 1.15), I 2 =89%, 8 RCTs) and haemoglobin A1c at 3 months (-0.25 percentage points (95% CI -0.40 to -0.11), I 2 =12%, 9 RCTs), but not quality of life. Despite a compelling theoretical base, researchers have only minimally studied the value of interventions targeting patients' social networks on diabetes care. Although the body of evidence to date is limited, and based on individual behaviour change theories, the results are promising. This review challenges the scientific community to design and test theory-based interventions that go beyond self-management approaches to focus on the largely untapped potential of social networks to improve diabetes care. CRD42016036117. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The Reciprocal Relationship Between Social Connectedness and Mental Health Among Older European Adults: A SHARE-Based Analysis.

PubMed

Schwartz, Ella; Litwin, Howard

2017-11-04

The current study aimed to understand the reciprocal relationship between social networks and mental health in old age. It explored the dynamic aspects of that relationship and assessed the influence of social networks on mental health, as well as a concurrent influence of mental health on change in social connectedness. The data came from two measurement points in the Survey of Health, Aging and Retirement in Europe (SHARE). The analytic sample was composed of adults aged 65 years and above (N = 14,706). Analyses were conducted via latent change score models. Analyses showed a reciprocal association between social networks and mental health; baseline social connectedness led to mental health improvements and a better initial mental state led to richer social networks. The results further indicated that the relative effect of mental health on change in social network connectedness was greater than the corresponding effect of social network connectedness on change in mental health. No gender differences were found regarding the reciprocal associations. The results of this study demonstrate the dynamic inter-relationship of social networks and mental health. It highlights the need to take into account both directions of influence when studying the impact of social relationships on mental health. © 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.

Mother's Social Network and Family Language Maintenance

ERIC Educational Resources Information Center

Velazquez, Isabel

2013-01-01

This article reports the results of a social network analysis (SNA) performed on the mother's primary network of interaction in 15 Mexican American families in the city of El Paso, Texas, the neighbourhood of La Villita, in Chicago, and the city of Lincoln, Nebraska. The goal of this study was to examine potential opportunities for Spanish use by…

Composite Social Network for Predicting Mobile Apps Installation

DTIC Science & Technology

2011-06-02

analysis used by social scientists such as matched sample estimation (Aral, Muchnik, and Sundararajan 2009) are only for identifying network effects and...ar X iv :1 10 6. 03 59 v1 [ cs .S I] 2 J un 2 01 1 Composite Social Network for Predicting Mobile Apps Installation Wei Pan and Nadav Aharony...and Alex (Sandy) Pentland MIT Media Laboratory 20 Ames Street Cambridge, Massachusetts 02139 Abstract We have carefully instrumented a large portion of

Using big data to map the network organization of the brain.

PubMed

Swain, James E; Sripada, Chandra; Swain, John D

2014-02-01

The past few years have shown a major rise in network analysis of "big data" sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles. We speculate that the dependency dimension - individuality versus sociality - might offer important insights into the dynamics of neurons and neuronal ensembles. Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization.

Using big data to map the network organization of the brain

PubMed Central

Swain, James E.; Sripada, Chandra; Swain, John D.

2015-01-01

The past few years have shown a major rise in network analysis of “big data” sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles. We speculate that the dependency dimension – individuality versus sociality – might offer important insights into the dynamics of neurons and neuronal ensembles. Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization. PMID:24572243

MSEE: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing

DTIC Science & Technology

2013-09-01

recognition, a Gaussian Process Dynamic Model with Social Network Analysis (GPDM-SNA) for a small human group action recognition, an extended GPDM-SNA...44  3.2. Small Human Group Activity Modeling Based on Gaussian Process Dynamic Model and Social Network Analysis (SN-GPDM...51  Approved for public release; distribution unlimited. 3 3.2.3. Gaussian Process Dynamical Model and

Why Should They Stay? A Social Network Analysis of Teacher Retention

ERIC Educational Resources Information Center

Hodgson, Kevin W.

2013-01-01

Decades of research have established that there is a significant issue retaining teachers in America's schools. In fact, upwards of 50% of all teachers do not last more than five years (Ingersoll, 2001). Despite a tremendous amount of research, very little in the form of social network analysis has been utilized to study the problem. This…

Analysis of Social Network Collaboration Using Selected APAN Communications from the Haiti Earthquake of 2010

DTIC Science & Technology

2012-06-01

POSTS .....................................................39 C . CONTENT ANALYSIS OF THE SINGLE POSTS ...................................41 1. Sitreps...Andrew, for their patience, understanding and love while I completed this project and other studies at the Naval Postgraduate School. I love you... the various relief efforts taking place, SOUTHCOM leveraged social media, in particular, the All Partners Access Network. 3 C . ALL PARTNERS

Social Network Analysis as an Analytic Tool for Task Group Research: A Case Study of an Interdisciplinary Community of Practice

ERIC Educational Resources Information Center

Lockhart, Naorah C.

2017-01-01

Group counselors commonly collaborate in interdisciplinary settings in health care, substance abuse, and juvenile justice. Social network analysis is a methodology rarely used in counseling research yet has potential to examine task group dynamics in new ways. This case study explores the scholarly relationships among 36 members of an…

Using Social Network Analysis to Examine How Perceived Beliefs Affect Service Quality in Public Higher Education Institutions

ERIC Educational Resources Information Center

Robinson-Neal, Andree

2009-01-01

In business, educational, and other organizations, team members often connect with one another in informal groups in order to fill certain needs (Accel-Team, 2006). Such needs include the ability to connect with others who share worldviews, opinions, or beliefs. When social network analysis (SNA) or concept mapping is used to examine interpersonal…

Investigation of the Impact of Extracting and Exchanging Health Information by Using Internet and Social Networks.

PubMed

Pistolis, John; Zimeras, Stelios; Chardalias, Kostas; Roupa, Zoe; Fildisis, George; Diomidous, Marianna

2016-06-01

Social networks (1) have been embedded in our daily life for a long time. They constitute a powerful tool used nowadays for both searching and exchanging information on different issues by using Internet searching engines (Google, Bing, etc.) and Social Networks (Facebook, Twitter etc.). In this paper, are presented the results of a research based on the frequency and the type of the usage of the Internet and the Social Networks by the general public and the health professionals. The objectives of the research were focused on the investigation of the frequency of seeking and meticulously searching for health information in the social media by both individuals and health practitioners. The exchanging of information is a procedure that involves the issues of reliability and quality of information. In this research, by using advanced statistical techniques an effort is made to investigate the participant's profile in using social networks for searching and exchanging information on health issues. Based on the answers 93 % of the people, use the Internet to find information on health-subjects. Considering principal component analysis, the most important health subjects were nutrition (0.719 %), respiratory issues (0.79 %), cardiological issues (0.777%), psychological issues (0.667%) and total (73.8%). The research results, based on different statistical techniques revealed that the 61.2% of the males and 56.4% of the females intended to use the social networks for searching medical information. Based on the principal components analysis, the most important sources that the participants mentioned, were the use of the Internet and social networks for exchanging information on health issues. These sources proved to be of paramount importance to the participants of the study. The same holds for nursing, medical and administrative staff in hospitals.

A Net of Friends: Investigating Friendship by Integrating Attachment Theory and Social Network Analysis.

PubMed

Gillath, Omri; Karantzas, Gery C; Selcuk, Emre

2017-11-01

The current article focuses on attachment style-an individual difference widely studied in the field of close relationships-and its application to the study of social networks. Specifically, we investigated whether attachment style predicts perception and management of social networks. In Study 1, we examined the associations of attachment style with perceptions of network tie strength and multiplexity. In Studies 2a and 2b, we investigated the association between attachment style and network management skills (initiating, maintaining, and dissolving ties) and whether network management skills mediated the associations of attachment style with network tie strength and multiplexity. In Study 3, experimentally enhancing attachment security made people more likely to initiate and less likely to dissolve social ties (for the latter, especially among those high on avoidance or anxiety). As for maintenance, security priming also increased maintenance; however, mainly among people high on attachment anxiety or low on attachment avoidance.

Nursing work stress: the impacts of social network structure and organizational citizenship behavior.

PubMed

Tsang, Seng-Su; Chen, Tzu-Yin; Wang, Shih-Fong; Tai, Hsin-Ling

2012-03-01

The nursing workplace imposes significantly more stress on its employees than other workplace settings. Organizational resources, both physical and psychological, have been recognized in prior studies as important alleviators of nursing workplace stress. Whereas physical resources are less difficult to manipulate because of their tangibility, psychological resources, particularly psychological support from colleagues, are typically not deployed to greatest effect. This article investigated the alleviation of nursing work stress using resources already extant in coworker social networks. Researchers conducted a survey in a dialysis department at a medical center located in Taipei City, Taiwan. This survey measured nurse work stress, satisfaction, organizational citizenship behavior (OCB) and social network structures. Researchers employed UCINET to analyze the network structure data, which were in dyadic matrix format to estimate nurse network centralities and used partial least squares analysis to estimate research construct path coefficients and test extrapolated hypotheses. The level of OCB induced by nurse social ties was satisfactory and did not only directly increased work satisfaction but also alleviated work stress, which indirectly boosted work satisfaction. Findings suggest that managers may be able to use social network analysis to identify persons appropriate to conduct the distribution of organizational resources. Choosing those with multiple social connections can help distribute resources effectively and induce higher OCB levels within the organization. In addition, staff with strong friendship network connections may provide appropriate psychological resources (support) to coworkers. If those with high friendship network centrality receive proper counseling training, they should be in a good position to provide assistance when needed.

Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks

PubMed Central

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

2016-01-01

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

Estimation of Anonymous Email Network Characteristics through Statistical Disclosure Attacks.

PubMed

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

2016-11-01

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

Bidirectional selection between two classes in complex social networks.

PubMed

Zhou, Bin; He, Zhe; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

2014-12-19

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

Community Structure in Online Collegiate Social Networks

NASA Astrophysics Data System (ADS)

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

2009-03-01

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

A Social Network Analysis of the Financial Links Backing Health and Fitness Apps.

PubMed

Grundy, Quinn; Held, Fabian; Bero, Lisa

2017-11-01

To identify the major stakeholders in mobile health app development and to describe their financial relationships using social network analysis. We conducted a structured content analysis of a purposive sample of prominent health and fitness apps available in November 2015 in the United States, Canada, and Australia. We conducted a social network analysis of apps' developers, investors, other funding sources, and content advisors to describe the financial relationships underpinning health app development. Prominent health and fitness apps are largely developed by private companies based in North America, with an average of 4.7 (SD = 5.5) financial relations, including founders, external investors, acquiring companies, and commercial partnerships. Network analysis revealed a core of 41 sampled apps connected to 415 other entities by 466 financial relations. This core largely comprised apps published by major technology, pharmaceutical, and fashion corporations. About one third of apps named advisors, many of whom had commercial affiliations. Public health needs to extend its scrutiny and advocacy beyond the health messages contained within apps to understanding commercial influences on health and, when necessary, challenging them.

Persistent ISR: the social network analysis connection

NASA Astrophysics Data System (ADS)

Bowman, Elizabeth K.

2012-06-01

Persistent surveillance provides decision makers with unprecedented access to multisource data collected from humans and sensor assets around the globe, yet these data exist in the physical world and provide few overt clues to meaning behind actions. In this paper we explore the recent growth in online social networking and ask the questions: 1) can these sites provide value-added information to compliment physical sensing and 2) what are the mechanisms by which these data could inform situational awareness and decision making? In seeking these answers we consider the range of options provided by Social Network Analysis (SNA), and focus especially on the dynamic nature of these networks. In our discussion we focus on the wave of reform experienced by the North African nations in early 2011 known as the Arab Spring. Demonstrators made widespread use of social networking applications to coordinate, document, and publish material to aid their cause. Unlike members of covert social networks who hide their activity and associations, these demonstrators openly posted multimedia information to coordinate activity and stimulate global support. In this paper we provide a review of SNA approaches and consider how one might track network adaptations by capturing temporal and conceptual trends. We identify opportunities and challenges for merging SNA with physical sensor output, and conclude by addressing future challenges in the persistent ISR domain with respect to SNA.

Systematic review of social network analysis in adolescent cigarette smoking behavior.

PubMed

Seo, Dong-Chul; Huang, Yan

2012-01-01

Social networks are important in adolescent smoking behavior. Previous research indicates that peer context is a major causal factor of adolescent smoking behavior. To date, however, little is known about the influence of peer group structure on adolescent smoking behavior. Studies that examined adolescent social networks with regard to their cigarette smoking behavior were identified through online and manual literature searches. Ten social network analysis studies involving a total of 28,263 adolescents were included in the final review. Of the 10 reviewed studies, 6 identify clique members, liaisons, and isolates as contributing factors to adolescent cigarette smoking. Significantly higher rates of smoking are noted among isolates than clique members or liaisons in terms of peer network structure. Eight of the reviewed studies indicate that peer selection or influence precedes adolescents' smoking behavior and intent to smoke. Such peer selection or influence accounts for a large portion of similarities among smoking adolescents. Adolescents who are identified as isolates are more likely to smoke and engage in risk-taking behaviors than others in the peer network structure. Given that the vast majority of current adult smokers started their smoking habits during adolescence, adolescent smoking prevention efforts will likely benefit from incorporating social network analytic approaches and focusing the efforts on isolates and other vulnerable adolescents from a peer selection and influence perspective. © 2011, American School Health Association.

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

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

PubMed

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

2016-09-28

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

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

PubMed Central

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

2016-01-01

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

Leveraging social networking sites for disease surveillance and public sensing: the case of the 2013 avian influenza A(H7N9) outbreak in China.

PubMed

Zhang, Emma Xuxiao; Yang, Yinping; Di Shang, Richard; Simons, Joseph John Pyne; Quek, Boon Kiat; Yin, Xiao Feng; See, Wanhan; Oh, Olivia Seen Huey; Nandar, Khine Sein Tun; Ling, Vivienne Ruo Yun; Chan, Pei Pei; Wang, Zhaoxia; Goh, Rick Siow Mong; James, Lyn; Tey, Jeannie Su Hui

2015-01-01

We conducted in-depth analysis on the use of a popular Chinese social networking and microblogging site, Sina Weibo, to monitor an avian influenza A(H7N9) outbreak in China and to assess the value of social networking sites in the surveillance of disease outbreaks that occur overseas. Two data sets were employed for our analysis: a line listing of confirmed cases obtained from conventional public health information channels and case information from Weibo posts. Our findings showed that the level of activity on Weibo corresponded with the number of new cases reported. In addition, the reporting of new cases on Weibo was significantly faster than those of conventional reporting sites and non-local news media. A qualitative review of the functions of Weibo also revealed that Weibo enabled timely monitoring of other outbreak-relevant information, provided access to additional crowd-sourced epidemiological information and was leveraged by the local government as an interactive platform for risk communication and monitoring public sentiment on the policy response. Our analysis demonstrated the potential for social networking sites to be used by public health agencies to enhance traditional communicable disease surveillance systems for the global surveillance of overseas public health threats. Social networking sites also can be used by governments for calibration of response policies and measures and for risk communication.

Leveraging social networking sites for disease surveillance and public sensing: the case of the 2013 avian influenza A(H7N9) outbreak in China

PubMed Central

Zhang, Emma Xuxiao; Yang, Yinping; Di Shang, Richard; Simons, Joseph John Pyne; Quek, Boon Kiat; Yin, Xiao Feng; See, Wanhan; Oh, Olivia Seen Huey; Nandar, Khine Sein Tun; Ling, Vivienne Ruo Yun; Chan, Pei Pei; Wang, Zhaoxia; Goh, Rick Siow Mong; James, Lyn

2015-01-01

We conducted in-depth analysis on the use of a popular Chinese social networking and microblogging site, Sina Weibo, to monitor an avian influenza A(H7N9) outbreak in China and to assess the value of social networking sites in the surveillance of disease outbreaks that occur overseas. Two data sets were employed for our analysis: a line listing of confirmed cases obtained from conventional public health information channels and case information from Weibo posts. Our findings showed that the level of activity on Weibo corresponded with the number of new cases reported. In addition, the reporting of new cases on Weibo was significantly faster than those of conventional reporting sites and non-local news media. A qualitative review of the functions of Weibo also revealed that Weibo enabled timely monitoring of other outbreak-relevant information, provided access to additional crowd-sourced epidemiological information and was leveraged by the local government as an interactive platform for risk communication and monitoring public sentiment on the policy response. Our analysis demonstrated the potential for social networking sites to be used by public health agencies to enhance traditional communicable disease surveillance systems for the global surveillance of overseas public health threats. Social networking sites also can be used by governments for calibration of response policies and measures and for risk communication. PMID:26306219

Increasing social capital via local networks: analysis in the context of a surgical practice.

PubMed

Thakur, Anjani; Yang, Isaac; Lee, Michael Y; Goel, Arpan; Ashok, Ashwin; Fonkalsrud, Eric W

2002-09-01

The relationship between social capital (support, trust, patient awareness, and increased practice revenue) and local networks (university hospital) in communities has received little attention. The development of computer-based communication networks (social networks) has added a new dimension to the argument, posing the question of whether local networks can (re-)create social capital in local communities. This relationship is examined through a review of the literature on local networks and social capital and a surgeon's practice management from 1990 to 2001 with respect to repair of pectus chest deformities. With respect to pectus repair there was a consistent but small number of new referrals (15-20 new patients/year), lack of patient awareness (eight to 12 self-referred patients/year), and modest practice revenue. Since the inception of an Internet website (social network) dedicated to pectus repair in 1996 there has been increased social participation (n = 630 hits/year to the website); facilitation of spread of information through E-mail messages (n = 430 messages/year); and a greater participation of groups such as women, minorities, adults, and those with disability (n = 120 patients/year). The dissemination of information via the local network has also allowed an "outward movement" with increased participation by interconnecting communities (n = 698,300 global Internet participants based on statistical ratios). We conclude that local networks have enhanced social networks providing new grounds for the development of relationships based on choice and shared interest.

Meta-analytically informed network analysis of resting state FMRI reveals hyperconnectivity in an introspective socio-affective network in depression.

PubMed

Schilbach, Leonhard; Müller, Veronika I; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto; Gruber, Oliver; Eickhoff, Simon B

2014-01-01

Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

PubMed Central

Schilbach, Leonhard; Müller, Veronika I.; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto

2014-01-01

Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology. PMID:24759619

Social networks predict selective observation and information spread in ravens

PubMed Central

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

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

PubMed

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

2018-02-20

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

Association of tuberculosis with multimorbidity and social networks

PubMed Central

Valenzuela-Jiménez, Hiram; Manrique-Hernández, Edgar Fabian; Idrovo, Alvaro Javier

2017-01-01

ABSTRACT The combination of tuberculosis with other diseases can affect tuberculosis treatment within populations. In the present study, social network analysis of data retrieved from the Mexican National Epidemiological Surveillance System was used in order to explore associations between the number of contacts and multimorbidity. The node degree was calculated for each individual with tuberculosis and included information from 242 contacts without tuberculosis. Multimorbidity was identified in 49.89% of individuals. The node degrees were highest for individuals with tuberculosis + HIV infection (p < 0.04) and lowest for those with tuberculosis + pulmonary edema (p < 0.07). Social network analysis should be used as a standard method for monitoring tuberculosis and tuberculosis-related syndemics. PMID:28125153

Coupling effect of nodes popularity and similarity on social network persistence

PubMed Central

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-01-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology. PMID:28220840

Coupling effect of nodes popularity and similarity on social network persistence

NASA Astrophysics Data System (ADS)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Coupling effect of nodes popularity and similarity on social network persistence.

PubMed

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men

PubMed Central

Mulawa, Marta; Yamanis, Thespina J.; Hill, Lauren; Balvanz, Peter; Kajula, Lusajo J.; Maman, Suzanne

2016-01-01

Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men’s social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men’s peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n= 1,249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men’s HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men’s social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men’s normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men’s social networks in Sub-Saharan Africa and map out several areas of future inquiry. PMID:26874081

Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men.

PubMed

Mulawa, Marta; Yamanis, Thespina J; Hill, Lauren M; Balvanz, Peter; Kajula, Lusajo J; Maman, Suzanne

2016-03-01

Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men's social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men's peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n = 1249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men's HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men's social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men's normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men's social networks in Sub-Saharan Africa and map out several areas of future inquiry. Copyright © 2016 Elsevier Ltd. All rights reserved.

Connections Among Communities: Preventing Radicalization and Violent Extremism Through Social Network Analysis in the Threat and Hazard Identification and Risk Assessment (THIRA) Framework

DTIC Science & Technology

2016-12-01

From Profiles to Pathways and Roots to Routes: Perspectives from Psychology on Radicalization into Terrorism, “Annals of the American Academy of... American Psychological Association 2, no. 2 (2015): 63–87, doi: http://dx.doi. org/10.1037/tam0000043; Martin Bouchard, Social Networks, Terrorism...The Sociology of Secrecy and of Secret Societies ,” American Journal of Sociology 11 (1906): 441–498. 28 With the exploration of social network theory

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

PubMed Central

2017-01-01

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

Social Support Systems and Social Network Characteristics of Older Adults with HIV.

PubMed

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

Social networks of older adults with HIV have been characterized as fragile, with a greater reliance on friends as compared to family. However, we know little about the subgroup differences in the social network constellations of this population, how such characteristics are related to social support resources, and their relationship with psychosocial well-being. We developed a typology of social networks of older HIV-positive adults and examined if they would be related to receipt of informal assistance, perceptions of support sufficiency, and psychosocial well-being. Data were obtained from Research on Older Adults with HIV (n = 914). Participants were 50 years and older, HIV positive, and diverse in terms of race/ethnicity, gender, and sexual orientation. Cluster analysis identified Isolated, Friend-centered, and Integrated social network types. The Isolated reported significantly lower levels of assistance, lower perceptions of support availability and adequacy, greater stigma and psychological distress, and lower well-being compared to their peers. While friends dominate many social networks in this population, a more nuanced interpretation is needed; many have no friends and a substantial proportion receive significant family support. Those with Isolated network types will likely need to access a high volume of community-based services as they age as they lack informal support resources. © 2017 S. Karger AG, Basel.

Associations of a social network typology with physical and mental health risks among older adults in South Korea.

PubMed

Park, N S; Jang, Y; Lee, B S; Chiriboga, D A; Chang, S; Kim, S Y

2018-05-01

The objectives of this study were to (1) develop an empirical typology of social networks in older Koreans; and (2) examine its effect on physical and mental health. A sample of 6900 community-dwelling older adults in South Korea was drawn from the 2014 Korean National Elderly Survey. Latent profile analysis (LPA) was conducted to derive social network types using eight common social network characteristics (marital status, living arrangement, the number and frequency of contact with close family/relatives, the number and frequency of contact with close friends, frequency of participation in social activities, and frequency of having visitors at home). The identified typologies were then regressed on self-rated health and depressive symptoms to explore the health risks posed by the group membership. The LPA identified a model with five types of social network as being most optimal (BIC = 153,848.34, entropy = .90). The groups were named diverse/family (enriched networks with more engagement with family), diverse/friend (enriched networks with more engagement with friends), friend-focused (high engagement with friends), distant (structurally disengaged), and restricted (structurally engaged but disengaged in family/friends networks). A series of regression analyses showed that membership in the restricted type was associated with more health and mental health risks than all types of social networks except the distant type. Findings demonstrate the importance of family and friends as a source of social network and call attention to not only structural but also non-structural aspects of social isolation. Findings and implications are discussed in cultural contexts.

Social grooming network in captive chimpanzees: does the wild or captive origin of group members affect sociality?

PubMed

Levé, Marine; Sueur, Cédric; Petit, Odile; Matsuzawa, Tetsuro; Hirata, Satoshi

2016-01-01

Many chimpanzees throughout the world are housed in captivity, and there is an increasing effort to recreate social groups by mixing individuals with captive origins with those with wild origins. Captive origins may entail restricted rearing conditions during early infant life, including, for example, no maternal rearing and a limited social life. Early rearing conditions have been linked with differences in tool-use behavior between captive- and wild-born chimpanzees. If physical cognition can be impaired by non-natural rearing, what might be the consequences for social capacities? This study describes the results of network analysis based on grooming interactions in chimpanzees with wild and captive origins living in the Kumamoto Sanctuary in Kumamoto, Japan. Grooming is a complex social activity occupying up to 25% of chimpanzees' waking hours and plays a role in the emergence and maintenance of social relationships. We assessed whether the social centralities and roles of chimpanzees might be affected by their origin (captive vs wild). We found that captive- and wild-origin chimpanzees did not differ in their grooming behavior, but that theoretical removal of individuals from the network had differing impacts depending on the origin of the individual. Contrary to findings that non-natural early rearing has long-term effects on physical cognition, living in social groups seems to compensate for the negative effects of non-natural early rearing. Social network analysis (SNA) and, in particular, theoretical removal analysis, were able to highlight differences between individuals that would have been impossible to show using classical methods. The social environment of captive animals is important to their well-being, and we are only beginning to understand how SNA might help to enhance animal welfare.

Community intervention to increase neighborhood social network among Japanese older adults.

PubMed

Harada, Kazuhiro; Masumoto, Kouhei; Katagiri, Keiko; Fukuzawa, Ai; Chogahara, Makoto; Kondo, Narihiko; Okada, Shuichi

2018-03-01

Strengthening neighborhood social networks is important for promoting health among older adults. However, effective intervention strategies aimed at increasing older adults' social networks have not yet been established. The present study examined whether a university-led community intervention that provided communication opportunities could increase older Japanese adults' neighborhood social networks. The present study used a quasi-experimental design. Before the intervention, using postal mail, we carried out a baseline questionnaire survey that was sent to all people living in the Tsurukabuto community aged ≥60 years (n = 1769), of whom 1068 responded. For the community intervention, 18 event-based programs were provided over the course of 1 year at Kobe University. Academic staff at Kobe University organized all the programs. During the program, social interactions among participants were promoted. A follow-up survey was distributed to those who responded to the baseline survey, and 710 individuals answered the question about their participation in the intervention programs (138 respondents were participants, 572 were non-participants). The neighborhood social network was measured in both the baseline and follow-up surveys. Analysis of covariance showed that the changes in neighborhood social network among participants in the program was significantly higher than the changes among non-participants (P = 0.046) after adjusting for the baseline score of social network. The present study found that participants of the intervention expanded their neighborhood social network, but non-participants did not. This finding shows that community interventions using university resources could increase older adults' neighborhood social networks. Geriatr Gerontol Int 2018; 18: 462-469. © 2017 Japan Geriatrics Society.

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.

Peer Relations and Access to Capital in the Mathematics Classroom: A Bourdieusian Social Network Analysis

ERIC Educational Resources Information Center

Choudry, Sophina; Williams, Julian; Black, Laura

2017-01-01

The aim of this article is to explore the structure of social capital in peer networks and its relation to the unequal access of educational resources within mathematics classrooms. We hypothesise that learners can gain access to mathematics through friendship networks which provide more or less help from peers that might sustain (or curtail)…

The Evolution of Recent Research on Catalan Literature through the Production of PhD Theses: A Bibliometric and Social Network Analysis

ERIC Educational Resources Information Center

Ardanuy, Jordi; Urbano, Cristobal; Quintana, Lluis

2009-01-01

Introduction: This paper studies the situation of research on Catalan literature between 1976 and 2003 by carrying out a bibliometric and social network analysis of PhD theses defended in Spain. It has a dual aim: to present interesting results for the discipline and to demonstrate the methodological efficacy of scientometric tools in the…

The Complexity of Crime Network Data: A Case Study of Its Consequences for Crime Control and the Study of Networks

PubMed Central

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks. PMID:25775130

The complexity of crime network data: a case study of its consequences for crime control and the study of networks.

PubMed

Rostami, Amir; Mondani, Hernan

2015-01-01

The field of social network analysis has received increasing attention during the past decades and has been used to tackle a variety of research questions, from prevention of sexually transmitted diseases to humanitarian relief operations. In particular, social network analyses are becoming an important component in studies of criminal networks and in criminal intelligence analysis. At the same time, intelligence analyses and assessments have become a vital component of modern approaches in policing, with policy implications for crime prevention, especially in the fight against organized crime. In this study, we have a unique opportunity to examine one specific Swedish street gang with three different datasets. These datasets are the most common information sources in studies of criminal networks: intelligence, surveillance and co-offending data. We use the data sources to build networks, and compare them by computing distance, centrality, and clustering measures. This study shows the complexity factor by which different data sources about the same object of study have a fundamental impact on the results. The same individuals have different importance ranking depending on the dataset and measure. Consequently, the data source plays a vital role in grasping the complexity of the phenomenon under study. Researchers, policy makers, and practitioners should therefore pay greater attention to the biases affecting the sources of the analysis, and be cautious when drawing conclusions based on intelligence assessments and limited network data. This study contributes to strengthening social network analysis as a reliable tool for understanding and analyzing criminality and criminal networks.

The Current State of Human Performance Technology: A Citation Network Analysis of "Performance Improvement Quarterly," 1988-2010

ERIC Educational Resources Information Center

Cho, Yonjoo; Jo, Sung Jun; Park, Sunyoung; Kang, Ingu; Chen, Zengguan

2011-01-01

This study conducted a citation network analysis (CNA) of human performance technology (HPT) to examine its current state of the field. Previous reviews of the field have used traditional research methods, such as content analysis, survey, Delphi, and citation analysis. The distinctive features of CNA come from using a social network analysis…

Predicting Positive and Negative Relationships in Large Social Networks.

PubMed

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

2015-01-01

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

Social network supported process recommender system.

PubMed

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

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.

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

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.

Social network analysis in identifying influential webloggers: A preliminary study

NASA Astrophysics Data System (ADS)

Hasmuni, Noraini; Sulaiman, Nor Intan Saniah; Zaibidi, Nerda Zura

2014-12-01

In recent years, second generation of internet-based services such as weblog has become an effective communication tool to publish information on the Web. Weblogs have unique characteristics that deserve users' attention. Some of webloggers have seen weblogs as appropriate medium to initiate and expand business. These webloggers or also known as direct profit-oriented webloggers (DPOWs) communicate and share knowledge with each other through social interaction. However, survivability is the main issue among DPOW. Frequent communication with influential webloggers is one of the way to keep survive as DPOW. This paper aims to understand the network structure and identify influential webloggers within the network. Proper understanding of the network structure can assist us in knowing how the information is exchanged among members and enhance survivability among DPOW. 30 DPOW were involved in this study. Degree centrality and betweenness centrality measurement in Social Network Analysis (SNA) were used to examine the strength relation and identify influential webloggers within the network. Thus, webloggers with the highest value of these measurements are considered as the most influential webloggers in the network.

Differential Impact of Types of Social Support in the Mental Health of Formerly Incarcerated Latino Men

PubMed Central

Muñoz-Laboy, Miguel; Severson, Nicolette; Perry, Ashley; Guilamo-Ramos, Vincent

2015-01-01

The role of social support in the mental health of formerly incarcerated Latino men (FILM) is an issue overlooked in public health prevention efforts. The objectives of this analysis were to (a) describe the levels of social support perceived and received by FILM; (b) identify the associations, if any, between levels of social support and mental health indicators such as depression and anxiety; and (c) explore the impact of familism and hypermasculinity on the receptivity of social support and the potential role of these factors in mediating associations between social support and mental health indicators. To accomplish the objectives, we conducted a cross-sectional survey with FILM (n = 259), ages 18 to 59, in New York City, and one nominated member of their social network (n = 130 dyads). In this analysis, we examined four dimensions of social support (instrumental, informational, appraisal, and emotional) from two perspectives: provided (as reported by members of the social networks) and perceived (as reported by FILM). The major outcome variables for this analysis were the presence/absence of major anxiety and depressive symptoms. Our logistic regression analyses suggest that perceived emotional support was inversely associated with both anxiety and depression. Our findings suggest that familism mediated the association between perceived emotional support and anxiety/depression. Therefore, we must consider designing network enhancement interventions that focus on both FILM and their social support systems. PMID:24323767

Agricultural Innovation Systems and Farm Technology Adoption: Findings from a Study of the Ghanaian Plantain Sector

ERIC Educational Resources Information Center

Weyori, Alirah Emmanuel; Amare, Mulubrhan; Garming, Hildegard; Waibel, Hermann

2018-01-01

Purpose: We assess farm technology adoption in an integrated analysis of social networks and innovation in plantain production in Ghana. The paper explores the strength of social networks in the agricultural innovation systems (AISs) and the effect of AISs on adoption of improved farm technology. Methodology/Approach: The paper uses social network…

Social Network Analysis of Children with Autism Spectrum Disorder: Predictors of Fragmentation and Connectivity in Elementary School Classrooms

ERIC Educational Resources Information Center

Anderson, Ariana; Locke, Jill; Kretzmann, Mark; Kasari, Connie

2016-01-01

Although children with autism spectrum disorder are frequently included in mainstream classrooms, it is not known how their social networks change compared to typically developing children and whether the factors predictive of this change may be unique. This study identified and compared predictors of social connectivity of children with and…

A natural experiment of social network formation and dynamics.

PubMed

Phan, Tuan Q; Airoldi, Edoardo M

2015-05-26

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities.

A natural experiment of social network formation and dynamics

PubMed Central

Phan, Tuan Q.; Airoldi, Edoardo M.

2015-01-01

Social networks affect many aspects of life, including the spread of diseases, the diffusion of information, the workers' productivity, and consumers' behavior. Little is known, however, about how these networks form and change. Estimating causal effects and mechanisms that drive social network formation and dynamics is challenging because of the complexity of engineering social relations in a controlled environment, endogeneity between network structure and individual characteristics, and the lack of time-resolved data about individuals' behavior. We leverage data from a sample of 1.5 million college students on Facebook, who wrote more than 630 million messages and 590 million posts over 4 years, to design a long-term natural experiment of friendship formation and social dynamics in the aftermath of a natural disaster. The analysis shows that affected individuals are more likely to strengthen interactions, while maintaining the same number of friends as unaffected individuals. Our findings suggest that the formation of social relationships may serve as a coping mechanism to deal with high-stress situations and build resilience in communities. PMID:25964337

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

PubMed

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

2017-04-13

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

[Using social network analysis to examine care for older drug users in three major cities in Germany : Results of a pilot study].

PubMed

Kuhn, U; Hofmann, L; Hoff, T; Färber, N

2018-05-04

Compared with the general population, chronic drug addicts already start showing typical aging problems by the age of 40 years. The increasing number of older drug addicts leads to questions of what an adequate health and social care should look like. This discussion particularly takes place in the context of a sufficient integration of different care systems. A sufficient integration requires an improvement in the networking of substance treatment, nursing care and medical care services. The purpose of this study was to investigate the care structure of older people who use drugs and the services involved in a social network analysis. This was a descriptive design of the pilot study. The study objective was to gain first-hand knowledge about the health and social care situation, the quality of care concerning this client group and to identify supply gaps. Therefore, the three regions Cologne, Dusseldorf and Frankfurt/Main were exemplarily examined. The data for the social network analysis was gathered by a quantitative online questionnaire. Therefore, especially central network members were contacted and asked to participate. The survey was conducted in two waves. In total, 65 practitioners of all surveyed cities participated in the second wave. The centrality measures assessed indicated that in all regions institutions of the substance abuse service network hold central positions in terms of conveying information. The moderate density values of the networks suggest that there are sufficient cooperation structures. Care deficits were identified most frequently in the areas of housing and nursing care. The results provide the first systematic insights and a description of the cooperation practice in the care system. Because of the limitations, further research and practice issues are raised.

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

PubMed

O'Malley, A James

2013-02-20

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

Intra-Urban Movement Flow Estimation Using Location Based Social Networking Data

NASA Astrophysics Data System (ADS)

Kheiri, A.; Karimipour, F.; Forghani, M.

2015-12-01

In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN) data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.

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

PubMed Central

Choi, Jun-Ho; Lee, Jong-Seok

2016-01-01

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

Latino Civic Group Participation, Social Networks, and Physical Activity.

PubMed

Marquez, Becky; Gonzalez, Patricia; Gallo, Linda; Ji, Ming

2016-07-01

We examined whether social networks and resource awareness for physical activity may mediate the relationship between civic group participation and physical activity. This is a cross-sectional study of a randomly selected sample of 335 Latinos (mean age 42.1 ± 16.4 years) participating in the San Diego Prevention Research Center's 2009 Household Community Survey. Serial multiple mediation analysis tested the hypothesis that civic group participation is associated with meeting physical activity recommendations through an indirect mechanism of larger social networks followed by greater knowledge of physical activity community resources. The indirect effects of level of civic group participation as well as religious, health, neighborhood, or arts group participation on meeting national physical activity recommendations were significant in models testing pathways through social network size and physical activity resource awareness. The direct effect was only significant for health group indicating that participating in a health group predicted physical activity independent of social network size and awareness of physical activity resources. Belonging to civic groups may promote physical activity engagement through social network diffusion of information on community physical activity resources which has implications for health.

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

PubMed

Choi, Jun-Ho; Lee, Jong-Seok

2015-01-01

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

Leveraging Social Networking Technologies: An Analysis of the Knowledge Flows Facilitated by Social Media and the Potential Improvements in Situational Awareness, Readiness, and Productivity

DTIC Science & Technology

2010-09-01

articulating perception, interpretation and actionable prediction in an operational environment . BCKS’ success with digital storytelling has far...podcasts; wikis and other collaborative spaces; social networks such as Facebook and LinkedIn; other user generated content; virtual social environments ...study of Xerox’s knowledge management systems noting that 80% of its IT was focused on adapting to the social dynamics of its workplace environment

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

Social Support Networks and HIV/STI Risk Behaviors Among Latino Immigrants in a New Receiving Environment.

PubMed

Althoff, Meghan D; Theall, Katherine; Schmidt, Norine; Hembling, John; Gebrekristos, Hirut T; Thompson, Michelle M; Muth, Stephen Q; Friedman, Samuel R; Kissinger, Patricia

2017-12-01

The objectives of this study were to: (1) describe the quantity and quality of social support networks of Latino immigrants living in a new receiving environment, and (2) determine the role such networks play in their HIV/STI risk behaviors, including substance use. Double incentivized convenience sampling was used to collect egocentric social support network data on 144 Latino immigrants. Latent class analysis was used for data reduction and to identify items best suited to measure quality and quantity of social support. Moderate and high quantity and quality of social support were protective of HIV/STI sexual risk behavior compared to low quantity and quality of support, after adjustment for gender, years in New Orleans and residing with family. Neither measure of social support was associated with binge drinking. The findings suggest that increased quantity and quality of social support decrease HIV/STI sexual risk behaviors but do not influence binge drinking. Interventions that improve the quantity and quality of social support are needed for Latino immigrants.

Functional connectivity mapping of regions associated with self- and other-processing.

PubMed

Murray, Ryan J; Debbané, Martin; Fox, Peter T; Bzdok, Danilo; Eickhoff, Simon B

2015-04-01

Neuroscience literature increasingly suggests a conceptual self composed of interacting neural regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the pregenual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Mining of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delineate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related to socially oriented processing and contextual information integration. Notably, our findings revealed shared RS connectivity between ensuing self-/other-networks within the ventromedial prefrontal cortex and medial orbitofrontal cortex, suggesting self-updating via integration of self-relevant social information. We, therefore, present initial neurobiological evidence corroborating the increasing claims of an intricate self-network, the architecture of which may promote social value processing. © 2014 Wiley Periodicals, Inc.

Association between financial strain, social network and five-year recovery from first episode psychosis.

PubMed

Mattsson, Maria; Topor, Alain; Cullberg, Johan; Forsell, Yvonne

2008-12-01

Despite much effort to positively affect long-term outcome in psychosis and schizophrenia many patients are still facing a poor outcome with persistent psychotic symptoms and decline in social functioning. The aim of this study was to examine the relationship between financial strain and social network and five-year outcome of first episode psychosis (FEP). FEP patients were divided into recovered (n = 52) and non-recovered (n = 19). Each person was matched according to age and gender with four persons (n = 284) from a longitudinal population-based study. All persons had answered an extensive questionnaire including social network, quantitative and qualitative, financial strain and mental health. Linear regression analysis showed that both financial strain and social network were associated, and had a unique contribution, to outcome. The results indicate that FEP patients might benefit from interventions that reduce financial strain thus facilitating daily life and cultural and social activities.

Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest

PubMed Central

Mayhew, Jessica A.; Mulcahy, John B.

2018-01-01

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

Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest.

PubMed

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

2018-01-01

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

Social Network and Mental Health Among Older Adults in Rural Uttar Pradesh, India: A Cross-Sectional Study.

PubMed

Singh, Lucky; Singh, Prashant Kumar; Arokiasamy, Perianayagam

2016-06-01

The rapid growth of the older population in India draws attention to the factors that contribute to their changing health realities. However, there has hardly been any study in India that has looked at the effects of specific social networks with children, relatives, friends and confidant on depression among older adults. The objective of the study is to investigate the association between social network and depression among the rural elderly. The study population comprised over 630 older adults (aged 60 and above) from the rural areas of Varanasi, Uttar Pradesh. We adopted Berkman's theoretical model of the impact of social relations on depression among the elderly in the Indian context. Results of the Confirmatory Factor Analysis (CFA) demonstrated that the four specific social network types: children, relatives, friends and confidant were tenable. The results showed that a better social network with 'friends/neighbours' was protective against depression among the rural elderly. This clearly points to the need for more social network centres for older adults, so that they can interact with friends within the community or between communities and participate in group activities.

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.

Connections, Paths, and Explanations--A Social Network Approach to Investigating Experiences of Early Childhood Special Education with the ECLS-K

ERIC Educational Resources Information Center

Akers, Kathryn Shirley

2011-01-01

The purpose of this study is to demonstrate a practical application of social network analysis in the field of education using a large-scale data source. Using the Early Childhood Longitudinal Base Year data, a network is identified by examining the connections that occur between supports, both inside and outside formal special education resources…

Mobilizing Ideas in Knowledge Networks: A Social Network Analysis of the Human Resource Management Community 1990-2005

ERIC Educational Resources Information Center

Henneberg, Stephan C.; Swart, Juani; Naude, Peter; Jiang, Zhizhong; Mouzas, Stefanos

2009-01-01

Purpose: The purpose of this paper is to show the role of social networks in mobilizing how actors both impact and are impacted on by their colleagues. It seeks to compare the human resource management (HRM) academic community with two other comparable communities, and to identify those groups that are seen to work closely together.…

Social Media and Networking Technologies: An Analysis of Collaborative Work and Team Communication

ERIC Educational Resources Information Center

Okoro, Ephraim A.; Hausman, Angela; Washington, Melvin C.

2012-01-01

Digital communication increases students' learning outcomes in higher education. Web 2.0 technologies encourages students' active engagement, collaboration, and participation in class activities, facilitates group work, and encourages information sharing among students. Familiarity with organizational use and sharing in social networks aids…

Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

PubMed

Hallgren, Kevin A; McCrady, Barbara S; Caudell, Thomas P; Witkiewitz, Katie; Tonigan, J Scott

2017-11-01

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

PubMed

Hindhede, Anette Lykke; Aagaard-Hansen, Jens

2017-03-01

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

Ontology Design of Influential People Identification Using Centrality

NASA Astrophysics Data System (ADS)

Maulana Awangga, Rolly; Yusril, Muhammad; Setyawan, Helmi

2018-04-01

Identifying influential people as a node in a graph theory commonly calculated by social network analysis. The social network data has the user as node and edge as relation forming a friend relation graph. This research is conducting different meaning of every nodes relation in the social network. Ontology was perfect match science to describe the social network data as conceptual and domain. Ontology gives essential relationship in a social network more than a current graph. Ontology proposed as a standard for knowledge representation for the semantic web by World Wide Web Consortium. The formal data representation use Resource Description Framework (RDF) and Web Ontology Language (OWL) which is strategic for Open Knowledge-Based website data. Ontology used in the semantic description for a relationship in the social network, it is open to developing semantic based relationship ontology by adding and modifying various and different relationship to have influential people as a conclusion. This research proposes a model using OWL and RDF for influential people identification in the social network. The study use degree centrality, between ness centrality, and closeness centrality measurement for data validation. As a conclusion, influential people identification in Facebook can use proposed Ontology model in the Group, Photos, Photo Tag, Friends, Events and Works data.

Nourishing networks: A social-ecological analysis of a network intervention for improving household nutrition in Western Kenya.

PubMed

DeLorme, Autumn L; Gavenus, Erika R; Salmen, Charles R; Benard, Gor Ouma; Mattah, Brian; Bukusi, Elizabeth; Fiorella, Kathryn J

2018-01-01

A growing body of research emphasizes the need to engage social networks in maternal and child nutrition interventions. However, an understanding of how interventions functionally engage not only mothers but fathers, grandparents, friends, and other social network members remains limited. This study uses an adaptation of a social-ecological model to analyze the multiple levels at which the Kanyakla Nutrition Program operates to change behavior. This study analyzes focus group data (four groups; n = 35, 7 men and 28 women) following the implementation of the Kanyakla Nutrition Program, a novel nutrition intervention engaging social networks to increase nutrition knowledge, shift perceptions, and promote positive practices for infant and young child feeding and community nutrition in general. Participant perspectives indicate that the Kanyakla Nutrition Program contributed to nutrition knowledge and confidence, changed perceptions, and supported infant and child feeding practices at the individual, interpersonal, and institutional levels. However, many respondents report challenges in transcending barriers at the broader community and systems levels of influence, where environmental and economic constraints continue to affect food access. Analysis of the Kanyakla Nutrition Program suggests that for interventions addressing household level determinants of nutrition, simultaneously engaging the household's network of interpersonal and community relationships can play a role in building momentum and consensus to address persistent structural barriers to improved nutrition. Copyright © 2017 Elsevier Ltd. All rights reserved.

White matter pathways and social cognition.

PubMed

Wang, Yin; Metoki, Athanasia; Alm, Kylie H; Olson, Ingrid R

2018-04-20

There is a growing consensus that social cognition and behavior emerge from interactions across distributed regions of the "social brain". Researchers have traditionally focused their attention on functional response properties of these gray matter networks and neglected the vital role of white matter connections in establishing such networks and their functions. In this article, we conduct a comprehensive review of prior research on structural connectivity in social neuroscience and highlight the importance of this literature in clarifying brain mechanisms of social cognition. We pay particular attention to three key social processes: face processing, embodied cognition, and theory of mind, and their respective underlying neural networks. To fully identify and characterize the anatomical architecture of these networks, we further implement probabilistic tractography on a large sample of diffusion-weighted imaging data. The combination of an in-depth literature review and the empirical investigation gives us an unprecedented, well-defined landscape of white matter pathways underlying major social brain networks. Finally, we discuss current problems in the field, outline suggestions for best practice in diffusion-imaging data collection and analysis, and offer new directions for future research. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-05-08

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

Social Network Behavior and Engagement Within a Smoking Cessation Facebook Page

PubMed Central

Cole-Lewis, Heather; Perotte, Adler; Galica, Kasia; Dreyer, Lindy; Griffith, Christopher; Schwarz, Mary; Yun, Christopher; Patrick, Heather; Coa, Kisha

2016-01-01

Background Social media platforms are increasingly being used to support individuals in behavior change attempts, including smoking cessation. Examining the interactions of participants in health-related social media groups can help inform our understanding of how these groups can best be leveraged to facilitate behavior change. Objective The aim of this study was to analyze patterns of participation, self-reported smoking cessation length, and interactions within the National Cancer Institutes’ Facebook community for smoking cessation support. Methods Our sample consisted of approximately 4243 individuals who interacted (eg, posted, commented) on the public Smokefree Women Facebook page during the time of data collection. In Phase 1, social network visualizations and centrality measures were used to evaluate network structure and engagement. In Phase 2, an inductive, thematic qualitative content analysis was conducted with a subsample of 500 individuals, and correlational analysis was used to determine how participant engagement was associated with self-reported session length. Results Between February 2013 and March 2014, there were 875 posts and 4088 comments from approximately 4243 participants. Social network visualizations revealed the moderator’s role in keeping the community together and distributing the most active participants. Correlation analyses suggest that engagement in the network was significantly inversely associated with cessation status (Spearman correlation coefficient = −0.14, P=.03, N=243). The content analysis of 1698 posts from 500 randomly selected participants identified the most frequent interactions in the community as providing support (43%, n=721) and announcing number of days smoke free (41%, n=689). Conclusions These findings highlight the importance of the moderator for network engagement and provide helpful insights into the patterns and types of interactions participants are engaging in. This study adds knowledge of how the social network of a smoking cessation community behaves within the confines of a Facebook group. PMID:27485315

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

PubMed

Sah, Pratha; Mann, Janet; Bansal, Shweta

2018-05-01

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

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

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

2014-02-01

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

Residents Perceptions of Friendship and Positive Social Networks Within a Nursing Home.

PubMed

Casey, Anne-Nicole S; Low, Lee-Fay; Jeon, Yun-Hee; Brodaty, Henry

2016-10-01

(i) To describe nursing home residents' perceptions of their friendship networks using social network analysis (SNA) and (ii) to contribute to theory regarding resident friendship schema, network structure, and connections between network ties and social support. Cross-sectional interviews, standardized assessments, and observational data were collected in three care units, including a Dementia Specific Unit (DSU), of a 94-bed Sydney nursing home. Full participation consent was obtained for 36 residents aged 63-94 years. Able residents answered open-ended questions about friendship, identified friendship ties, and completed measures of nonfamily social support. Residents retained clear concepts of friendship and reported small, sparse networks. Nonparametric pairwise comparisons indicated that DSU residents reported less perceived social support (median = 7) than residents from the other units (median = 17; U = 10.0, p = .034, r = -.51), (median = 14; U = 0.0, p = .003, r = -.82). Greater perceived social support was moderately associated with higher number of reciprocated ties [ρ(25) = .49, p = .013]. Though some residents had friendships, many reported that nursing home social opportunities did not align with their expectations of friendship. Relationships with coresidents were associated with perceptions of social support. SNA's relational perspective elucidated network size, tie direction, and density, advancing understanding of the structure of residents' networks and flow of subjective social support through that structure. Understanding resident expectations and perceptions of their social networks is important for care providers wishing to improve quality of life in nursing homes. © The Author 2015. 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.

Enhancing topology adaptation in information-sharing social networks

NASA Astrophysics Data System (ADS)

Cimini, Giulio; Chen, Duanbing; Medo, Matúš; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

2012-04-01

The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an empirical analysis of different online social networking sites and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. These rules create networks which are effective in information diffusion and resemble structures resulting from real social systems.

Foregrounding the Role of Relationships in Reform: A Social Network Perspective on Leadership and Change

ERIC Educational Resources Information Center

Liou, Yi-Hwa; Daly, Alan J.; Brown, Chris; del Fresno, Miguel

2015-01-01

Purpose: The role of relationships in the process of leadership and change is central, yet the social aspect of the work of reform is often background in favor of more technical approaches to improvement. Therefore, the purpose of this paper is to argue that social network theory and analysis provides a useful theory and set of tools to unpack the…

Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

NASA Astrophysics Data System (ADS)

Hou, Rui; Wu, Jiawen; Du, Helen S.

2017-03-01

To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

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.

Patterns of victimization between and within peer clusters in a high school social network.

PubMed

Swartz, Kristin; Reyns, Bradford W; Wilcox, Pamela; Dunham, Jessica R

2012-01-01

This study presents a descriptive analysis of patterns of violent victimization between and within the various cohesive clusters of peers comprising a sample of more than 500 9th-12th grade students from one high school. Social network analysis techniques provide a visualization of the overall friendship network structure and allow for the examination of variation in victimization across the various peer clusters within the larger network. Social relationships among clusters with varying levels of victimization are also illustrated so as to provide a sense of possible spatial clustering or diffusion of victimization across proximal peer clusters. Additionally, to provide a sense of the sorts of peer clusters that support (or do not support) victimization, characteristics of clusters at both the high and low ends of the victimization scale are discussed. Finally, several of the peer clusters at both the high and low ends of the victimization continuum are "unpacked", allowing examination of within-network individual-level differences in victimization for these select clusters.

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach

PubMed Central

Senior, Alistair M.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. PMID:26858671

Social network correlates of risky sexual behavior among adolescents in Bahir Dar and Mecha Districts, North West Ethiopia: an institution-based study.

PubMed

Asrese, Kerebih; Mekonnen, Alemtsehay

2018-04-11

Behaviors established during adolescence such as risky sexual behaviors have negative effects on future health and well-being. Extant literature indicated that individual attributes such as peer pressure and substance use have impacts on healthy development of young peoples' sexual behavior. The patterns of relationships (social network structure) and the social network content (members' norm regarding sexual practice) established by adolescents' network on adolescents' risky sexual behaviors are not well investigated. This cross-sectional study assessed the roles of social networks on sexual behavior of high school adolescents in Bahir Dar and Mecha district, North West Ethiopia. Data were collected from 806 high school adolescents using a pretested anonymously self administered questionnaire. Hierarchical logistic regression model was used for analysis. The results indicated that more than 13% had risky sexual behavior. Taking social networks into account improved the explanation of risky sexual behavior over individual attributes. Adolescents embedded within increasing sexual practice approving norm (AOR 1.61; 95%CI: 1.04 - 2.50), increasing network tie strength (AOR 1.12; 95% CI: 1.06 - 1.19), and homogeneous networks (AOR 1.58; 95% CI: .98 - 2.55) were more likely to had risky sexual behavior. Engaging within increasing number of sexuality discussion networks was found protective of risky sexual behavior (AOR .84; 95% CI: .72 - .97). Social networks better predict adolescent's risky sexual behavior than individual attributes. The findings indicated the circumstances or contexts that social networks exert risks or protective effects on adolescents' sexual behavior. Programs designed to reduce school adolescents' sexual risk behavior should consider their patterns of social relationships.

Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives

PubMed Central

2016-01-01

Background Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. Objective We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members’ conversations. Methods Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. Results We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. Conclusions (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck’s cognitive theory of depression; (2) the social structure of the MDD group is much stickier than those of other social media groups, indicating the tendency of mutual communications and efficient spread of information in the MDD group; and (3) the linguistic patterns of MDD members are associated with their topological positions in the social network. PMID:26966078

Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives.

PubMed

Xu, Ronghua; Zhang, Qingpeng

2016-03-10

Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members' conversations. Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck's cognitive theory of depression; (2) the social structure of the MDD group is much stickier than those of other social media groups, indicating the tendency of mutual communications and efficient spread of information in the MDD group; and (3) the linguistic patterns of MDD members are associated with their topological positions in the social network.

Ego Network Analysis of Upper Division Physics Student Survey

NASA Astrophysics Data System (ADS)

Brewe, Eric

2017-01-01

We present the analysis of student networks derived from a survey of upper division physics students. Ego networks focus on the connections that center on one person (the ego). The ego networks in this talk come from a survey that is part of an overall project focused on understanding student retention and persistence. The theory underlying this work is that social and academic integration are essential components to supporting students continued enrollment and ultimately graduation. This work uses network analysis as a way to investigate the role of social and academic interactions in retention and persistence decisions. We focus on student interactions with peers, on mentoring interactions with physics department faculty, and on engagement in physics groups and how they influence persistence. Our results, which are preliminary, will help frame the ongoing research project and identify ways in which departments can support students. This work supported by NSF grant #PHY 1344247.

Pattern Analysis in Social Networks with Dynamic Connections

NASA Astrophysics Data System (ADS)

Wu, Yu; Zhang, Yu

In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Most existing work in this area models social network in which agent relations are fixed; instead, we focus on dynamic social networks where agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation rule called the Highest Weighted Reward (HWR) rule, with which agents dynamically choose their neighbors in order to maximize their own utilities based on the rewards from previous interactions. Our experiments show that in the 2-action pure coordination game, our system will stabilize to a clustering state where all relationships in the network are rewarded with the optimal payoff. Our experiments also reveal additional interesting patterns in the network.

Are maternal social networks and perceptions of trust associated with suspected autism spectrum disorder in offspring? A population-based study in Japan.

PubMed

Fujiwara, Takeo; Kawachi, Ichiro

2014-01-01

To investigate the associations of maternal social networks and perceptions of trust with the prevalence of suspected autism spectrum disorders in 18-month-old offspring in Japan. Questionnaires included measurements of maternal social networks (number of relatives or friends they could call upon for assistance), maternal perceptions of trust, mutual assistance (i.e. individual measures of "cognitive social capital"), and social participation (i.e. individual measures of "structural social capital") as well as the Modified Checklist for Autism in Toddlers to detect suspected autism spectrum disorder (ASD). These tools were mailed to all families with 18-month-old toddlers in Chiba, a city near Tokyo (N = 6061; response rate: 64%). The association between social capital or social network indicators and suspected ASD were analyzed, adjusted for covariates by logistic regression analysis. Low maternal social trust was found to be significantly positively associated with suspected ASD in toddlers compared with high maternal social trust (adjusted odds ratio [OR]: 1.82, 95% confidence interval [CI]: 1.38 to 2.40); mutual aid was also significantly positively related (low vs. high: OR, 2.08, 95% CI: 1.59 to 2.73 [corrected]). However, maternal community participation showed U-shape association with suspected ASD of offspring. Maternal social network showed consistent inverse associations with suspected ASD of offspring, regardless of the type of social connection (e.g., relatives, neighbors, or friends living outside of their neighborhood). Mothers' cognitive social capital and social networks, but not structural social capital, might be associated with suspected ASD in offspring.

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

PubMed

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

2015-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Power Positions: International Organizations, Social Networks, and Conflict

ERIC Educational Resources Information Center

Hafner-Burton, Emilie M.; Montgomery, Alexander H.

2006-01-01

A growing number of international relations scholars argue that intergovernmental organizations (IGOs) promote peace. Existing approaches emphasize IGO membership as an important causal attribute of individual states, much like economic development and regime type. The authors use social network analysis to show that IGO memberships also create a…

Teacher Agency in Educational Reform: Lessons from Social Networks Research

ERIC Educational Resources Information Center

Datnow, Amanda

2012-01-01

This article provides a context for understanding how social networks among teachers support or constrain school improvement in terms of instructional practice, professional development, and educational reform. It comments on the articles in this special issue, summarizing their contributions to the field. This analysis reveals several important…

The Contribution of Extracurricular Activities to Adolescent Friendships: New Insights through Social Network Analysis

ERIC Educational Resources Information Center

Schaefer, David R.; Simpkins, Sandra D.; Vest, Andrea E.; Price, Chara D.

2011-01-01

Extracurricular activities are settings that are theorized to help adolescents maintain existing friendships and develop new friendships. The overarching goal of the current investigation was to examine whether coparticipating in school-based extracurricular activities supported adolescents' school-based friendships. We used social network methods…

Social and Virtual Networks: Evaluating Synchronous Online Interviewing Using Instant Messenger

ERIC Educational Resources Information Center

Hinchcliffe, Vanessa; Gavin, Helen

2009-01-01

This paper describes an evaluation of the quality and utility of synchronous online interviewing for data collection in social network research. Synchronous online interviews facilitated by Instant Messenger as the communication medium, were undertaken with ten final year university students. Quantitative and qualitative content analysis of…

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

ERIC Educational Resources Information Center

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

2016-01-01

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

Social Network Supported Process Recommender System

PubMed Central

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

Axelrod's Metanorm Games on Networks

PubMed Central

Galán, José M.; Łatek, Maciej M.; Rizi, Seyed M. Mussavi

2011-01-01

Metanorms is a mechanism proposed to promote cooperation in social dilemmas. Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation. We generalize Axelrod's analysis of metanorms dynamics to interactions unfolding on networks through simulation and mathematical modeling. Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation. In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperation. PMID:21655211

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.

Incorporating geographic settings into a social network analysis of injection drug use and bloodborne pathogen prevalence.

PubMed

Wylie, John L; Shah, Lena; Jolly, Ann

2007-09-01

Using social network analysis, we investigated how communal meeting places can link injection drug user (IDU) populations and create opportunities for the transmission of bloodborne pathogens. In our locale, specific hotels played a key role in the injection drug scene. Within this hotel network some IDU injected at only one hotel while others injected at multiple hotels; this latter group potentially acted as spatial bridges linking relatively distinct hotel networks. Pathogen prevalence showed a gradation with the highest prevalence occurring at the centre of the network. Consistent with pathogen prevalence, people most central to the network were more likely to engage in risky injection practices. Incorporating geographic place into analyses involving IDU can contribute to an understanding of pathogen transmission patterns in an area and assist public health efforts to develop targeted intervention programs.

Methamphetamine Use among Homeless Former Foster Youth: The Mediating Role of Social Networks

PubMed Central

Yoshioka-Maxwell, Amanda; Rice, Eric; Rhoades, Harmony; Winetrobe, Hailey

2015-01-01

Objectives Social network analysis can provide added causal insight into otherwise confusing epidemiologic findings in public health research. Although foster care and homelessness are risk factors for methamphetamine use, current research has failed to explicate why homeless youth with foster care experience engage in methamphetamine use at higher rates than other homeless young adults. This study examined the mediating effect of network engagement and time spent homeless on the relationship between foster care experience and recent methamphetamine use among homeless youth in Los Angeles. Methods Egocentric network data from a cross-sectional community-based sample (n = 652) of homeless youth aged 13–25 were collected from drop-in centers in Los Angeles. Questions addressed foster care experience, time spent homeless, methamphetamine use, and perceived drug use in social networks. Path analysis was performed in SAS to examine mediation. Results Controlling for all other variables, results of path analysis regarding recent methamphetamine use indicated a direct effect between foster care experience and recent methamphetamine use (B = .269, t = 2.73, p < .01). However, this direct effect became statistically nonsignificant when time spent homeless and network methamphetamine use were added to the model, and indirect paths from time spent homeless and network methamphetamine use became statistically significant. Conclusions Foster care experience influenced recent methamphetamine use indirectly through time spent homeless and methamphetamine use by network members. Efforts to reduce methamphetamine use should focus on securing stable housing and addressing network interactions among homeless former foster youth. PMID:26146647

Learning Networks: Iran and the Effects of Sanctions

DTIC Science & Technology

2013-03-27

synthesizes and summarizes our research efforts. 15. SUBJECT TERMS Network Science, Social Network Analysis, Dynamic Networks 16. SECURITY...www.ecssr.com/ECSSR/appmanager/portal/ecssr?_nfpb=true. Klebnikov, Paul. " Millionaire Mullahs." Forbes. Forbes Magazine, 21 July 2003. Web. http

The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at ‘La Forêt des Singes’: A Multilevel Social Network Approach

PubMed Central

Sosa, Sebastian

2016-01-01

A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network. PMID:27148137

The Influence of Gender, Age, Matriline and Hierarchical Rank on Individual Social Position, Role and Interactional Patterns in Macaca sylvanus at 'La Forêt des Singes': A Multilevel Social Network Approach.

PubMed

Sosa, Sebastian

2016-01-01

A society is a complex system composed of individuals that can be characterized by their own attributes that influence their behaviors. In this study, a specific analytical protocol based on social network analysis was adopted to investigate the influence of four attributes (gender, age, matriline, and hierarchical rank) on affiliative (allogrooming) and agonistic networks in a non-human primate species, Macaca sylvanus, at the park La Forêt des Singes in France. The results show significant differences with respect to the position (i.e., centric, peripheral) and role (i.e., implication in the network cohesiveness) of an individual within a social network and hence interactional patterns. Females are more central, more active, and have a denser ego network in the affiliative social network tan males; thus, they contribute in a greater way to the cohesive structure of the network. High-ranking individuals are likely to receive fewer agonistic behaviors than low-ranking individuals, and high-ranking females receive more allogrooming. I also observe homophily for affiliative interactions regarding all attributes and homophily for agonistic interactions regarding gender and age. Revealing the positions, the roles, and the interactional behavioral patterns of individuals can help understand the mechanisms that shape the overall structure of a social network.

A dedicated network for social interaction processing in the primate brain.

PubMed

Sliwa, J; Freiwald, W A

2017-05-19

Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities. Copyright © 2017, American Association for the Advancement of Science.

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.

Network analysis reveals disrupted functional brain circuitry in drug-naive social anxiety disorder.

PubMed

Yang, Xun; Liu, Jin; Meng, Yajing; Xia, Mingrui; Cui, Zaixu; Wu, Xi; Hu, Xinyu; Zhang, Wei; Gong, Gaolang; Gong, Qiyong; Sweeney, John A; He, Yong

2017-12-07

Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the "fear circuit", including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety. Copyright © 2017. Published by Elsevier Inc.

For everything a season? A month-by-month analysis of social network resources in later life.

PubMed

Upenieks, Laura; Settels, Jason; Schafer, Markus H

2018-01-01

It is widely acknowledged that informal social ties provide older persons with many resources that serve to protect and improve their levels of health and well-being. Most studies on this topic, however, ignore the month or season of the year during which data was accumulated. This study proposes two hypotheses to explain seniors' social network resources over the calendar year: the "fluctuation hypothesis", which proposes that seasonal variation, in the form of weather fluctuations, institutional calendars, and holidays, might influence the social lives and resources of older persons, and the "network stability" perspective, which, informed by tenets of convoy theory and socioemotional selectivity theory, emphasizes the increasing importance of close network ties as individuals age and the stability of these ties. Using two waves (2005-2006 and 2010-2011) of the National Social Life, Health, and Aging Project (NSHAP), a nationally representative sample of community-dwelling older adults aged 57-85 in the United States, we examine a diverse set of nine social connectedness outcomes. Results, overall, support the network stability perspective, as the only social connectedness outcome found to significantly vary by month of year was average closeness with network members. We conclude by suggesting some methodological considerations for survey research and by noting how these findings complement the growing literature on inter-year fluctuation in social networks and social support. Changes in older adults' networks, while frequently observable over the course of years, do not seem to be seasonally patterned. Copyright © 2017 Elsevier Inc. All rights reserved.

Bayesian Analysis for Exponential Random Graph Models Using the Adaptive Exchange Sampler.

PubMed

Jin, Ick Hoon; Yuan, Ying; Liang, Faming

2013-10-01

Exponential random graph models have been widely used in social network analysis. However, these models are extremely difficult to handle from a statistical viewpoint, because of the intractable normalizing constant and model degeneracy. In this paper, we consider a fully Bayesian analysis for exponential random graph models using the adaptive exchange sampler, which solves the intractable normalizing constant and model degeneracy issues encountered in Markov chain Monte Carlo (MCMC) simulations. The adaptive exchange sampler can be viewed as a MCMC extension of the exchange algorithm, and it generates auxiliary networks via an importance sampling procedure from an auxiliary Markov chain running in parallel. The convergence of this algorithm is established under mild conditions. The adaptive exchange sampler is illustrated using a few social networks, including the Florentine business network, molecule synthetic network, and dolphins network. The results indicate that the adaptive exchange algorithm can produce more accurate estimates than approximate exchange algorithms, while maintaining the same computational efficiency.

A longitudinal social network analysis of the editorial boards of medical informatics and bioinformatics journals.

PubMed

Malin, Bradley; Carley, Kathleen

2007-01-01

The goal of this research is to learn how the editorial staffs of bioinformatics and medical informatics journals provide support for cross-community exposure. Models such as co-citation and co-author analysis measure the relationships between researchers; but they do not capture how environments that support knowledge transfer across communities are organized. In this paper, we propose a social network analysis model to study how editorial boards integrate researchers from disparate communities. We evaluate our model by building relational networks based on the editorial boards of approximately 40 journals that serve as research outlets in medical informatics and bioinformatics. We track the evolution of editorial relationships through a longitudinal investigation over the years 2000 through 2005. Our findings suggest that there are research journals that support the collocation of editorial board members from the bioinformatics and medical informatics communities. Network centrality metrics indicate that editorial board members are located in the intersection of the communities and that the number of individuals in the intersection is growing with time. Social network analysis methods provide insight into the relationships between the medical informatics and bioinformatics communities. The number of editorial board members facilitating the publication intersection of the communities has grown, but the intersection remains dependent on a small group of individuals and fragile.

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

Community Attachment and Satisfaction: The Role of a Community's Social Network Structure

ERIC Educational Resources Information Center

Crowe, Jessica

2010-01-01

This paper links the micro and macro levels of analysis by examining how different aspects of community sentiment are affected by one's personal ties to the community compared with the organizational network structure of the community. Using data collected from residents of six communities in Washington State, network analysis combined with…

Personal Network Correlates of Alcohol, Cigarette, and Marijuana Use Among Homeless Youth

PubMed Central

Wenzel, Suzanne L.; Tucker, Joan S.; Golinelli, Daniela; Green, Harold D.; Zhou, Annie

2013-01-01

Background Youth who are homeless and on their own are among the most marginalized individuals in the United States and face multiple risks, including use of substances. This study investigates how the use of alcohol, cigarettes, and marijuana among homeless youth may be influenced by characteristics of their social networks. Methods Homeless youth aged 13–24 were randomly sampled from 41 service and street sites in Los Angeles County (N = 419). Predictors of substance use were examined using linear regression analysis (for average number of drinks and average number of cigarettes per day) and negative binomal regression analysis (for frequency of past month marijuana use). Results Youth with more substance users in their networks reported greater alcohol, cigarette, and marijuana consumption regardless of whether these network members provided tangible or emotional support. Marijuana use was more frequent for youth who met more network members through homeless settings, but less frequent among those who met more network members through treatment or AA/NA. Greater alcohol use occurred among youth who met more network members through substance use-related activities. Youth having more adults in positions of responsibility in their networks consumed less alcohol, and those with more school attendees in their networks consumed less alcohol and cigarettes. Conclusions Findings highlight the importance of social context in understanding substance use among homeless youth. Results also support the relevance of network-based interventions to change social context for substance using youth, in terms of both enhancing pro-social influences and reducing exposure to substance use. PMID:20656423

Personal network correlates of alcohol, cigarette, and marijuana use among homeless youth.

PubMed

Wenzel, Suzanne L; Tucker, Joan S; Golinelli, Daniela; Green, Harold D; Zhou, Annie

2010-11-01

Youth who are homeless and on their own are among the most marginalized individuals in the United States and face multiple risks, including use of substances. This study investigates how the use of alcohol, cigarettes, and marijuana among homeless youth may be influenced by characteristics of their social networks. Homeless youth aged 13-24 were randomly sampled from 41 service and street sites in Los Angeles County (N=419). Predictors of substance use were examined using linear regression analysis (for average number of drinks and average number of cigarettes per day) and negative binomial regression analysis (for frequency of past month marijuana use). Youth with more substance users in their networks reported greater alcohol, cigarette, and marijuana consumption regardless of whether these network members provided tangible or emotional support. Marijuana use was more frequent for youth who met more network members through homeless settings, but less frequent among those who met more network members through treatment or AA/NA. Greater alcohol use occurred among youth who met more network members through substance use-related activities. Youth having more adults in positions of responsibility in their networks consumed less alcohol, and those with more school attendees in their networks consumed less alcohol and cigarettes. Findings highlight the importance of social context in understanding substance use among homeless youth. Results also support the relevance of network-based interventions to change social context for substance-using youth, in terms of both enhancing pro-social influences and reducing exposure to substance use. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

2010-01-01

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

Origin of Peer Influence in Social Networks

NASA Astrophysics Data System (ADS)

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

2014-03-01

Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

Social dilemmas in an online social network: The structure and evolution of cooperation

NASA Astrophysics Data System (ADS)

Fu, Feng; Chen, Xiaojie; Liu, Lianghuan; Wang, Long

2007-11-01

We investigate two paradigms for studying the evolution of cooperation—Prisoner's Dilemma and Snowdrift game in an online friendship network, obtained from a social networking site. By structural analysis, it is revealed that the empirical social network has small-world and scale-free properties. Besides, it exhibits assortative mixing pattern. Then, we study the evolutionary version of the two types of games on it. It is found that cooperation is substantially promoted with small values of game matrix parameters in both games. Whereas the competent cooperators induced by the underlying network of contacts will be dramatically inhibited with increasing values of the game parameters. Further, we explore the role of assortativity in evolution of cooperation by random edge rewiring. We find that increasing amount of assortativity will to a certain extent diminish the cooperation level. We also show that connected large hubs are capable of maintaining cooperation. The evolution of cooperation on empirical networks is influenced by various network effects in a combined manner, compared with that on model networks. Our results can help understand the cooperative behaviors in human groups and society.

Competition between Homophily and Information Entropy Maximization in Social Networks

PubMed Central

Zhao, Jichang; Liang, Xiao; Xu, Ke

2015-01-01

In social networks, it is conventionally thought that two individuals with more overlapped friends tend to establish a new friendship, which could be stated as homophily breeding new connections. While the recent hypothesis of maximum information entropy is presented as the possible origin of effective navigation in small-world networks. We find there exists a competition between information entropy maximization and homophily in local structure through both theoretical and experimental analysis. This competition suggests that a newly built relationship between two individuals with more common friends would lead to less information entropy gain for them. We demonstrate that in the evolution of the social network, both of the two assumptions coexist. The rule of maximum information entropy produces weak ties in the network, while the law of homophily makes the network highly clustered locally and the individuals would obtain strong and trust ties. A toy model is also presented to demonstrate the competition and evaluate the roles of different rules in the evolution of real networks. Our findings could shed light on the social network modeling from a new perspective. PMID:26334994

Social network analysis of public health programs to measure partnership.

PubMed

Schoen, Martin W; Moreland-Russell, Sarah; Prewitt, Kim; Carothers, Bobbi J

2014-12-01

In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Social Network Analysis and Its Applications in Wireless Sensor and Vehicular Networks

NASA Astrophysics Data System (ADS)

Papadimitriou, Alexis; Katsaros, Dimitrios; Manolopoulos, Yannis

Ever since the introduction of wireless sensor networks in the research and development agenda, the corresponding community has been eager to harness the endless possibilities that this new technology has to offer. These micro sensor nodes, whose capabilities have skyrocketed over the last couple of years, have allowed for a wide range of applications to be created; applications that not so long ago would seem impossible, impractical and time-consuming. It would only be logical to expect that researchers from other fields would take an interest in sensor networks, hence expanding the already wide variety of algorithms, theoretical proofs and applications that existed beforehand. Social Network Analysis is one such field, which has instigated a paradigm shift in the way we view sensor nodes.

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.

A Privacy Preservation Model for Health-Related Social Networking Sites.

PubMed

Li, Jingquan

2015-07-08

The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.

A Privacy Preservation Model for Health-Related Social Networking Sites

PubMed Central

2015-01-01

The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS. PMID:26155953

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