Social Software: Participants' Experience Using Social Networking for Learning

ERIC Educational Resources Information Center

Batchelder, Cecil W.

2010-01-01

Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…

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

PubMed Central

Wang, Xue-Guang

2014-01-01

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

Data Quality in Online Health Social Networks for Chronic Diseases

ERIC Educational Resources Information Center

Venkatesan, Srikanth

2017-01-01

Can medical advice from other participants in online health social networks impact patient safety? What can we do alleviate this problem? How does the accuracy of information on such networks affect the patients?. There has been a significant increase , in recent years, in the use of online health social network sites as more patients seek to…

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

PubMed Central

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

2016-01-01

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

Community-Based Social Networks: Generation of Power Law Degree Distribution and IP Solutions to the KPP

ERIC Educational Resources Information Center

Wu, Wentao

2012-01-01

The objective of this thesis is two-fold: (1) to investigate the degree distribution property of community-based social networks (CSNs) and (2) to provide solutions to a pertinent problem, the Key Player Problem. In the first part of this thesis, we consider a growing community-based network in which the ability of nodes competing for links to new…

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

PubMed Central

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

2010-01-01

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

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…

Independent and Interactive Effects of Neighborhood Disadvantage and Social Network Characteristics on Problem Drinking after Treatment.

PubMed

Mericle, Amy A; Kaskutas, Lee A; Polcin, Doug L; Karriker-Jaffe, Katherine J

2018-01-01

Socioecological approaches to public health problems like addiction emphasize the importance of person-environment interactions. Neighborhood and social network characteristics may influence the likelihood of relapse among individuals in recovery, but these factors have been understudied, particularly with respect to conceptualizing social network characteristics as moderators of neighborhood disadvantage. Drawing from a larger prospective study of individuals recruited from outpatient treatment (N=451) and interviewed 1, 3, 5, and 7 years later, the aim of this study was to examine the independent and interactive effects of neighborhood and social network characteristics on continued problem drinking after treatment. Models using generalized estimating equations controlling for demographic and other risk factors found the number of heavy drinkers in one's network increases risk of relapse, with the effects being significantly stronger among those living in disadvantaged neighborhoods than among those in non-disadvantaged neighborhoods. No independent effects were found for neighborhood disadvantage or for the number of network members supporting reduced drinking. Future research is needed to examine potential protective factors in neighborhoods which may offset socioeconomic disadvantage as well as to investigate the functions that network members serve in helping to improve long-term treatment outcomes.

Adolescent Peer Relationships and Behavior Problems Predict Young Adults' Communication on Social Networking Websites

ERIC Educational Resources Information Center

Mikami, Amori Yee; Szwedo, David E.; Allen, Joseph P.; Evans, Meredyth A.; Hare, Amanda L.

2010-01-01

This study examined online communication on social networking web pages in a longitudinal sample of 92 youths (39 male, 53 female). Participants' social and behavioral adjustment was assessed when they were ages 13-14 years and again at ages 20-22 years. At ages 20-22 years, participants' social networking website use and indicators of friendship…

Perceived control moderates the relationship between social capital and binge drinking: longitudinal findings from the Montreal Neighborhood Networks and Health Aging (MoNNET-HA) panel.

PubMed

Child, Stephanie; Stewart, Steven; Moore, Spencer

2017-02-01

Cross-sectional research suggests social capital has negative consequences for problem drinking behaviors. Previous studies have suggested psychosocial resources, including perceived control, may buffer this association. Little research has examined whether such relationships persist longitudinally. Random effects models examined between-person relationships among problem drinking, social capital, and perceived control, and whether perceived control moderated the relationship between social capital and drinking. Fixed effects models assessed whether social capital and perceived control were related to changes in problem drinking. Greater network capital and generalized trust predicted higher odds of binge drinking (RR = 1.08; 95% CI = 1.03-1.12 and RR = 1.23; 95% CI = 1.03-1.48, respectively). Perceived control moderated the positive association of network capital with binge drinking (RR = 0.91; 95% CI = 0.87-0.96). The present findings support previous notions about the complex role of social capital on health, and offer new insights on the role of perceived control on problem drinking. Copyright © 2016 Elsevier Inc. All rights reserved.

Social Networks and the Poor: Toward Effective Policy and Practice.

ERIC Educational Resources Information Center

Auslander, Gail K.; Litwin, Howard

1988-01-01

Study of adults (N=3,025) revealed significantly fewer network resources among the poor than among higher income groups. Asserts social workers must avoid addressing the problems of the poor solely through informal networks and target network interventions carefully to achieve maximum effectiveness. (Author)

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

PubMed Central

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-01-01

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

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

PubMed

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-10-11

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

An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks

NASA Astrophysics Data System (ADS)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.

Pakistani women's use of mental health services and the role of social networks: a systematic review of quantitative and qualitative research.

PubMed

Kapadia, Dharmi; Brooks, Helen Louise; Nazroo, James; Tranmer, Mark

2017-07-01

Pakistani women in the UK are an at-risk group with high levels of mental health problems, but low levels of mental health service use. However, the rates of service use for Pakistani women are unclear, partly because research with South Asian women has been incorrectly generalised to Pakistani women. Further, this research has been largely undertaken within an individualistic paradigm, with little consideration of patients' social networks, and how these may drive decisions to seek help. This systematic review aimed to clarify usage rates, and describe the nature of Pakistani women's social networks and how they may influence mental health service use. Ten journal databases (ASSIA, CINAHL Plus, EMBASE, HMIC, IBSS, MEDLINE, PsycINFO, Social Sciences Abstracts, Social Science Citation Index and Sociological Abstracts) and six sources of grey literature were searched for studies published between 1960 and the end of March 2014. Twenty-one studies met inclusion criteria. Ten studies (quantitative) reported on inpatient or outpatient service use between ethnic groups. Seven studies (four quantitative, three qualitative) investigated the nature of social networks, and four studies (qualitative) commented on how social networks were involved in accessing mental health services. Pakistani women were less likely than white (British) women to use most specialist mental health services. No difference was found between Pakistani and white women for the consultation of general practitioners for mental health problems. Pakistani women's networks displayed high levels of stigmatising attitudes towards mental health problems and mental health services, which acted as a deterrent to seeking help. No studies were found which compared stigma in networks between Pakistani women and women of other ethnic groups. Pakistani women are at a considerable disadvantage in gaining access to and using statutory mental health services, compared with white women; this, in part, is due to negative attitudes to mental health problems evident in social support networks. © 2015 The Authors. Health and Social Care in the Community Published by John Wiley & Sons Ltd.

Adolescent peer relationships and behavior problems predict young adults' communication on social networking websites.

PubMed

Mikami, Amori Yee; Szwedo, David E; Allen, Joseph P; Evans, Meredyth A; Hare, Amanda L

2010-01-01

This study examined online communication on social networking web pages in a longitudinal sample of 92 youths (39 male, 53 female). Participants' social and behavioral adjustment was assessed when they were ages 13-14 years and again at ages 20-22 years. At ages 20-22 years, participants' social networking website use and indicators of friendship quality on their web pages were coded by observers. Results suggested that youths who had been better adjusted at ages 13-14 years were more likely to be using social networking web pages at ages 20-22 years, after statistically controlling for age, gender, ethnicity, and parental income. Overall, youths' patterns of peer relationships, friendship quality, and behavioral adjustment at ages 13-14 years and at ages 20-22 years predicted similar qualities of interaction and problem behavior on their social networking websites at ages 20-22 years. Findings are consistent with developmental theory asserting that youths display cross-situational continuity in their social behaviors and suggest that the conceptualization of continuity may be extended into the online domain. Copyright 2009 APA, all rights reserved.

Adolescent Peer Relationships and Behavior Problems Predict Young Adults' Communication on Social Networking Websites

PubMed Central

Mikami, Amori Yee; Szwedo, David E.; Allen, Joseph P.; Evans, Meredyth A.; Hare, Amanda L.

2010-01-01

This study examined online communication on social networking web pages in a longitudinal sample of 92 youths (39 male, 53 female). Participants' social and behavioral adjustment was assessed when they were ages 13–14 years and again at ages 20–22 years. At ages 20–22 years, participants' social networking website use and indicators of friendship quality on their web pages were coded by observers. Results suggested that youths who had been better adjusted at ages 13–14 years were more likely to be using social networking web pages at ages 20–22 years, after statistically controlling for age, gender, ethnicity, and parental income. Overall, youths' patterns of peer relationships, friendship quality, and behavioral adjustment at ages 13–14 years and at ages 20–22 years predicted similar qualities of interaction and problem behavior on their social networking websites at ages 20–22 years. Findings are consistent with developmental theory asserting that youths display cross-situational continuity in their social behaviors and suggest that the conceptualization of continuity may be extended into the online domain. PMID:20053005

Countervailing social network influences on problem behaviors among homeless youth.

PubMed

Rice, Eric; Stein, Judith A; Milburn, Norweeta

2008-10-01

The impact of countervailing social network influences (i.e., pro-social, anti-social or HIV risk peers) on problem behaviors (i.e., HIV drug risk, HIV sex risk or anti-social behaviors) among 696 homeless youth was assessed using structural equation modeling. Results revealed that older youth were less likely to report having pro-social peers and were more likely to have HIV risk and anti-social peers. A longer time homeless predicted fewer pro-social peers, more anti-social peers, and more HIV risk peers. Heterosexual youth reported fewer HIV risk peers and more pro-social peers. Youth recruited at agencies were more likely to report pro-social peers. Having pro-social peers predicted less HIV sex risk behavior and less anti-social behavior. Having HIV risk peers predicted all problem behavior outcomes. Anti-social peers predicted more anti-social behavior. Once the association between anti-social and HIV risk peers was accounted for independently, having anti-social peers did not independently predict sex or drug risk behaviors.

Male-to-Female Transgender Individuals Building Social Support and Capital From Within a Gender-Focused Network

PubMed Central

Pinto, Rogério M.; Melendez, Rita M.; Spector, Anya Y.

2009-01-01

The literature on male-to-female transgender (MTF) individuals lists myriad problems such individuals face in their day-to-day lives, including high rates of HIV/AIDS, addiction to drugs, violence, and lack of health care. These problems are exacerbated for ethnic and racial minority MTFs. Support available from their social networks can help MTFs alleviate these problems. This article explores how minority MTFs, specifically in an urban environment, develop supportive social networks defined by their gender and sexual identities. Using principles of community-based participatory research (CBPR), 20 African American and Latina MTFs were recruited at a community-based health care clinic. Their ages ranged from 18 to 53. Data were coded and analyzed following standard procedure for content analysis. The qualitative interviews revealed that participants formed their gender and sexual identities over time, developed gender-focused social networks based in the clinic from which they receive services, and engaged in social capital building and political action. Implications for using CBPR in research with MTFs are discussed. PMID:20418965

Male-to-Female Transgender Individuals Building Social Support and Capital From Within a Gender-Focused Network.

PubMed

Pinto, Rogério M; Melendez, Rita M; Spector, Anya Y

2008-09-01

The literature on male-to-female transgender (MTF) individuals lists myriad problems such individuals face in their day-to-day lives, including high rates of HIV/AIDS, addiction to drugs, violence, and lack of health care. These problems are exacerbated for ethnic and racial minority MTFs. Support available from their social networks can help MTFs alleviate these problems. This article explores how minority MTFs, specifically in an urban environment, develop supportive social networks defined by their gender and sexual identities. Using principles of community-based participatory research (CBPR), 20 African American and Latina MTFs were recruited at a community-based health care clinic. Their ages ranged from 18 to 53. Data were coded and analyzed following standard procedure for content analysis. The qualitative interviews revealed that participants formed their gender and sexual identities over time, developed gender-focused social networks based in the clinic from which they receive services, and engaged in social capital building and political action. Implications for using CBPR in research with MTFs are discussed.

E-Center: A Collaborative Platform for Wide Area Network Users

NASA Astrophysics Data System (ADS)

Grigoriev, M.; DeMar, P.; Tierney, B.; Lake, A.; Metzger, J.; Frey, M.; Calyam, P.

2012-12-01

The E-Center is a social collaborative web-based platform for assisting network users in understanding network conditions across network paths of interest to them. It is designed to give a user the necessary tools to isolate, identify, and resolve network performance-related problems. E-Center provides network path information on a link-by-link level, as well as from an end-to-end perspective. In addition to providing current and recent network path data, E-Center is intended to provide a social media environment for them to share issues, ideas, concerns, and problems. The product has a modular design that accommodates integration of other network services that make use of the same network path and performance data.

Lesion mapping of social problem solving

PubMed Central

Colom, Roberto; Paul, Erick J.; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H.

2014-01-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion–symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511

Stress, Social Support and Problem Drinking among Women in Poverty

PubMed Central

Mulia, Nina; Schmidt, Laura; Bond, Jason; Jacobs, Laurie; Korcha, Rachael

2009-01-01

Aims Prior studies find that stress contributes to problem drinking while social support can buffer its effects. However, these studies are largely confined to middle class and general populations. We extend what is known by examining how the unique stressors and forms of social support experienced by women in poverty impact alcohol problems over a 4-year time period. Design and Participants This prospective study used GEE transition modeling and 4 annual waves of survey data from 392 American mothers receiving Temporary Assistance for Needy Families (TANF) in a large Northern California county. Measurements We examined the effects of neighborhood disorder, stressful life events and economic hardship on psychological distress and problem drinking over time, and whether social support moderated these relationships for women in poverty. Findings Neighborhood disorder and stressful life events significantly increased the risk for problem drinking, largely through their effect on psychological distress. We found little evidence, however, that social support buffers poor women from the effects of these stressors. Conclusions Women in poverty are exposed to severe, chronic stressors within their communities and immediate social networks which increase vulnerability to psychological distress and problem drinking. The finding that social support does not buffer stress among these women may reflect their high level of exposure to stressors, as well as the hardships and scarce resources within their networks. If the “private safety net” of the social network fails to provide a strong buffer, more effective environmental interventions that reduce exposure to stressors may be needed to prevent alcohol problems in poor women’s lives. PMID:18855817

Stress, social support and problem drinking among women in poverty.

PubMed

Mulia, Nina; Schmidt, Laura; Bond, Jason; Jacobs, Laurie; Korcha, Rachael

2008-08-01

Previous studies have found that stress contributes to problem drinking, while social support can buffer its effects. However, these studies are confined largely to middle-class and general populations. We extend what is known by examining how the unique stressors and forms of social support experienced by women in poverty impact alcohol problems over a 4-year time-period. This prospective study used generalized estimating equations (GEE) transition modeling and four annual waves of survey data from 392 American mothers receiving Temporary Assistance for Needy Families (TANF) in a large Northern California county. We examined the effects of neighborhood disorder, stressful life events and economic hardship on psychological distress and problem drinking over time, and whether social support moderated these relationships for women in poverty. Neighborhood disorder and stressful life events increased significantly the risk for problem drinking, largely through their effect on psychological distress. We found little evidence, however, that social support buffers poor women from the effects of these stressors. Women in poverty are exposed to severe, chronic stressors within their communities and immediate social networks which increase vulnerability to psychological distress and problem drinking. The finding that social support does not buffer stress among these women may reflect their high level of exposure to stressors, as well as the hardships and scarce resources within their networks. If the 'private safety net' of the social network fails to provide a strong buffer, more effective environmental interventions that reduce exposure to stressors may be needed to prevent alcohol problems in poor women's lives.

A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies

PubMed Central

2017-01-01

The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100

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

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

Unethical Behaviours Preservice Teachers Encounter on Social Networks

ERIC Educational Resources Information Center

Deveci Topal, Arzu; Kolburan Gecer, Aynur

2015-01-01

The development of web 2.0 technology has resulted in an increase in internet sharing. The scope of this study is social networking, which is one of the web 2.0 tools most heavily used by internet users. In this paper, the unethical behaviours that preservice teachers encounter on social networks and the ways to deal with these problems are…

Anti-social networking: crowdsourcing and the cyber defence of national critical infrastructures.

PubMed

Johnson, Chris W

2014-01-01

We identify four roles that social networking plays in the 'attribution problem', which obscures whether or not cyber-attacks were state-sponsored. First, social networks motivate individuals to participate in Distributed Denial of Service attacks by providing malware and identifying potential targets. Second, attackers use an individual's social network to focus attacks, through spear phishing. Recipients are more likely to open infected attachments when they come from a trusted source. Third, social networking infrastructures create disposable architectures to coordinate attacks through command and control servers. The ubiquitous nature of these architectures makes it difficult to determine who owns and operates the servers. Finally, governments recruit anti-social criminal networks to launch attacks on third-party infrastructures using botnets. The closing sections identify a roadmap to increase resilience against the 'dark side' of social networking.

Socially Indigenous Help: The Community Cares for Itself.

ERIC Educational Resources Information Center

Curry, Ronald; Young, Richard D.

Recently, interest has increased in self-help groups, lay referral networks, social support networks, natural helpers, and others which may be placed under a single conceptual umbrella--socially indigenous help--because they all deal with the issue of how people use other people, social groups, and lay institutions to alleviate problems in living,…

Research on social communication network evolution based on topology potential distribution

NASA Astrophysics Data System (ADS)

Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

2011-12-01

Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

Online Social Networking and Addiction—A Review of the Psychological Literature

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2011-01-01

Social Networking Sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. They are seen as a ‘global consumer phenomenon’ with an exponential rise in usage within the last few years. Anecdotal case study evidence suggests that ‘addiction’ to social networks on the Internet may be a potential mental health problem for some users. However, the contemporary scientific literature addressing the addictive qualities of social networks on the Internet is scarce. Therefore, this literature review is intended to provide empirical and conceptual insight into the emerging phenomenon of addiction to SNSs by: (1) outlining SNS usage patterns, (2) examining motivations for SNS usage, (3) examining personalities of SNS users, (4) examining negative consequences of SNS usage, (5) exploring potential SNS addiction, and (6) exploring SNS addiction specificity and comorbidity. The findings indicate that SNSs are predominantly used for social purposes, mostly related to the maintenance of established offline networks. Moreover, extraverts appear to use social networking sites for social enhancement, whereas introverts use it for social compensation, each of which appears to be related to greater usage, as does low conscientiousness and high narcissism. Negative correlates of SNS usage include the decrease in real life social community participation and academic achievement, as well as relationship problems, each of which may be indicative of potential addiction. PMID:22016701

Online social networking and addiction--a review of the psychological literature.

PubMed

Kuss, Daria J; Griffiths, Mark D

2011-09-01

Social Networking Sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. They are seen as a 'global consumer phenomenon' with an exponential rise in usage within the last few years. Anecdotal case study evidence suggests that 'addiction' to social networks on the Internet may be a potential mental health problem for some users. However, the contemporary scientific literature addressing the addictive qualities of social networks on the Internet is scarce. Therefore, this literature review is intended to provide empirical and conceptual insight into the emerging phenomenon of addiction to SNSs by: (1) outlining SNS usage patterns, (2) examining motivations for SNS usage, (3) examining personalities of SNS users, (4) examining negative consequences of SNS usage, (5) exploring potential SNS addiction, and (6) exploring SNS addiction specificity and comorbidity. The findings indicate that SNSs are predominantly used for social purposes, mostly related to the maintenance of established offline networks. Moreover, extraverts appear to use social networking sites for social enhancement, whereas introverts use it for social compensation, each of which appears to be related to greater usage, as does low conscientiousness and high narcissism. Negative correlates of SNS usage include the decrease in real life social community participation and academic achievement, as well as relationship problems, each of which may be indicative of potential addiction.

Managing Trust in Online Social Networks

NASA Astrophysics Data System (ADS)

Bhuiyan, Touhid; Josang, Audun; Xu, Yue

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Link prediction in multiplex online social networks

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Link prediction in multiplex online social networks.

PubMed

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

2017-02-01

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

Peer influences on internalizing and externalizing problems among adolescents: a longitudinal social network analysis.

PubMed

Fortuin, Janna; van Geel, Mitch; Vedder, Paul

2015-04-01

Adolescents who like each other may become more similar to each other with regard to internalizing and externalizing problems, though it is not yet clear which social mechanisms explain these similarities. In this longitudinal study, we analyzed four mechanisms that may explain similarity in adolescent peer networks with regard to externalizing and internalizing problems: selection, socialization, avoidance and withdrawal. At three moments during one school-year, we asked 542 adolescents (8th grade, M-age = 13.3 years, 51 % female) to report who they liked in their classroom, and their own internalizing and externalizing problems. Adolescents tend to prefer peers who have similar externalizing problem scores, but no significant selection effect was found for internalizing problems. Adolescents who share the same group of friends socialize each other and then become more similar with respect to externalizing problems, but not with respect to internalizing problems. We found no significant effects for avoidance or withdrawal. Adolescents may choose to belong to a peer group that is similar to them in terms of externalizing problem behaviors, and through peer group socialization (e.g., enticing, modelling, mimicking, and peer pressure) become more similar to that group over time.

Online Formative Assessments with Social Network Awareness

ERIC Educational Resources Information Center

Lin, Jian-Wei; Lai, Yuan-Cheng

2013-01-01

Social network awareness (SNA) has been used extensively as one of the strategies to increase knowledge sharing and collaboration opportunities. However, most SNA studies either focus on being aware of peer's knowledge context or on social context. This work proposes online formative assessments with SNA, trying to address the problems of online…

Managing Digital Learning Environments: Student Teachers' Perception on the Social Networking Services Use in Writing Courses in Teacher Education

ERIC Educational Resources Information Center

Prasojo, Lantip Diat; Habibi, Akhmad; Mukminin, Amirul; Muhaimin; Taridi, Muhammad; Ikhsan; Saudagar, Ferdiaz

2017-01-01

Limited studies have been conducted to examine how effective and what impacts dealing with students' learning experiences as well as the problems faced by the students. This study focused on English student teachers' experiences on the advantages and problems faced in using Social Networking Services (SNS) in English as Foreign Language (EFL)…

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

PubMed

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

2012-06-28

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

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

PubMed Central

2012-01-01

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

Embedded Efficiency: A Social Networks Approach to Popular Support and Dark Network Structure

DTIC Science & Technology

2016-03-01

Raab in “Dark networks as problems ,” (2003) where dark refers to illegal and, covert and bright refers to legal and overt. Throughout this report these...Milward, Jörg Raab, “Dark Networks as Organizational Problems : Elements of a Theory,” International Public Management Journal 9, no.3 ( 2006): 333–360...Emirbayer and Jeff Goodwin, “Network Analysis, Culture and the Problem of Agency,” American Journal of Sociology Vol. 99, No. 6 (May 1994): 1436. 35 Ibid

Age Moderates the Relationship between Social Support and Psychosocial Problems.

ERIC Educational Resources Information Center

Segrin, Chris

2003-01-01

Examines the association between social support from various sources and psychosocial problems, and how these associations vary over the life span. Finds that perceived social support and contact with social network members appears to have beneficial effects for all participants, as evidenced through reduced symptoms of depression and loneliness.…

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-08-03

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

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.

Online social networks—Paradise of computer viruses

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2011-01-01

Online social network services have attracted more and more users in recent years. So the security of social networks becomes a critical problem. In this paper, we propose a virus propagation model based on the application network of Facebook, which is the most popular among these social network service providers. We also study the virus propagation with an email virus model and compare the behaviors of a virus spreading on Facebook with the original email network. It is found that Facebook provides the same chance for a virus spreading while it gives a platform for application developers. And a virus will spread faster in the Facebook network if users of Facebook spend more time on it.

Influencing Busy People in a Social Network

PubMed Central

Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach. PMID:27711127

Influencing Busy People in a Social Network.

PubMed

Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach.

Networked Community Change: Understanding Community Systems Change through the Lens of Social Network Analysis.

PubMed

Lawlor, Jennifer A; Neal, Zachary P

2016-06-01

Addressing complex problems in communities has become a key area of focus in recent years (Kania & Kramer, 2013, Stanford Social Innovation Review). Building on existing approaches to understanding and addressing problems, such as action research, several new approaches have emerged that shift the way communities solve problems (e.g., Burns, 2007, Systemic Action Research; Foth, 2006, Action Research, 4, 205; Kania & Kramer, 2011, Stanford Social Innovation Review, 1, 36). Seeking to bring clarity to the emerging literature on community change strategies, this article identifies the common features of the most widespread community change strategies and explores the conditions under which such strategies have the potential to be effective. We identify and describe five common features among the approaches to change. Then, using an agent-based model, we simulate network-building behavior among stakeholders participating in community change efforts using these approaches. We find that the emergent stakeholder networks are efficient when the processes are implemented under ideal conditions. © Society for Community Research and Action 2016.

A Promising Practice: Using Facebook as a Communication and Social Networking Tool

ERIC Educational Resources Information Center

Schultz, Susan M.; Jacobs, Gloria; Schultz, Jacob

2013-01-01

Individuals with autism often face barriers to social interaction. Residing in a rural environment can compound these difficulties for individuals diagnosed with autism. Some of the reasons include transportation problems and small social networks, in addition to the characteristics of autism. This article discusses a promising practice for…

Cost effectiveness of treatment for alcohol problems: findings of the randomised UK alcohol treatment trial (UKATT).

PubMed

2005-09-10

To compare the cost effectiveness of social behaviour and network therapy, a new treatment for alcohol problems, with that of the proved motivational enhancement therapy. Cost effectiveness analysis alongside a pragmatic randomised trial. Seven treatment sites around Birmingham, Cardiff, and Leeds. 742 clients with alcohol problems; 617 (83.2%) were interviewed at 12 months and full economic data were obtained on 608 (98.5% of 617). Main economic measures Quality adjusted life years (QALYs), costs of trial treatments, and consequences for public sector resources (health care, other alcohol treatment, social services, and criminal justice services). Both therapies saved about five times as much in expenditure on health, social, and criminal justice services as they cost. Neither net savings nor cost effectiveness differed significantly between the therapies, despite the average cost of social behaviour and network therapy (221 pounds sterling; 385 dollars; 320 euros) being significantly more than that of motivational enhancement therapy (129 pounds sterling). If a QALY were worth 30,000 pounds sterling, then the motivational therapy would have 58% chance of being more cost effective than the social therapy, and the social therapy would have 42% chance of being more cost effective than the motivational therapy. Participants reported highly significant reductions in drinking and associated problems and costs. The novel social behaviour and network therapy did not differ significantly in cost effectiveness from the proved motivational enhancement therapy.

Lesion mapping of social problem solving.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H

2014-10-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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

PubMed

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

2015-11-11

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

Interdisciplinary Matchmaking: Choosing Collaborators by Skill, Acquaintance and Trust

NASA Astrophysics Data System (ADS)

Hupa, Albert; Rzadca, Krzysztof; Wierzbicki, Adam; Datta, Anwitaman

Social networks are commonly used to enhance recommender systems. Most of such systems recommend a single resource or a person. However, complex problems or projects usually require a team of experts that must work together on a solution. Team recommendation is much more challenging, mostly because of the complex interpersonal relations between members. This chapter presents fundamental concepts on how to score a team based on members' social context and their suitability for a particular project. We represent the social context of an individual as a three-dimensional social network (3DSN) composed of a knowledge dimension expressing skills, a trust dimension and an acquaintance dimension. Dimensions of a 3DSN are used to mathematically formalize the criteria for prediction of the team's performance. We use these criteria to formulate the team recommendation problem as a multi-criteria optimization problem. We demonstrate our approach on empirical data crawled from two web2.0 sites: onephoto.net and a social networking site. We construct 3DSNs and analyze properties of team's performance criteria.

Dynamic node immunization for restraint of harmful information diffusion in social networks

NASA Astrophysics Data System (ADS)

Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

2018-08-01

To restrain the spread of harmful information is crucial for the healthy and sustainable development of social networks. We address the problem of restraining the spread of harmful information by immunizing nodes in the networks. Previous works have developed methods based on the network topology or studied how to immunize nodes in the presence of initial infected nodes. These static methods, in which nodes are immunized at once, may have poor performance in the certain situation due to the dynamics of diffusion. To tackle this problem, we introduce a new dynamic immunization problem of immunizing nodes during the process of the diffusion in this paper. We formulate the problem and propose a novel heuristic algorithm by dealing with two sub-problems: (1) how to select a node to achieve the best immunization effect at the present time? (2) whether the selected node should be immunized right now? Finally, we demonstrate the effectiveness of our algorithm through extensive experiments on various real datasets.

Interactions among human behavior, social networks, and societal infrastructures: A Case Study in Computational Epidemiology

NASA Astrophysics Data System (ADS)

Barrett, Christopher L.; Bisset, Keith; Chen, Jiangzhuo; Eubank, Stephen; Lewis, Bryan; Kumar, V. S. Anil; Marathe, Madhav V.; Mortveit, Henning S.

Human behavior, social networks, and the civil infrastructures are closely intertwined. Understanding their co-evolution is critical for designing public policies and decision support for disaster planning. For example, human behaviors and day to day activities of individuals create dense social interactions that are characteristic of modern urban societies. These dense social networks provide a perfect fabric for fast, uncontrolled disease propagation. Conversely, people’s behavior in response to public policies and their perception of how the crisis is unfolding as a result of disease outbreak can dramatically alter the normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. In this chapter, we describe a computer simulation based approach to study these issues using public health and computational epidemiology as an illustrative example. We also formulate game-theoretic and stochastic optimization problems that capture many of the problems that we study empirically.

Something Old, Not Much New, and a Lot Borrowed: Philanthropy, Business, and the Changing Roles of Government in Global Education Policy Networks

ERIC Educational Resources Information Center

Olmedo, Antonio

2017-01-01

This paper focuses on the role of governments in contemporary networked political configurations. Such networks constitute policy communities, usually based upon shared conceptions of social problems and their solutions. By enabling social, political, and economic connections at local, regional, national, and international levels, such networks…

Measures of node centrality in mobile social networks

NASA Astrophysics Data System (ADS)

Gao, Zhenxiang; Shi, Yan; Chen, Shanzhi

2015-02-01

Mobile social networks exploit human mobility and consequent device-to-device contact to opportunistically create data paths over time. While links in mobile social networks are time-varied and strongly impacted by human mobility, discovering influential nodes is one of the important issues for efficient information propagation in mobile social networks. Although traditional centrality definitions give metrics to identify the nodes with central positions in static binary networks, they cannot effectively identify the influential nodes for information propagation in mobile social networks. In this paper, we address the problems of discovering the influential nodes in mobile social networks. We first use the temporal evolution graph model which can more accurately capture the topology dynamics of the mobile social network over time. Based on the model, we explore human social relations and mobility patterns to redefine three common centrality metrics: degree centrality, closeness centrality and betweenness centrality. We then employ empirical traces to evaluate the benefits of the proposed centrality metrics, and discuss the predictability of nodes' global centrality ranking by nodes' local centrality ranking. Results demonstrate the efficiency of the proposed centrality metrics.

Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits.

PubMed

Hormes, Julia M; Kearns, Brianna; Timko, C Alix

2014-12-01

To assess disordered online social networking use via modified diagnostic criteria for substance dependence, and to examine its association with difficulties with emotion regulation and substance use. Cross-sectional survey study targeting undergraduate students. Associations between disordered online social networking use, internet addiction, deficits in emotion regulation and alcohol use problems were examined using univariate and multivariate analyses of covariance. A large University in the Northeastern United States. Undergraduate students (n = 253, 62.8% female, 60.9% white, age mean = 19.68, standard deviation = 2.85), largely representative of the target population. The response rate was 100%. Disordered online social networking use, determined via modified measures of alcohol abuse and dependence, including DSM-IV-TR diagnostic criteria for alcohol dependence, the Penn Alcohol Craving Scale and the Cut-down, Annoyed, Guilt, Eye-opener (CAGE) screen, along with the Young Internet Addiction Test, Alcohol Use Disorders Identification Test, Acceptance and Action Questionnaire-II, White Bear Suppression Inventory and Difficulties in Emotion Regulation Scale. Disordered online social networking use was present in 9.7% [n = 23; 95% confidence interval (5.9, 13.4)] of the sample surveyed, and significantly and positively associated with scores on the Young Internet Addiction Test (P < 0.001), greater difficulties with emotion regulation (P = 0.003) and problem drinking (P = 0.03). The use of online social networking sites is potentially addictive. Modified measures of substance abuse and dependence are suitable in assessing disordered online social networking use. Disordered online social networking use seems to arise as part of a cluster of symptoms of poor emotion regulation skills and heightened susceptibility to both substance and non-substance addiction. © 2014 Society for the Study of Addiction.

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.

[Gender differences in the social relations of students].

PubMed

Bak, Nanna Hasle; Petersson, Birgit H; Dissing, Agnete Skovlund; Pedersen, Laura Toftegaard

2010-07-19

The aim of this study is to study gender differences in social network and social support among university students with a special view to social relations as a coping strategy for dealing with personal problems. A total of 1,126 (48%) medical, psychology and liberal arts students who initiated their studies in 2006 or 2007 participated in the study. Data derives from a student register and a questionnaire on social network and social support. Approximately 85% of the students visit friends weekly, and about 40% spend time with their family weekly. Nearly half of the students have a partner. More female than male medical students have a partner when initiating their studies. More than 80% of the students have experienced mental health or social problems in the past, more female than male medical and liberal arts students. More than half of the male students handle their personal problems by themselves, whereas female students receive more social support. Significant gender differences in social support are mostly found among medical and liberal arts students. The results suggest that male and female students use different coping strategies when dealing with social and mental health problems, and gender differences in social relations seem to be most widespread among medical and liberal arts students - why and how should be investigated further.

The effect of social networks and social support on common mental disorders following specific life events.

PubMed

Maulik, P K; Eaton, W W; Bradshaw, C P

2010-08-01

This study examined the association between life events and common mental disorders while accounting for social networks and social supports. Participants included 1920 adults in the Baltimore Epidemiologic Catchment Area Cohort who were interviewed in 1993-1996, of whom 1071 were re-interviewed in 2004-2005. Generalized estimating equations were used to analyze the data. Social support from friends, spouse or relatives was associated with significantly reduced odds of panic disorder and psychological distress, after experiencing specific life events. Social networks or social support had no significant stress-buffering effect. Social networks and social support had almost no direct or buffering effect on major depressive disorder, and no effect on generalized anxiety disorder and alcohol abuse or dependence disorder. The significant association between social support and psychological distress, rather than diagnosable mental disorders, highlights the importance of social support, especially when the severity of a mental health related problem is low.

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

PubMed Central

Reafee, Waleed; Salim, Naomie; Khan, Atif

2016-01-01

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

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

Social Networking Sites and Addiction: Ten Lessons Learned

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2017-01-01

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided. PMID:28304359

Social Networking Sites and Addiction: Ten Lessons Learned.

PubMed

Kuss, Daria J; Griffiths, Mark D

2017-03-17

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.

Social networking sites and older users - a systematic review.

PubMed

Nef, Tobias; Ganea, Raluca L; Müri, René M; Mosimann, Urs P

2013-07-01

Social networking sites can be beneficial for senior citizens to promote social participation and to enhance intergenerational communication. Particularly for older adults with impaired mobility, social networking sites can help them to connect with family members and other active social networking users. The aim of this systematic review is to give an overview of existing scientific literature on social networking in older users. Computerized databases were searched and 105 articles were identified and screened using exclusion criteria. After exclusion of 87 articles, 18 articles were included, reviewed, classified, and the key findings were extracted. Common findings are identified and critically discussed and possible future research directions are outlined. The main benefit of using social networking sites for older adults is to enter in an intergenerational communication with younger family members (children and grandchildren) that is appreciated by both sides. Identified barriers are privacy concerns, technical difficulties and the fact that current Web design does not take the needs of older users into account. Under the conditions that these problems are carefully addressed, social networking sites have the potential to support today's and tomorrow's communication between older and younger family members.

The moderating role of social networks in the relationship between alcohol consumption and treatment utilization for alcohol-related problems

PubMed Central

Mowbray, Orion

2014-01-01

Many individuals wait until alcohol use becomes severe before treatment is sought. However, social networks, or the number of social groups an individual belongs to, may play a moderating role in this relationship. Logistic regression examined the interaction of alcohol consumption and social networks as a predictor of treatment utilization while adjusting for sociodemographic and clinical variables among 1,433 lifetime alcohol-dependent respondents from wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC). Results showed that social networks moderate the relationship between alcohol consumption and treatment utilization such that for individuals with few network ties, the relationship between alcohol consumption and treatment utilization was diminished, compared to the relationship between alcohol consumption and treatment utilization for individuals with many network ties. Findings offer insight into how social networks, at times, can influence individuals to pursue treatment, while at other times, influence individuals to stay out of treatment, or seek treatment substitutes. PMID:24462223

Multi-Agent Inference in Social Networks: A Finite Population Learning Approach.

PubMed

Fan, Jianqing; Tong, Xin; Zeng, Yao

When people in a society want to make inference about some parameter, each person may want to use data collected by other people. Information (data) exchange in social networks is usually costly, so to make reliable statistical decisions, people need to trade off the benefits and costs of information acquisition. Conflicts of interests and coordination problems will arise in the process. Classical statistics does not consider people's incentives and interactions in the data collection process. To address this imperfection, this work explores multi-agent Bayesian inference problems with a game theoretic social network model. Motivated by our interest in aggregate inference at the societal level, we propose a new concept, finite population learning , to address whether with high probability, a large fraction of people in a given finite population network can make "good" inference. Serving as a foundation, this concept enables us to study the long run trend of aggregate inference quality as population grows.

Social Trust Prediction Using Heterogeneous Networks

PubMed Central

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

2014-01-01

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

Social Trust Prediction Using Heterogeneous Networks.

PubMed

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

2013-11-01

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

Information and Communications Technologies (ICT): Problematic use of Internet, video games, mobile phones, instant messaging and social networks using MULTICAGE-TIC.

PubMed

Pedrero Pérez, Eduardo J; Ruiz Sánchez de León, José María; Rojo Mota, Gloria; Llanero Luque, Marcos; Pedrero Aguilar, Jara; Morales Alonso, Sara; Puerta García, Carmen

2018-01-01

Use/abuse of Information and Communications Technologies (ICT) has in recent years become a topic of great interest. Current discussion addresses whether it must be considered addictive behaviour and if it is a problem that primarily affects adolescents and youth. This study aims to understand the problems that affect people of all ages in controlling the use of these ICTs and whether they are related to mental health problems, stress and difficulties in executive control of behaviour. A survey was administered through social networks and email, using the MULTICAGE-ICT, a questionnaire that explores problems in the use of Internet, mobile phones, video games, instant messaging and social networks. Additionally, the Prefrontal Symptom Inventory, General Health Questionnaire and Perceived Stress Scale were administered. The sample was comprised of 1,276 individuals of all ages from different Spanish-speaking countries. The results indicate that about 50% of the sample, regardless of age or other variables, presents significant problems with the use of these technologies, and that these problems are directly related to symptoms of poor prefrontal functioning, stress and mental health problems. The results reveal the need for reconsidering whether we are facing an addictive behaviour or a new problem demanding environmental, psychological, sociological and sociopolitical explanations; therefore, it is necessary to reformulate actions to be implemented to address and refocus our understanding of the problem.

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.

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

PubMed Central

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

2010-01-01

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

Social Network 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…

A Descriptive Study of the Prevalence and Typology of Alcohol-Related Posts in an Online Social Network for Smoking Cessation.

PubMed

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

2017-09-01

Alcohol use and problem drinking are associated with smoking relapse and poor smoking-cessation success. User-generated content in online social networks for smoking cessation provides an opportunity to understand the challenges and treatment needs of smokers. This study used machine-learning text classification to identify the prevalence, sentiment, and social network correlates of alcohol-related content in the social network of a large online smoking-cessation program, BecomeAnEX.org. Data were analyzed from 814,258 posts (January 2012 to May 2015). Posts containing alcohol keywords were coded via supervised machine-learning text classification for information about the user's personal experience with drinking, whether the user self-identified as a problem drinker or indicated problem drinking, and negative sentiment about drinking in the context of a quit attempt (i.e., alcohol should be avoided during a quit attempt). Less than 1% of posts were related to alcohol, contributed by 13% of users. Roughly a third of alcohol posts described a personal experience with drinking; very few (3%) indicated "problem drinking." The majority (70%) of alcohol posts did not express negative sentiment about drinking alcohol during a quit attempt. Users who did express negative sentiment about drinking were more centrally located within the network compared with those who did not. Discussion of alcohol was rare, and most posts did not signal the need to quit or abstain from drinking during a quit attempt. Featuring expert information or highlighting discussions that are consistent with treatment guidelines may be important steps to ensure smokers are educated about drinking risks.

Algorithm research for user trajectory matching across social media networks based on paragraph2vec

NASA Astrophysics Data System (ADS)

Xu, Qian; Chen, Hongchang; Zhi, Hongxin; Wang, Yanchuan

2018-04-01

Identifying users across different social media networks (SMN) is to link accounts of the same user that belong to the same individual across SMNs. The problem is fundamental and important, and its results can benefit many applications such as cross SMN user modeling and recommendation. With the development of GPS technology and mobile communication, more and more social networks provide location services. This provides a new opportunity for cross SMN user identification. In this paper, we solve cross SMN user identification problem in an unsupervised manner by utilizing user trajectory data in SMNs. A paragraph2vec based algorithm is proposed in which location sequence feature of user trajectory is captured in temporal and spatial dimensions. Our experimental results validate the effectiveness and efficiency of our algorithm.

Symposium Connects Government Problems with State of the Art Network Science Research

DTIC Science & Technology

2015-10-16

Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering

Identifying influential user communities on the social network

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Social Networks and the Diffusion of Adolescent Problem Behavior: Reliable Estimates of Selection and Influence from Sixth Through Ninth Grades.

PubMed

Osgood, D Wayne; Feinberg, Mark E; Ragan, Daniel T

2015-08-01

Seeking to reduce problematic peer influence is a prominent theme of programs to prevent adolescent problem behavior. To support the refinement of this aspect of prevention programming, we examined peer influence and selection processes for three problem behaviors (delinquency, alcohol use, and smoking). We assessed not only the overall strengths of these peer processes, but also their consistency versus variability across settings. We used dynamic stochastic actor-based models to analyze five waves of friendship network data across sixth through ninth grades for a large sample of U.S. adolescents. Our sample included two successive grade cohorts of youth in 26 school districts participating in the PROSPER study, yielding 51 longitudinal social networks based on respondents' friendship nominations. For all three self-reported antisocial behaviors, we found evidence of both peer influence and selection processes tied to antisocial behavior. There was little reliable variance in these processes across the networks, suggesting that the statistical imprecision of the peer influence and selection estimates in previous studies likely accounts for inconsistencies in results. Adolescent friendship networks play a strong role in shaping problem behavior, but problem behaviors also inform friendship choices. In addition to preferring friends with similar levels of problem behavior, adolescents tend to choose friends who engage in problem behaviors, thus creating broader diffusion.

Social Networks and the Diffusion of Adolescent Problem Behavior: Reliable Estimates of Selection and Influence from 6th through 9th Grade

PubMed Central

Osgood, D. Wayne; Feinberg, Mark E.; Ragan, Daniel T.

2015-01-01

Seeking to reduce problematic peer influence is a prominent theme of programs to prevent adolescent problem behavior. To support the refinement of this aspect of prevention programming, we examined peer influence and selection processes for three problem behaviors (delinquency, alcohol use, and smoking). We assessed not only the overall strengths of these peer processes, but also their consistency versus variability across settings. We used dynamic stochastic actor-based models to analyze five waves of friendship network data across sixth through ninth grades for a large sample of U.S. adolescents. Our sample included two successive grade cohorts of youth in 26 school districts participating in the PROSPER study, yielding 51 longitudinal social networks based on respondents’ friendship nominations. For all three self-reported antisocial behaviors, we found evidence of both peer influence and selection processes tied to antisocial behavior. There was little reliable variance in these processes across the networks, suggesting that the statistical imprecision of the peer influence and selection estimates in previous studies likely accounts for inconsistencies in results. Adolescent friendship networks play a strong role in shaping problem behavior, but problem behaviors also inform friendship choices. In addition to preferring friends with similar levels of problem behavior, adolescents tend to choose friends who engage in problem behaviors, thus creating broader diffusion. PMID:25943034

Information Overload and Viral Marketing: Countermeasures and Strategies

NASA Astrophysics Data System (ADS)

Cheng, Jiesi; Sun, Aaron; Zeng, Daniel

Studying information diffusion through social networks has become an active research topic with important implications in viral marketing applications. One of the fundamental algorithmic problems related to viral marketing is the Influence Maximization (IM) problem: given an social network, which set of nodes should be considered by the viral marketer as the initial targets, in order to maximize the influence of the advertising message. In this work, we study the IM problem in an information-overloaded online social network. Information overload occurs when individuals receive more information than they can process, which can cause negative impacts on the overall marketing effectiveness. Many practical countermeasures have been proposed for alleviating the load of information on recipients. However, how these approaches can benefit viral marketers is not well understood. In our work, we have adapted the classic Information Cascade Model to incorporate information overload and study its countermeasures. Our results suggest that effective control of information overload has the potential to improve marketing effectiveness, but the targeting strategy should be re-designed in response to these countermeasures.

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.

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

PubMed

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

2016-12-01

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

Social 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.

The relation between social network site usage and loneliness and mental health in community-dwelling older adults.

PubMed

Aarts, S; Peek, S T M; Wouters, E J M

2015-09-01

Loneliness is expected to become an even bigger social problem in the upcoming decades, because of the growing number of older adults. It has been argued that the use of social network sites can aid in decreasing loneliness and improving mental health. The purpose of this study was to examine whether and how social network sites usage is related to loneliness and mental health in community-dwelling older adults. The study population included community-dwelling older adults aged 60 and over residing in the Netherlands (n = 626) collected through the LISS panel (www.lissdata.nl). Univariate and multivariate linear regression analyses, adjusted for potentially important confounders, were conducted in order to investigate the relation between social network sites usage and (emotional and social) loneliness and mental health. More than half of the individuals (56.2%) reported to use social network sites at least several times per week. Social network sites usage appeared unrelated to loneliness in general, and to emotional and social loneliness in particular. Social network sites usage also appeared unrelated to mental health. Several significant associations between related factors and the outcomes at hand were detected. In this sample, which was representative for the Dutch population, social network sites usage was unrelated to loneliness and/or mental health. The results indicate that a simple association between social network site usage and loneliness and mental health as such, cannot automatically be assumed in community-dwelling older adults. Copyright © 2014 John Wiley & Sons, Ltd.

Post-conflict struggles as networks of problems: A network analysis of trauma, daily stressors and psychological distress among Sri Lankan war survivors.

PubMed

Jayawickreme, Nuwan; Mootoo, Candace; Fountain, Christine; Rasmussen, Andrew; Jayawickreme, Eranda; Bertuccio, Rebecca F

2017-10-01

A growing body of literature indicates that the mental distress experienced by survivors of war is a function of both experienced trauma and stressful life events. However, the majority of these studies are limited in that they 1) employ models of psychological distress that emphasize underlying latent constructs and do not allow researchers to examine the unique associations between particular symptoms and various stressors; and 2) use one or more measures that were not developed for that particular context and thus may exclude key traumas, stressful life events and symptoms of psychopathology. The current study addresses both these limitations by 1) using a novel conceptual model, network analysis, which assumes that symptoms covary with each other not because they stem from a latent construct, but rather because they represent meaningful relationships between the symptoms; and 2) employing a locally developed measure of experienced trauma, stressful life problems and symptoms of psychopathology. Over the course of 2009-2011, 337 survivors of the Sri Lankan civil war were administered the Penn-RESIST-Peradeniya War Problems Questionnaire (PRPWPQ). Network analysis revealed that symptoms of psychopathology, problems pertaining to lack of basic needs, and social problems were central to the network relative to experienced trauma and other types of problems. After controlling for shared associations, social problems in particular were the most central, significantly more so than traumatic events and family problems. Several particular traumatic events, stressful life events and symptoms of psychopathology that were central to the network were also identified. Discussion emphasizes the utility of such network models to researchers and practitioners determining how to spend limited resources in the most impactful way possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2010-01-01

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

Learning to Predict Social Influence in Complex Networks

DTIC Science & Technology

2012-03-29

03/2010 – 17/03/2012 Abstract: First, we addressed the problem of analyzing information diffusion process in a social network using two kinds...algorithm which avoids the inner loop optimization during the search. We tested the performance using the structures of four real world networks, and...result of information diffusion that starts from the node. 2 We use “infected” and “activated” interchangeably. Efficient Discovery of Influential

Equal Graph Partitioning on Estimated Infection Network as an Effective Epidemic Mitigation Measure

PubMed Central

Hadidjojo, Jeremy; Cheong, Siew Ann

2011-01-01

Controlling severe outbreaks remains the most important problem in infectious disease area. With time, this problem will only become more severe as population density in urban centers grows. Social interactions play a very important role in determining how infectious diseases spread, and organization of people along social lines gives rise to non-spatial networks in which the infections spread. Infection networks are different for diseases with different transmission modes, but are likely to be identical or highly similar for diseases that spread the same way. Hence, infection networks estimated from common infections can be useful to contain epidemics of a more severe disease with the same transmission mode. Here we present a proof-of-concept study demonstrating the effectiveness of epidemic mitigation based on such estimated infection networks. We first generate artificial social networks of different sizes and average degrees, but with roughly the same clustering characteristic. We then start SIR epidemics on these networks, censor the simulated incidences, and use them to reconstruct the infection network. We then efficiently fragment the estimated network by removing the smallest number of nodes identified by a graph partitioning algorithm. Finally, we demonstrate the effectiveness of this targeted strategy, by comparing it against traditional untargeted strategies, in slowing down and reducing the size of advancing epidemics. PMID:21799777

Tractable Analysis for Large Social Networks

ERIC Educational Resources Information Center

Zhang, Bin

2012-01-01

Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

Social Dynamics within Electronic Networks of Practice

ERIC Educational Resources Information Center

Mattson, Thomas A., Jr.

2013-01-01

Electronic networks of practice (eNoP) are special types of electronic social structures focused on discussing domain-specific problems related to a skill-based craft or profession in question and answer style forums. eNoP have implemented peer-to-peer feedback systems in order to motivate future contributions and to distinguish contribution…

Assessing Middle School Students' Knowledge of Conduct and Consequences and Their Behaviors regarding the Use of Social Networking Sites

ERIC Educational Resources Information Center

Kite, Stacey L.; Gable, Robert; Filippelli, Lawrence

2010-01-01

Cyberbullying and threats of Internet predators, not to mention the enduring consequences of postings, may lead to dangerous, unspeakable consequences. Cyberbullying and threats of Internet predators through social networking sites and instant messaging programs are initiating numerous problems for parents, school administrators, and law…

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.

Social inclusion and relationship satisfaction of patients with a severe mental illness.

PubMed

Koenders, Jitske F; de Mooij, Liselotte D; Dekker, Jack M; Kikkert, Martijn

2017-12-01

Research suggests that patients with a severe mental illness (SMI) are among the most social excluded in society. However, comparisons of social network composition and relationship satisfaction between SMI patients and a control group are rare. Our aim was to compare differences in size, satisfaction and composition of the social network between patients with SMI and a control group. Potential sociodemographic and clinical risk factors in relation to social network size in SMI patients were explored. The sample consisted of a control group ( N = 949) and SMI patients ( N = 211) who were under treatment in Dutch mental health care institutions. In these groups, network size, relationship satisfaction, sociodemographic and clinical (patients only) characteristics were assessed. Social network size was 2.5 times lower in SMI patients, which was also reflected in a lower relationship satisfaction. The composition of the social network of SMI patients differs from that of controls: patients' network seems to consist of a smaller part of friends. Different risk factors were associated with the impoverishment of the social network of family, friends and acquaintances of patients with SMI. SMI patients have very small networks compared to controls. This may be a problem, given the ongoing emphasis on outpatient treatment of SMI patients and self-dependence. This outcome advocates for more attention to social isolation of SMI patients and involvement of family in the treatment and aftercare of SMI patients.

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

PubMed

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

2017-05-01

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

Gender differences in the association of perceived social support and social network with self-rated health status among older adults: a population-based study in Brazil

PubMed Central

2013-01-01

Background Older adults are more likely to live alone, because they may have been predeceased by their spouse and friends. Social interaction could also be reduced in this age group due by limited mobility caused by chronic conditions. Therefore, aging is frequently accompanied by reduced social support, which might affect health status. Little is known about the role of gender in the relationship between social support and health in older adults. Hence, the present study tests the hypothesis that gender differences exist in the relationship between perceived social support, social network, and self-rated health (SRH) among older adults. Methods A cross-sectional study using two-stage probabilistic sampling recruited 3,649 individuals aged 60 years and above. Data were collected during the national influenza vaccination campaign in Rio de Janeiro, Brazil, in 2006. Individual interviews collected information on SRH, perceived social support, social network, and other covariates. Multivariate logistic regression analyses using nested models were conducted separately for males and females. Independent variables were organised into six blocks: (1) perceived social support and social network, (2) age group, (3) socioeconomic characteristics, (4) health-related behaviours, (5) use of health care services, (6) functional status measures and somatic health problems. Results Older men who did not participate in group activities were more likely to report poor SRH compared to those who did, (OR = 1.63; 95% CI = 1.16–2.30). Low perceived social support predicted the probability of poor SRH in women (OR = 1.64; 95% CI = 1.16–2.34). Poor SRH was associated with low age, low income, not working, poor functional capacity, and depression in both men and women. More somatic health problems were associated with poor SRH in women. Conclusions The association between social interactions and SRH varies between genders. Low social network involvement is associated with poor SRH in older men, whereas low perceived social support is associated with poor SRH in older women. The hypothesis that the relationship of perceived social support and social networks to SRH differs according to gender has been confirmed. PMID:24229389

Gender differences in the association of perceived social support and social network with self-rated health status among older adults: a population-based study in Brazil.

PubMed

Caetano, Silvana C; Silva, Cosme M F P; Vettore, Mario V

2013-11-15

Older adults are more likely to live alone, because they may have been predeceased by their spouse and friends. Social interaction could also be reduced in this age group due by limited mobility caused by chronic conditions. Therefore, aging is frequently accompanied by reduced social support, which might affect health status. Little is known about the role of gender in the relationship between social support and health in older adults. Hence, the present study tests the hypothesis that gender differences exist in the relationship between perceived social support, social network, and self-rated health (SRH) among older adults. A cross-sectional study using two-stage probabilistic sampling recruited 3,649 individuals aged 60 years and above. Data were collected during the national influenza vaccination campaign in Rio de Janeiro, Brazil, in 2006. Individual interviews collected information on SRH, perceived social support, social network, and other covariates. Multivariate logistic regression analyses using nested models were conducted separately for males and females. Independent variables were organised into six blocks: (1) perceived social support and social network, (2) age group, (3) socioeconomic characteristics, (4) health-related behaviours, (5) use of health care services, (6) functional status measures and somatic health problems. Older men who did not participate in group activities were more likely to report poor SRH compared to those who did, (OR = 1.63; 95% CI = 1.16-2.30). Low perceived social support predicted the probability of poor SRH in women (OR = 1.64; 95% CI = 1.16-2.34). Poor SRH was associated with low age, low income, not working, poor functional capacity, and depression in both men and women. More somatic health problems were associated with poor SRH in women. The association between social interactions and SRH varies between genders. Low social network involvement is associated with poor SRH in older men, whereas low perceived social support is associated with poor SRH in older women. The hypothesis that the relationship of perceived social support and social networks to SRH differs according to gender has been confirmed.

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

Emergence of communities and diversity in social networks

PubMed Central

Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross

2017-01-01

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics. PMID:28235785

Emergence of communities and diversity in social networks.

PubMed

Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene

2017-03-14

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.

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.

An Inside Look at Homeless Youths’ Social Networks: Perceptions of Substance Use Norms1

PubMed Central

Melander, Lisa A.; Tyler, Kimberly A.; Schmitz, Rachel M.

2016-01-01

Substance use among homeless young people is a pervasive problem, and there have been many efforts to understand more about the dynamics of this health compromising behavior. The current study examined perceived substance use norms within homeless youths’ social networks utilizing in-depth interviews. The sample included 19 homeless individuals aged 16 to 21. Four elements of substance use within networks emerged: substance use choices, drug use safety issues, encouragement and/or discouragement, and appropriate situations in which substance use is condoned. These findings provide unique insight into the norms associated with drug and alcohol use within homeless youths’ social networks. PMID:26989340

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.

[Boundaries and integrity in the "Social Contract for Spanish Science", 1907-1939].

PubMed

Gómez, Amparo

2014-01-01

This article analyzes the relationship between science and politics in Spain in the early 20th century from the perspective of the Social Contract for Science. The article shows that a genuine social contract for science was instituted in Spain during this period, although some boundary and integrity problems emerged. These problems are analyzed, showing that the boundary problems were a product of the conservative viewpoint on the relationship between science and politics, while the integrity problems involved the activation of networks of influence in the awarding of scholarships to study abroad. Finally, the analysis reveals that these problems did not invalidate the Spanish social contract for science.

Social network and census tract-level influences on substance use among emerging adult males: An activity spaces approach

PubMed Central

Gibson, Crystal; Perley, Lauren; Bailey, Jonathan; Barbour, Russell; Kershaw, Trace

2015-01-01

Social network and area level characteristics have been linked to substance use. We used snowball sampling to recruit 90 predominantly African American emerging adult men who provided typical locations visited (n=510). We used generalized estimating equations to examine social network and area level predictors of substance use. Lower social network quality was associated with days of marijuana use (B=-0.0037, p<0.0001) and problem alcohol use (B=-0.0050, p=0.0181). The influence of area characteristics on substance use differed between risky and non-risky spaces. Peer and area influences are important for substance use among men, and may differ for high and low risk places. PMID:26176810

Why Are Some More Peer Than Others? Evidence from a Longitudinal Study of Social Networks and Individual Academic Performance

PubMed Central

Lomi, Alessandro; Snijders, Tom A.B.; Steglich, Christian E.G.; Torlo, Vanina Jasmine

2014-01-01

Studies of peer effects in educational settings confront two main problems. The first is the presence of endogenous sorting which confounds the effects of social influence and social selection on individual attainment. The second is how to account for the local network dependencies through which peer effects influence individual behavior. We empirically address these problems using longitudinal data on academic performance, friendship, and advice seeking relations among students in a full-time graduate academic program. We specify stochastic agent-based models that permit estimation of the interdependent contribution of social selection and social influence to individual performance. We report evidence of peer effects. Students tend to assimilate the average performance of their friends and of their advisors. At the same time, students attaining similar levels of academic performance are more likely to develop friendship and advice ties. Together, these results imply that processes of social influence and social selection are sub-components of a more general a co-evolutionary process linking network structure and individual behavior. We discuss possible points of contact between our findings and current research in the economics and sociology of education. PMID:25641999

Why Are Some More Peer Than Others? Evidence from a Longitudinal Study of Social Networks and Individual Academic Performance.

PubMed

Lomi, Alessandro; Snijders, Tom A B; Steglich, Christian E G; Torlo, Vanina Jasmine

2011-11-01

Studies of peer effects in educational settings confront two main problems. The first is the presence of endogenous sorting which confounds the effects of social influence and social selection on individual attainment. The second is how to account for the local network dependencies through which peer effects influence individual behavior. We empirically address these problems using longitudinal data on academic performance, friendship, and advice seeking relations among students in a full-time graduate academic program. We specify stochastic agent-based models that permit estimation of the interdependent contribution of social selection and social influence to individual performance. We report evidence of peer effects. Students tend to assimilate the average performance of their friends and of their advisors. At the same time, students attaining similar levels of academic performance are more likely to develop friendship and advice ties. Together, these results imply that processes of social influence and social selection are sub-components of a more general a co-evolutionary process linking network structure and individual behavior. We discuss possible points of contact between our findings and current research in the economics and sociology of education.

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.

Multi-Agent Inference in Social Networks: A Finite Population Learning Approach

PubMed Central

Tong, Xin; Zeng, Yao

2016-01-01

When people in a society want to make inference about some parameter, each person may want to use data collected by other people. Information (data) exchange in social networks is usually costly, so to make reliable statistical decisions, people need to trade off the benefits and costs of information acquisition. Conflicts of interests and coordination problems will arise in the process. Classical statistics does not consider people’s incentives and interactions in the data collection process. To address this imperfection, this work explores multi-agent Bayesian inference problems with a game theoretic social network model. Motivated by our interest in aggregate inference at the societal level, we propose a new concept, finite population learning, to address whether with high probability, a large fraction of people in a given finite population network can make “good” inference. Serving as a foundation, this concept enables us to study the long run trend of aggregate inference quality as population grows. PMID:27076691

The Game of Contacts: Estimating the Social Visibility of Groups.

PubMed

Salganik, Matthew J; Mello, Maeve B; Abdo, Alexandre H; Bertoni, Neilane; Fazito, Dimitri; Bastos, Francisco I

2011-01-01

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations-illicit drug users, men who have sex with men, and sex workers-are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys.

Social networks, mental health problems, and mental health service utilization in OEF/OIF National Guard veterans.

PubMed

Sripada, Rebecca K; Bohnert, Amy S B; Teo, Alan R; Levine, Debra S; Pfeiffer, Paul N; Bowersox, Nicholas W; Mizruchi, Mark S; Chermack, Stephen T; Ganoczy, Dara; Walters, Heather; Valenstein, Marcia

2015-09-01

Low social support and small social network size have been associated with a variety of negative mental health outcomes, while their impact on mental health services use is less clear. To date, few studies have examined these associations in National Guard service members, where frequency of mental health problems is high, social support may come from military as well as other sources, and services use may be suboptimal. Surveys were administered to 1448 recently returned National Guard members. Multivariable regression models assessed the associations between social support characteristics, probable mental health conditions, and service utilization. In bivariate analyses, large social network size, high social network diversity, high perceived social support, and high military unit support were each associated with lower likelihood of having a probable mental health condition (p < .001). In adjusted analyses, high perceived social support (OR .90, CI .88-.92) and high unit support (OR .96, CI .94-.97) continued to be significantly associated with lower likelihood of mental health conditions. Two social support measures were associated with lower likelihood of receiving mental health services in bivariate analyses, but were not significant in adjusted models. General social support and military-specific support were robustly associated with reduced mental health symptoms in National Guard members. Policy makers, military leaders, and clinicians should attend to service members' level of support from both the community and their units and continue efforts to bolster these supports. Other strategies, such as focused outreach, may be needed to bring National Guard members with need into mental health care.

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

PubMed

Kishi, Reiko; Horikawa, Naoko

2004-02-01

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

Online Identities and Social Networking

NASA Astrophysics Data System (ADS)

Maheswaran, Muthucumaru; Ali, Bader; Ozguven, Hatice; Lord, Julien

Online identities play a critical role in the social web that is taking shape on the Internet. Despite many technical proposals for creating and managing online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are growing at a rapid pace and has millions of members in them. While the recent trend is to create explicit OSNs such as Facebook and MySpace, we also have implicit OSNs such as interaction graphs created by email and instant messaging services. Explicit OSNs allow users to create profiles and use them to project their identities on the web. There are many interesting identity related issues in the context of social networking including how OSNs help and hinder the definition of online identities.

The Use of Social Networks to Employ the Wisdom of Crowds for Teaching

ERIC Educational Resources Information Center

Klieger, Aviva

2016-01-01

The "Wisdom of Crowds" hypothesis has been introduced into many fields, but not into education. Groups with diverse knowledge and skills make better decisions than homogenous groups or expert groups. Diversity adds different points of view, which improve the problem solving ability of the group. The increased use of social networks makes…

Does a brief state mindfulness induction moderate disgust-driven social avoidance and decision-making? An experimental investigation.

PubMed

Reynolds, Lisa M; Lin, Yee Sing; Zhou, Eric; Consedine, Nathan S

2015-02-01

In this experimental study, we evaluated whether manipulated disgust and mindfulness predicted social avoidance in bowel health contexts. Community participants (n = 101) were randomised to conditions in which disgust and/or state mindfulness were experimentally induced. Tasks assessing social avoidance and perceptions of available social networks in the context of bowel/health problems were conducted. Manipulation checks confirmed the elicitation of disgust and state mindfulness in the applicable conditions. As expected, persons in the disgust condition were more likely to exhibit immediate social avoidance (rejecting a glass of water). State disgust predicted greater socially avoidant decision-making, less decisional conflict, and smaller social network maps. State mindfulness predicted fewer names on inner network circles and amplified the effect of disgust on creating smaller social network maps. This report furthers understanding of disgust and avoidance in bowel health contexts, and suggests the need for caution in mindfulness interventions that raise awareness of emotion without also providing skills in emotional regulation.

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.

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

PubMed

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

2018-06-13

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

Setting Access Permission through Transitive Relationship in Web-based Social Networks

NASA Astrophysics Data System (ADS)

Hong, Dan; Shen, Vincent Y.

The rising popularity of various social networking websites has created a huge problem on Internet privacy. Although it is easy to post photos, comments, opinions on some events, etc. on the Web, some of these data (such as a person’s location at a particular time, criticisms of a politician, etc.) are private and should not be accessed by unauthorized users. Although social networks facilitate sharing, the fear of sending sensitive data to a third party without knowledge or permission of the data owners discourages people from taking full advantage of some social networking applications. We exploit the existing relationships on social networks and build a ‘‘trust network’’ with transitive relationship to allow controlled data sharing so that the privacy and preferences of data owners are respected. The trust network linking private data owners, private data requesters, and intermediary users is a directed weighted graph. The permission value for each private data requester can be automatically assigned in this network based on the transitive relationship. Experiments were conducted to confirm the feasibility of constructing the trust network from existing social networks, and to assess the validity of permission value assignments in the query process. Since the data owners only need to define the access rights of their closest contacts once, this privacy scheme can make private data sharing easily manageable by social network participants.

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

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.

Acceptability of participatory social network analysis for problem-solving in Australian Aboriginal health service partnerships

PubMed Central

2012-01-01

Background While participatory social network analysis can help health service partnerships to solve problems, little is known about its acceptability in cross-cultural settings. We conducted two case studies of chronic illness service partnerships in 2007 and 2008 to determine whether participatory research incorporating social network analysis is acceptable for problem-solving in Australian Aboriginal health service delivery. Methods Local research groups comprising 13–19 partnership staff, policy officers and community members were established at each of two sites to guide the research and to reflect and act on the findings. Network and work practice surveys were conducted with 42 staff, and the results were fed back to the research groups. At the end of the project, 19 informants at the two sites were interviewed, and the researchers conducted critical reflection. The effectiveness and acceptability of the participatory social network method were determined quantitatively and qualitatively. Results Participants in both local research groups considered that the network survey had accurately described the links between workers related to the exchange of clinical and cultural information, team care relationships, involvement in service management and planning and involvement in policy development. This revealed the function of the teams and the roles of workers in each partnership. Aboriginal workers had a high number of direct links in the exchange of cultural information, illustrating their role as the cultural resource, whereas they had fewer direct links with other network members on clinical information exchange and team care. The problem of their current and future roles was discussed inside and outside the local research groups. According to the interview informants the participatory network analysis had opened the way for problem-solving by “putting issues on the table”. While there were confronting and ethically challenging aspects, these informants considered that with flexibility of data collection to account for the preferences of Aboriginal members, then the method was appropriate in cross-cultural contexts for the difficult discussions that are needed to improve partnerships. Conclusion Critical reflection showed that the preconditions for difficult discussions are, first, that partners have the capacity to engage in such discussions, second, that partners assess whether the effort required for these discussions is balanced by the benefits they gain from the partnership, and, third, that “boundary spanning” staff can facilitate commitment to partnership goals. PMID:22682504

A Tale of Two Towns: A Comparative Study Exploring the Possibilities and Pitfalls of Social Capital among People Seeking Recovery from Substance Misuse.

PubMed

Weston, Samantha; Honor, Stuart; Best, David

2018-02-23

Social capital has become an influential concept in debating and understanding the modern world. Within the drug and alcohol sector, the concept of 'recovery capital' has gained traction with researchers suggesting that people who have access to such capital are better placed to overcome their substance use-related problems than those who do not (Cloud and Granfield, 2008), leading to requests for interventions that focus on building social capital networks (Neale & Stevenson, 2015). While accepting that the concept of social capital has enormous potential for addressing the problems associated with drug use, this paper also considers its 'dark side'. Data were drawn from semi-structured interviews with 180 participants including 135 people who use drugs and 45 people who formerly used drugs. High levels of trust, acquired through the establishment of dense social networks, are required to initiate recovery. However, these 'strong bonds' may also lead to the emergence of what is perceived by others as an exclusive social network that limits membership to those who qualify and abide by the 'rules' of the recovery community, particularly around continuous abstinence. Depending on the nature of the networks and the types of links participants have into them being socially connected can both inhibit and encourage recovery. Therefore, the successful application of social capital within the drugs and alcohol field requires a consideration of not only the presence or absence of social connections but their nature, the value they produce, and the social contexts within which they are developed.

Illness representations of depression and perceptions of the helpfulness of social support: comparing depressed and never-depressed persons.

PubMed

Vollmann, Manja; Scharloo, Margreet; Salewski, Christel; Dienst, Alexander; Schonauer, Klaus; Renner, Britta

2010-09-01

Interactions between depressed persons and persons within their social network are often characterized by misunderstanding and unsuccessful social support attempts. These interpersonal problems could be fostered by discrepancies between depressed and never-depressed persons' illness representations of depression and/or discrepancies in the perceived helpfulness of supportive behaviors. Illness representations of depression (IPQ-R) and perceptions of the helpfulness of different social support behaviors (ISU-DYA and ISAD) were assessed in 41 currently depressed persons and 58 persons without a history of depression. Never-depressed persons perceived depression as more controllable by treatment and as less emotionally impairing than depressed persons, but also as having more severe consequences. Never-depressed persons considered activation-oriented support (motivation to approach problems) as more helpful and protection-oriented support (allowance to draw back) as less helpful in comparison to depressed persons. Data were collected in unrelated samples of depressed and never-depressed persons. Discrepancies in illness representations and perceptions of the helpfulness of social support do exist and may be the origin of problematic social interactions between depressed patients and persons within their social network. Therapeutic interventions should address the issue of conflicting perceptions and encourage depressed patients to acknowledge and discuss this topic within their social network. 2010 Elsevier B.V. All rights reserved.

Location-based social networking media for restaurant promotion and food review using mobile application

NASA Astrophysics Data System (ADS)

Luhur, H. S.; Widjaja, N. D.

2014-03-01

This paper is focusing on the development of a mobile application for searching restaurants and promotions with location based and social networking features. The main function of the application is to search restaurant information. Other functions are also available in this application such as add restaurant, add promotion, add photo, add food review, and other features including social networking features. The restaurant and promotion searching application will be developed under Android platform. Upon completion of this paper, heuristic evaluation and usability testing have been conducted. The result of both testing shows that the application is highly usable. Even though there are some usability problems discovered, the problems can be eliminated immediately by implementing the recommendations from the expert evaluators and the users as the testers of the application. Further improvement made to the application will ensure that the application can really be beneficial for the users of the application.

A practical guide to social networks.

PubMed

Cross, Rob; Liedtka, Jeanne; Weiss, Leigh

2005-03-01

Saying that networks are important is stating the obvious. But harnessing the power of these seemingly invisible groups to achieve organizational goals is an elusive undertaking. Most efforts to promote collaboration are haphazard and built on the implicit philosophy that more connectivity is better. In truth, networks create relational demands that sap people's time and energy and can bog down entire organizations. It's crucial for executives to learn how to promote connectivity only where it benefits an organization or individual and to decrease unnecessary connections. In this article, the authors introduce three types of social networks, each of which delivers unique value. The customized response network excels at framing the ambiguous problems involved in innovation. Strategy consulting firms and new-product development groups rely on this format. By contrast, surgical teams and law firms rely mostly on the modular response network, which works best when components of the problem are known but the sequence of those components in the solution is unknown. And the routine response network is best suited for organizations like call centers, where the problems and solutions are fairly predictable but collaboration is still needed. Executives shouldn't simply hope that collaboration will spontaneously occur in the right places atthe right times in their organization. They need to develop a strategic, nuanced view of collaboration, and they must take steps to ensure that their companies support the types of social networks that best fit their goals. Drawing on examples from Novartis, the FAA, and Sallie Mae, the authors offer managers the tools they need to determine which network will deliver the best results for their organizations and which strategic investments will nurture the right degree of connectivity.

Constructing Social Networks from Unstructured Group Dialog in Virtual Worlds

NASA Astrophysics Data System (ADS)

Shah, Fahad; Sukthankar, Gita

Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. In this paper, we present techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world. We present an algorithm for addressing this problem, Shallow Semantic Temporal Overlap (SSTO), that combines temporal and language information to create directional links between participants, and a second approach that relies on temporal overlap alone to create undirected links between participants. Relying on temporal overlap is noisy, resulting in a low precision and networks with many extraneous links. In this paper, we demonstrate that we can ameliorate this problem by using network modularity optimization to perform community detection in the noisy networks and severing cross-community links. Although using the content of the communications still results in the best performance, community detection is effective as a noise reduction technique for eliminating the extra links created by temporal overlap alone.

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.

Psychiatric Patients Tracking Through a Private Social Network for Relatives: Development and Pilot Study.

PubMed

García-Peñalvo, Francisco J; Martín, Manuel Franco; García-Holgado, Alicia; Guzmán, José Miguel Toribio; Antón, Jesús Largo; Sánchez-Gómez, Ma Cruz

2016-07-01

The treatment of psychiatric patients requires different health care from that of patients from other medical specialties. In particular, in the case of Department of Psychiatry from the Zamora Hospital (Spain), the period of time which patients require institutionalized care is a tiny part of their treatment. A large part of health care provided to the patient is aimed at his/her rehabilitation and social integration through day-care centres, supervised flats or activities. Conversely, several reports reveal that approximately 50 % of Internet users use the network as a source of health information, which has led to the emergence of virtual communities where patients, relatives or health professionals share their knowledge concerning an illness, health problem or specific health condition. In this context, we have identified that the relatives have a lack of information regarding the daily activities of patients under psychiatric treatment. The social networks or the virtual communities regarding health problems do not provide a private space where relatives can follow the patient's progress, despite being in different places. The goal of the study was to use technologies to develop a private social network for being used by severe mental patients (mainly schizophrenic patients). SocialNet is a pioneer social network in the health sector because it provides a social interaction context restricted to persons authorized by the patient or his/her legal guardian in such a way that they can track his/her daily activity. Each patient has a private area only accessible to authorized persons and their caregivers, where they can share pictures, videos or texts regarding his/her progress. A preliminary study of usability of the system has been made for increasing the usefulness and usability of SocialNet. SocialNet is the first system for promoting personal interactions among formal caregivers, family, close friends and patient, promoting the recovery of schizophrenic patients. Future studies should study the network's potential usefulness for improving the prognosis and recovery of schizophrenia.

The anatomy of urban social networks and its implications in the searchability problem

PubMed Central

Herrera-Yagüe, C.; Schneider, C. M.; Couronné, T.; Smoreda, Z.; Benito, R. M.; Zufiria, P. J.; González, M. C.

2015-01-01

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the social network structure of over 25 million phone users from three countries at three different scales: country, provinces and cities. We consistently find that this last urban scenario presents significant differences to common knowledge about social networks. First, the emergence of a giant component in the network seems to be controlled by whether or not the network spans over the entire urban border, almost independently of the population or geographic extension of the city. Second, urban communities are much less geographically clustered than expected. These two findings shed new light on the widely-studied searchability in self-organized networks. By exhaustive simulation of decentralized search strategies we conclude that urban networks are searchable not through geographical proximity as their country-wide counterparts, but through an homophily-driven community structure. PMID:26035529

The anatomy of urban social networks and its implications in the searchability problem.

PubMed

Herrera-Yagüe, C; Schneider, C M; Couronné, T; Smoreda, Z; Benito, R M; Zufiria, P J; González, M C

2015-06-02

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the social network structure of over 25 million phone users from three countries at three different scales: country, provinces and cities. We consistently find that this last urban scenario presents significant differences to common knowledge about social networks. First, the emergence of a giant component in the network seems to be controlled by whether or not the network spans over the entire urban border, almost independently of the population or geographic extension of the city. Second, urban communities are much less geographically clustered than expected. These two findings shed new light on the widely-studied searchability in self-organized networks. By exhaustive simulation of decentralized search strategies we conclude that urban networks are searchable not through geographical proximity as their country-wide counterparts, but through an homophily-driven community structure.

GraphStore: A Distributed Graph Storage System for Big Data Networks

ERIC Educational Resources Information Center

Martha, VenkataSwamy

2013-01-01

Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…

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…

The Need for a More Efficient User Notification System in Using Social Networks as Ubiquitous Learning Platforms

ERIC Educational Resources Information Center

Mihci, Can; Donmez, Nesrin Ozdener

2017-01-01

While carrying out formative assessment activities over social network services (SNS), it has been noted that personalized notifications have a high chance of "the important post getting lost" in the notification feed. In order to highlight this problem, this paper compares within a posttest only quasi-experiment, a total of 104 first…

Exploring the Potential of Social Network Sites in Relation to Intercultural Communication

ERIC Educational Resources Information Center

Lang, Anouk

2012-01-01

This article reports on the results of a project which used a social network site to support students on a year abroad and foster informal learning, particularly in the area of intercultural communication. The project employed a peer-mentoring structure to solve the problem of role conflict, in which users of these sites may feel some tension as…

The Strength of the Strongest Ties in Collaborative Problem Solving

NASA Astrophysics Data System (ADS)

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-01

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

The strength of the strongest ties in collaborative problem solving.

PubMed

de Montjoye, Yves-Alexandre; Stopczynski, Arkadiusz; Shmueli, Erez; Pentland, Alex; Lehmann, Sune

2014-06-20

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

DARPA ADAMS Project

DTIC Science & Technology

2015-05-11

it means that Mary distrusts John. We showed that it is possible to analyze such trust- distrust relationships within signed social networks in... relationship problems) − Professional Problems (negative changes at workplace, interpersonal conflicts) Furthermore, we encode in 2nd degree variables...a social media forum data. • Processed initial set of Vegas metrics data (clustering coefficient, # similar users, # skip levels) through time

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

PubMed

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

2015-03-01

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

Modeling and analyzing malware propagation in social networks with heterogeneous infection rates

NASA Astrophysics Data System (ADS)

Jia, Peng; Liu, Jiayong; Fang, Yong; Liu, Liang; Liu, Luping

2018-10-01

With the rapid development of social networks, hackers begin to try to spread malware more widely by utilizing various kinds of social networks. Thus, studying malware epidemic dynamics in these networks is becoming a popular subject in the literature. Most of the previous works focus on the effects of factors, such as network topology and user behavior, on malware propagation. Some researchers try to analyze the heterogeneity of infection rates, but the common problem of their works is the factors they mentioned that could affect the heterogeneity are not comprehensive enough. In this paper, focusing on the effects of heterogeneous infection rates, we propose a novel model called HSID (heterogeneous-susceptible-infectious-dormant model) to characterize virus propagation in social networks, in which a connection factor is presented to evaluate the heterogeneous relationships between nodes, and a resistance factor is introduced to represent node's mutable resistant ability. We analyzed how key parameters in the two factors affect the heterogeneity and then performed simulations to explore the effects in three real-world social networks. The results indicate: heterogeneous relationship could lead to wider diffusion in directed network, and heterogeneous security awareness could lead to wider diffusion in both directed and undirected networks; heterogeneous relationship could restrain the outbreak of malware but heterogeneous initial security awareness would increase the probability; furthermore, the increasing resistibility along with infected times would lead to malware's disappearance in social networks.

The Game of Contacts: Estimating the Social Visibility of Groups☆

PubMed Central

Salganik, Matthew J.; Mello, Maeve B.; Abdo, Alexandre H.; Bertoni, Neilane; Fazito, Dimitri; Bastos, Francisco I.

2010-01-01

Estimating the sizes of hard-to-count populations is a challenging and important problem that occurs frequently in social science, public health, and public policy. This problem is particularly pressing in HIV/AIDS research because estimates of the sizes of the most at-risk populations—illicit drug users, men who have sex with men, and sex workers—are needed for designing, evaluating, and funding programs to curb the spread of the disease. A promising new approach in this area is the network scale-up method, which uses information about the personal networks of respondents to make population size estimates. However, if the target population has low social visibility, as is likely to be the case in HIV/AIDS research, scale-up estimates will be too low. In this paper we develop a game-like activity that we call the game of contacts in order to estimate the social visibility of groups, and report results from a study of heavy drug users in Curitiba, Brazil (n = 294). The game produced estimates of social visibility that were consistent with qualitative expectations but of surprising magnitude. Further, a number of checks suggest that the data are high-quality. While motivated by the specific problem of population size estimation, our method could be used by researchers more broadly and adds to long-standing efforts to combine the richness of social network analysis with the power and scale of sample surveys. PMID:21318126

Predicting the global spread range via small subnetworks

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Women as Managers.

ERIC Educational Resources Information Center

Moore, Linda L.

1981-01-01

Discusses theories that socialization or "the system" cause women's problems in management, contending that both contribute. Analyzes women manager's problems in using and misusing power and coping with stress. Discusses public/private sector differences. Suggests that networking and constructive self-analysis can alleviate some problems. (AYC)

Social medicine and international expert networks in Latin America, 1930-1945.

PubMed

Carter, Eric D

2018-01-03

This paper examines the international networks that influenced ideas and policy in social medicine in the 1930s and 1940s in Latin America, focusing on institutional networks organised by the League of Nations Health Organization, the International Labour Organization, and the Pan-American Sanitary Bureau. After examining the architecture of these networks, this paper traces their influence on social and health policy in two policy domains: social security and nutrition. Closer scrutiny of a series of international conferences and local media accounts of them reveals that international networks were not just 'conveyor belts' for policy ideas from the industrialised countries of the US and Europe into Latin America; rather, there was often contentious debate over the relevance and appropriateness of health and social policy models in the Latin American context. Recognition of difference between Latin America and the global economic core regions was a key impetus for seeking 'national solutions to national problems' in countries like Argentina and Chile, even as integration into these networks provided progressive doctors, scientists, and other intellectuals important international support for local political reforms.

The role of social media in schizophrenia: evaluating risks, benefits, and potential.

PubMed

Torous, John; Keshavan, Matcheri

2016-05-01

Patients with schizophrenia suffer from numerous social problems often because of negative symptoms of the illness and impairments in social cognition. Social media and social networks now offer a novel tool to engage and help patients navigate and potentially improve social functioning. In this review, we aim to explore how impaired neural networks in schizophrenia impair social functioning, examine the evidence base for social networks and social media to help in the role, consider the evidence for current risks and benefits of use, and discuss the future of social media and social networks for schizophrenia. Patients with schizophrenia are increasingly connected to and engaged with social media. There is strong evidence that they own, use, and accept digital tools like smartphones and already use social media services like Facebook at high rates, especially among those who are younger. Less is known about the clinical risks and benefits of social media use in schizophrenia, although there are increasingly more social networking platforms being designed specifically for those with mental illness. Social media tools have the potential to offer a plethora of new services to patients with schizophrenia, although the clinical evidence base for such is still nascent. It is important to ensure that both clinicians and patients are aware of and educated about the risks of using social media. Going forward, it is likely that social media will have an expanding role in care, with social media offering new pathways to address negative symptoms and impairments in social cognition in schizophrenia.

An effective immunization strategy for airborne epidemics in modular and hierarchical social contact network

NASA Astrophysics Data System (ADS)

Song, Zhichao; Ge, Yuanzheng; Luo, Lei; Duan, Hong; Qiu, Xiaogang

2015-12-01

Social contact between individuals is the chief factor for airborne epidemic transmission among the crowd. Social contact networks, which describe the contact relationships among individuals, always exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated. We find that traditional global targeted immunization strategy would lose its superiority in controlling the epidemic propagation in the social contact networks with modular and hierarchical structure. Therefore, we propose a hierarchical targeted immunization strategy to settle this problem. In this novel strategy, importance of the hierarchical structure is considered. Transmission control experiments of influenza H1N1 are carried out based on a modular and hierarchical network model. Results obtained indicate that hierarchical structure of the network is more critical than the degrees of the immunized targets and the modular network layer is the most important for the epidemic propagation control. Finally, the efficacy and stability of this novel immunization strategy have been validated as well.

Optimal information dissemination strategy to promote preventive behaviors in multilayer epidemic networks.

PubMed

Shakeri, Heman; Sahneh, Faryad Darabi; Scoglio, Caterina; Poggi-Corradini, Pietro; Preciado, Victor M

2015-06-01

Launching a prevention campaign to contain the spread of infection requires substantial financial investments; therefore, a trade-off exists between suppressing the epidemic and containing costs. Information exchange among individuals can occur as physical contacts (e.g., word of mouth, gatherings), which provide inherent possibilities of disease transmission, and non-physical contacts (e.g., email, social networks), through which information can be transmitted but the infection cannot be transmitted. Contact network (CN) incorporates physical contacts, and the information dissemination network (IDN) represents non-physical contacts, thereby generating a multilayer network structure. Inherent differences between these two layers cause alerting through CN to be more effective but more expensive than IDN. The constraint for an epidemic to die out derived from a nonlinear Perron-Frobenius problem that was transformed into a semi-definite matrix inequality and served as a constraint for a convex optimization problem. This method guarantees a dying-out epidemic by choosing the best nodes for adopting preventive behaviors with minimum monetary resources. Various numerical simulations with network models and a real-world social network validate our method.

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

PubMed

Ahmed, Amr; Xing, Eric P

2009-07-21

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

Statistical Mechanics of Temporal and Interacting Networks

NASA Astrophysics Data System (ADS)

Zhao, Kun

In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide a new framework to quantify the information encoded in these networks and to answer a fundamental problem in network science: how complex are temporal and growing networks. Finally, we consider two examples of critical phenomena in interacting networks. In particular, on one side we investigate the percolation of interacting networks by introducing antagonistic interactions. On the other side, we investigate a model of political election based on the percolation of antagonistic networks. The aim of this research is to show how antagonistic interactions change the physics of critical phenomena on interacting networks. We believe that the work presented in these thesis offers the possibility to appreciate the large variability of problems that can be addressed in the new framework of temporal and interacting networks.

Social and strategic imitation: the way to consensus.

PubMed

Vilone, Daniele; Ramasco, José J; Sánchez, Angel; Miguel, Maxi San

2012-01-01

Humans do not always make rational choices, a fact that experimental economics is putting on solid grounds. The social context plays an important role in determining our actions, and often we imitate friends or acquaintances without any strategic consideration. We explore here the interplay between strategic and social imitative behavior in a coordination problem on a social network. We observe that for interactions on 1D and 2D lattices any amount of social imitation prevents the freezing of the network in domains with different conventions, thus leading to global consensus. For interactions on complex networks, the interplay of social and strategic imitation also drives the system towards global consensus while neither dynamics alone does. We find an optimum value for the combination of imitative behaviors to reach consensus in a minimum time, and two different dynamical regimes to approach it: exponential when social imitation predominates, power-law when strategic considerations prevail.

The use of social-networking sites in medical education.

PubMed

Cartledge, Peter; Miller, Michael; Phillips, Bob

2013-10-01

A social-network site is a dedicated website or application which enables users to communicate with each other and share information, comments, messages, videos and images. This review aimed to ascertain if "social-networking sites have been used successfully in medical education to deliver educational material", and whether "healthcare professionals, and students, are engaging with social-networking sites for educational purposes". A systematic-review was undertaken using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Eight databases were searched with pre-defined search terms, limits and inclusion criteria. Data was extracted into a piloted data-table prior to the narrative-synthesis of the Quality, Utility, Extent, Strength, Target and Setting of the evidence. 1047 articles were identified. Nine articles were reviewed with the majority assessing learner satisfaction. Higher outcome measures were rarely investigated. Educators used Facebook, Twitter, and a custom-made website, MedicineAfrica to achieve their objectives. Social-networking sites have been employed without problems of professionalism, and received positive feedback from learners. However, there is no solid evidence base within the literature that social-networking is equally or more effective than other media available for educational purposes.

A new centrality measure for identifying influential nodes in social networks

NASA Astrophysics Data System (ADS)

Rhouma, Delel; Ben Romdhane, Lotfi

2018-04-01

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

The Transmission of Gun and Other Weapon-Involved Violence Within Social Networks

PubMed Central

Tracy, Melissa; Braga, Anthony A.; Papachristos, Andrew V.

2016-01-01

Fatal and nonfatal injuries resulting from gun violence remain a persistent problem in the United States. The available research suggests that gun violence diffuses among people and across places through social relationships. Understanding the relationship between gun violence within social networks and individual gun violence risk is critical in preventing the spread of gun violence within populations. This systematic review examines the existing scientific evidence on the transmission of gun and other weapon-related violence in household, intimate partner, peer, and co-offending networks. Our review identified 16 studies published between 1996 and 2015 that suggest that exposure to a victim or perpetrator of violence in one's interpersonal relationships and social networks increases the risk of individual victimization and perpetration. Formal network analyses find high concentrations of gun violence in small networks and that exposure to gun violence in one's networks is highly correlated with one's own probability of being a gunshot victim. Physical violence by parents and weapon use by intimate partners also increase risk for victimization and perpetration. Additional work is needed to better characterize the mechanisms through which network exposures increase individual risk for violence and to evaluate interventions aimed at disrupting the spread of gun and other weapon violence in high-risk social networks. PMID:26733492

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

PubMed

Liu, Lianggui; Chen, Li; Jia, Huiling

2016-02-19

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

Predictors of Change in Self-Reported Social Networks among Homeless Young People

PubMed Central

Falci, Christina D.; Whitbeck, Les B.; Hoyt, Dan R.; Rose, Trina

2011-01-01

This research investigates changes in social network size and composition of 351 homeless adolescents over three years. Findings show that network size decreases over time. Homeless youth with a conduct disorder begin street life with small networks that remain small over time. Caregiver abuse is associated with smaller emotional networks due to fewer home ties, especially to parents, and a more rapid loss of emotional home ties over time. Homeless youth with major depression start out with small networks, but are more likely to maintain network ties. Youth with substance abuse problems are more likely to maintain instrumental home ties. Finally, homeless adolescents tend to reconnect with their parents for instrumental aid and form romantic relationship that provide emotional support. PMID:22121332

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.

How do people with long-term mental health problems negotiate relationships with network members at times of crisis?

PubMed

Walker, Sandra; Kennedy, Anne; Vassilev, Ivaylo; Rogers, Anne

2018-02-01

Social network processes impact on the genesis and management of mental health problems. There is currently less understanding of the way people negotiate networked relationships in times of crisis compared to how they manage at other times. This paper explores the patterns and nature of personal network involvement at times of crises and how these may differ from day-to-day networks of recovery and maintenance. Semi-structured interviews with 25 participants with a diagnosis of long-term mental health (MH) problems drawn from recovery settings in the south of England. Interviews centred on personal network mapping of members and resources providing support. The mapping interviews explored the work of network members and changes in times of crisis. Interviews were recorded, transcribed and analysed using a framework analysis. Three key themes were identified: the fluidity of network relationality between crisis and recovery; isolation as a means of crises management; leaning towards peer support. Personal network input retreated at times of crisis often as result of "ejection" from the network by participants who used self-isolation as a personal management strategy in an attempt to deal with crises. Peer support is considered useful during a crisis, whilst the role of services was viewed with some ambiguity. Social networks membership, and type and depth of involvement, is subject to change between times of crisis and everyday support. This has implications for managing mental health in terms of engaging with network support differently in times of crises versus recovery and everyday living. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.

Positive Impact of Social Media Use on Depression in Cancer Patients

PubMed

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

2017-11-26

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

Social learning strategies modify the effect of network structure on group performance.

PubMed

Barkoczi, Daniel; Galesic, Mirta

2016-10-07

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Social learning strategies modify the effect of network structure on group performance

NASA Astrophysics Data System (ADS)

Barkoczi, Daniel; Galesic, Mirta

2016-10-01

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.

Final Report: Sensorpedia Phases 1 and 2

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

Gorman, Bryan L; Resseguie, David R

2010-08-01

Over the past several years, ORNL has been actively involved in research to formalize the engineering principles and best practices behind emerging social media and social networking concepts to solve real-time data sharing problems for national security and defense, public health and safety, environmental and infrastructure awareness, and disaster preparedness and response. Sensorpedia, an ORNL web site, is a practical application of several key social media principles. Dubbed the Wikipedia for sensors, Sensorpedia is currently in limited BETA testing and was selected in 2009 by Federal Computer Week as one of the government s top 10 social networking sites.

Social Support and Intellectual Disabilities: A Comparison between Social Networks of Adults with Intellectual Disability and Those with Physical Disability

ERIC Educational Resources Information Center

Lippold, T.; Burns, J.

2009-01-01

Background: Social support has been identified as a major protective factor in preventing mental health problems and also as a major contributor to quality of life. People with intellectual disabilities (ID) have been identified as having limited social support structures. Interventions have been focused on promoting their social presence and…

Extracting information from multiplex networks

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Bianconi, Ginestra

2016-06-01

Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

Evolution of co-management: role of knowledge generation, bridging organizations and social learning.

PubMed

Berkes, Fikret

2009-04-01

Over a period of some 20 years, different aspects of co-management (the sharing of power and responsibility between the government and local resource users) have come to the forefront. The paper focuses on a selection of these: knowledge generation, bridging organizations, social learning, and the emergence of adaptive co-management. Co-management can be considered a knowledge partnership. Different levels of organization, from local to international, have comparative advantages in the generation and mobilization of knowledge acquired at different scales. Bridging organizations provide a forum for the interaction of these different kinds of knowledge, and the coordination of other tasks that enable co-operation: accessing resources, bringing together different actors, building trust, resolving conflict, and networking. Social learning is one of these tasks, essential both for the co-operation of partners and an outcome of the co-operation of partners. It occurs most efficiently through joint problem solving and reflection within learning networks. Through successive rounds of learning and problem solving, learning networks can incorporate new knowledge to deal with problems at increasingly larger scales, with the result that maturing co-management arrangements become adaptive co-management in time.

Why Universities Join Cross-Sector Social Partnerships: Theory and Evidence

ERIC Educational Resources Information Center

Siegel, David J.

2010-01-01

Cross-sector partnerships are an increasingly popular mode of organizing to address intractable social problems, yet theory and research have virtually ignored university involvement in such activity. This article attempts to ascertain the reasons universities join networks of other social actors to support a common cause. Theories on the…

Social Knowledge Awareness Map for Computer Supported Ubiquitous Learning Environment

ERIC Educational Resources Information Center

El-Bishouty, Moushir M.; Ogata, Hiroaki; Rahman, Samia; Yano, Yoneo

2010-01-01

Social networks are helpful for people to solve problems by providing useful information. Therefore, the importance of mobile social software for learning has been supported by many researches. In this research, a model of personalized collaborative ubiquitous learning environment is designed and implemented in order to support learners doing…

Modeling cascading failures with the crisis of trust in social networks

NASA Astrophysics Data System (ADS)

Yi, Chengqi; Bao, Yuanyuan; Jiang, Jingchi; Xue, Yibo

2015-10-01

In social networks, some friends often post or disseminate malicious information, such as advertising messages, informal overseas purchasing messages, illegal messages, or rumors. Too much malicious information may cause a feeling of intense annoyance. When the feeling exceeds a certain threshold, it will lead social network users to distrust these friends, which we call the crisis of trust. The crisis of trust in social networks has already become a universal concern and an urgent unsolved problem. As a result of the crisis of trust, users will cut off their relationships with some of their untrustworthy friends. Once a few of these relationships are made unavailable, it is likely that other friends will decline trust, and a large portion of the social network will be influenced. The phenomenon in which the unavailability of a few relationships will trigger the failure of successive relationships is known as cascading failure dynamics. To our best knowledge, no one has formally proposed cascading failures dynamics with the crisis of trust in social networks. In this paper, we address this potential issue, quantify the trust between two users based on user similarity, and model the minimum tolerance with a nonlinear equation. Furthermore, we construct the processes of cascading failures dynamics by considering the unique features of social networks. Based on real social network datasets (Sina Weibo, Facebook and Twitter), we adopt two attack strategies (the highest trust attack (HT) and the lowest trust attack (LT)) to evaluate the proposed dynamics and to further analyze the changes of the topology, connectivity, cascading time and cascade effect under the above attacks. We numerically find that the sparse and inhomogeneous network structure in our cascading model can better improve the robustness of social networks than the dense and homogeneous structure. However, the network structure that seems like ripples is more vulnerable than the other two network structures. Our findings will be useful in further guiding the construction of social networks to effectively avoid the cascading propagation with the crisis of trust. Some research results can help social network service providers to avoid severe cascading failures.

Online Social Networking and Mental Health

PubMed Central

2014-01-01

Abstract During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction. PMID:25192305

Online social networking and mental health.

PubMed

Pantic, Igor

2014-10-01

During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction.

Usability Evaluation of a Private Social Network on Mental Health for Relatives.

PubMed

Toribio-Guzmán, José Miguel; García-Holgado, Alicia; Soto Pérez, Felipe; García-Peñalvo, Francisco J; Franco Martín, Manuel

2017-09-01

Usability is one of the most prominent criteria that must be fulfilled by a software product. This study aims to evaluate the usability of SocialNet, a private social network for monitoring the daily progress of patients by their relatives, using a mixed usability approach: heuristic evaluation conducted by experts and user testing. A double heuristic evaluation with one expert evaluator identified the issues related to consistency, design, and privacy. User testing was conducted on 20 users and one evaluator using observation techniques and questionnaires. The main usability problems were found to be related to the structure of SocialNet, and the users presented some difficulties in locating the buttons or links. The results show a high level of usability and satisfaction with the product. This evaluation provides data on the usability of SocialNet based on the difficulties experienced by the users and the expert. The results help in redesigning the tool to resolve the identified problems as part of an iterative process.

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

NASA Astrophysics Data System (ADS)

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

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

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

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

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

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

Social networks as mediators of the effect of Alcoholics Anonymous.

PubMed

Kaskutas, Lee Ann; Bond, Jason; Humphreys, Keith

2002-07-01

This study tested the hypothesis that the relationship between Alcoholics Anonymous (AA) involvement and reduced substance use is partially explained (or 'mediated') by changes in social networks. This is a naturalistic longitudinal study of the course of alcohol problems. Study sites were the 10 largest public and private alcohol treatment programs in a northern California county. Three hundred and seventy-seven men and 277 women were recruited upon seeking treatment at study sites. At baseline and 1-year follow-up, we assessed alcohol consequences and dependence symptoms, consumption, social support for abstinence, pro-drinking social influences and AA involvement. In the structural equation model, AA involvement was a significant predictor of lower alcohol consumption and fewer related problems. The size of this effect decreased by 36% when network size and support for drinking were included as mediators. In logistic regression models predicting abstinence at follow-up, AA remained highly significant after including social network variables but was again reduced in magnitude. Thirty-day abstinence was predicted by AA involvement (OR=2.9), not having pro-drinking influences in one's network (OR=0.7) and having support for reducing consumption from people met in AA (versus no support; OR=3.4). In contrast, having support from non-AA members was not a significant predictor of abstinence. For alcohol-related outcomes other than abstinence, significant relationships were found for both AA-based and non-AA-based support. The type of social support specifically given by AA members, such as 24-hour availability, role modeling and experientially based advice for staying sober, may help to explain AA's mechanism of action. Results highlight the value of focusing on outcomes reflective of AA's goals (such as abstinence) when studying how AA works.

Influence of Personal Social Network and Coping Skills on Risk for Suicidal Ideation in Chinese University Students

PubMed Central

Tang, Fang; Qin, Ping

2015-01-01

Background Personal social network and coping skills have important influences on suicidality of young people and such influences must be understood in the context of other factors. This study aims to assess the influences of social contacts and coping skills on risk for suicidal ideation and to disentangle their possible pathways using a large sample of university students from China. Methods 5972 students, randomly selected from 6 universities in China, completed the questionnaire survey for the study. Logistic regression was performed to estimate individual effect of social contacts and coping skills on risk for suicidal ideation. A partial least squares path model (PLSPM) was used to probe possible paths of their effects in the context of psychopathology. Results Of the 5972 students, 16.39% reported the presence of suicidal ideation. Poor social contacts were significantly associated with an increased risk for suicidal ideation. The influence of coping skills varied by coping styles adapted toward problems. A high score of skills on seeking guidance and support, problem solving as well as seeking alternative rewards was associated with a reduced risk of suicidal ideation; whereas a high score of acceptance or resignation, emotional discharge as well as logical analysis was associated with a significantly increased risk. Modeling the data with PLSPM indicated that the avoidance coping skills conferred the most important dimensional variable in suicidal ideation prediction, followed by the approach coping skills and social network. Conclusions Poor social contacts and deficient coping skills are strong risk factors for suicidal ideation in young students. Prevention program focusing on these problems may have an enduring effect on reducing suicidal behavior in this population. PMID:25803665

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

NASA Astrophysics Data System (ADS)

Wexler-Robock, Stephanie

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

The rise and fall of social communities: Cascades of followers triggered by innovators

NASA Astrophysics Data System (ADS)

Hu, Yanqing; Havlin, Shlomo; Makse, Hernan

2013-03-01

New scientific ideas as well as key political messages, consumer products, advertisement strategies and art trends are originally adopted by a small number of pioneers who innovate and develop the ``new ideas''. When these innovators migrate to develop the novel idea, their former social network gradually weakens its grips as followers migrate too. As a result, an internal ``cascade of followers'' starts immediately thereafter speeding up the extinction of the entire original network. A fundamental problem in network theory is to determine the minimum number of pioneers that, upon leaving, will disintegrate their social network. Here, we first employ empirical analyses of collaboration networks of scientists to show that these communities are extremely fragile with regard to the departure of a few pioneers. This process can be mapped out on a percolation model in a correlated graph crucially augmented with outgoing ``influence links''. Analytical solutions predict phase transitions, either abrupt or continuous, where networks are disintegrated through cascades of followers as in the empirical data. The theory provides a framework to predict the vulnerability of a large class of networks containing influence links ranging from social and infrastructure networks to financial systems and markets.

Legitimacy and status groups in financial markets.

PubMed

Preda, Alex

2005-09-01

Economic sociologists have argued that financial markets should be analysed as uncertainty-processing social networks and intermediary groups. Networks and intermediaries alone cannot confer legitimacy upon financial actors and transactions. Status groups are a solution to this problem. They emphasize reputation, honour and good social behaviour as stabilizers of collective action, as means of social control and as indicators of legitimacy. I examine here the emergence and evolution of status groups of brokers in London, New York and Paris, and show how emphasis on honour was used to legitimize financial transactions. I argue that financial markets should be conceived as networks, intermediary and status groups. In global, automated financial markets status groups like securities analysts are gaining in prominence.

Interspecific social networks promote information transmission in wild songbirds.

PubMed

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

2015-03-22

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

Metric projection for dynamic multiplex networks.

PubMed

Jurman, Giuseppe

2016-08-01

Evolving multiplex networks are a powerful model for representing the dynamics along time of different phenomena, such as social networks, power grids, biological pathways. However, exploring the structure of the multiplex network time series is still an open problem. Here we propose a two-step strategy to tackle this problem based on the concept of distance (metric) between networks. Given a multiplex graph, first a network of networks is built for each time step, and then a real valued time series is obtained by the sequence of (simple) networks by evaluating the distance from the first element of the series. The effectiveness of this approach in detecting the occurring changes along the original time series is shown on a synthetic example first, and then on the Gulf dataset of political events.

Divergent Drinking Patterns of Restaurant Workers: The Influence of Social Networks and Job Position.

PubMed

Duke, Michael R; Ames, Genevieve M; Moore, Roland S; Cunradi, Carol B

2013-01-01

Restaurant workers have higher rates of problem drinking than most occupational groups. However, little is known about the environmental risks and work characteristics that may lead to these behaviors. An exploration of restaurant workers' drinking networks may provide important insights into their alcohol consumption patterns, thus guiding workplace prevention efforts. Drawing from social capital theory, this paper examines the unique characteristics of drinking networks within and between various job categories. Our research suggests that these multiple, complex networks have unique risk characteristics, and that self-selection is based on factors such as job position and college attendance, among other factors.

Divergent Drinking Patterns of Restaurant Workers: The Influence of Social Networks and Job Position

PubMed Central

Ames, Genevieve M.; Moore, Roland S.; Cunradi, Carol B.

2013-01-01

Restaurant workers have higher rates of problem drinking than most occupational groups. However, little is known about the environmental risks and work characteristics that may lead to these behaviors. An exploration of restaurant workers’ drinking networks may provide important insights into their alcohol consumption patterns, thus guiding workplace prevention efforts. Drawing from social capital theory, this paper examines the unique characteristics of drinking networks within and between various job categories. Our research suggests that these multiple, complex networks have unique risk characteristics, and that self-selection is based on factors such as job position and college attendance, among other factors. PMID:23687470

[Social media, children and pediatricians].

PubMed

Le Heuzey, M-F

2012-01-01

Using social media web sites is a common activity for children, and any site that allows social interaction (social network, games, virtual worlds...) is a social media site. Pediatricians are in a position to help families understand the benefits and the risks of these sites, and to diagnose problems in children and adolescents as cyberbullying, depression, and post traumatic disorder. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

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.

Sleep problems: predictor or outcome of media use among emerging adults at university?

PubMed

Tavernier, Royette; Willoughby, Teena

2014-08-01

The pervasiveness of media use in our society has raised concerns about its potential impact on important lifestyle behaviours, including sleep. Although a number of studies have modelled poor sleep as a negative outcome of media use, a critical assessment of the literature indicates two important gaps: (i) studies have almost exclusively relied on concurrent data, and thus have not been able to assess the direction of effects; and (ii) studies have largely been conducted with children and adolescents. The purpose of the present 3-year longitudinal study, therefore, was to examine whether both sleep duration and sleep problems would be predictors or outcomes of two forms of media use (i.e. television and online social networking) among a sample of emerging adults. Participants were 942 (71.5% female) university students (M = 19.01 years, SD = 0.90) at Time 1. Survey measures, which were assessed for three consecutive years starting in the first year of university, included demographics, sleep duration, sleep problems, television and online social networking use. Results of a cross-lagged model indicated that the association between sleep problems and media use was statistically significant: sleep problems predicted longer time spent watching television and on social networking websites, but not vice versa. Contrary to our hypotheses, sleep duration was not associated with media use. Our findings indicate no negative effects of media use on sleep among emerging adults, but instead suggest that emerging adults appear to seek out media as a means of coping with their sleep problems. © 2014 European Sleep Research Society.

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 distributed incentive compatible pricing mechanism for P2P networks

NASA Astrophysics Data System (ADS)

Zhang, Jie; Zhao, Zheng; Xiong, Xiao; Shi, Qingwei

2007-09-01

Peer-to-Peer (P2P) systems are currently receiving considerable interest. However, as experience with P2P networks shows, the selfish behaviors of peers may lead to serious problems of P2P network, such as free-riding and white-washing. In order to solve these problems, there are increasing considerations on reputation system design in the study of P2P networks. Most of the existing works is concerning probabilistic estimation or social networks to evaluate the trustworthiness for a peer to others. However, these models can not be efficient all the time. In this paper, our aim is to provide a general mechanism that can maximize P2P networks social welfare in a way of Vickrey-Clarke-Groves family, while assuming every peer in P2P networks is rational and selfish, which means they only concern about their own outcome. This mechanism has some desirable properties using an O(n) algorithm: (1) incentive compatibility, every peer truly report its connection type; (2) individually rationality; and (3) fully decentralized, we design a multiple-principal multiple-agent model, concerning about the service provider and service requester individually.

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.

Structure and inference in annotated networks

PubMed Central

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

2016-01-01

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

Structure and inference in annotated networks

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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

PubMed

Ihm, Jennifer

2018-06-01

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

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Social and content aware One-Class recommendation of papers in scientific social networks.

PubMed

Wang, Gang; He, XiRan; Ishuga, Carolyne Isigi

2017-01-01

With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs.

Social and content aware One-Class recommendation of papers in scientific social networks

PubMed Central

Wang, Gang; He, XiRan

2017-01-01

With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs. PMID:28771495

Social Media’s Impact on Civic Engagement in Mexico

DTIC Science & Technology

2016-06-01

however, some analysts argue that social media 35 “PressThink: The People Formerly Known as the...can harm rather than benefit the society. Finally, technology brings about a level of inherent problems. Some concerns are that social media ...aforementioned evidence attesting to the civic awareness social media networks have provided the Mexican people , some critics, found in the literature review

Optimal network modification for spectral radius dependent phase transitions

NASA Astrophysics Data System (ADS)

Rosen, Yonatan; Kirsch, Lior; Louzoun, Yoram

2016-09-01

The dynamics of contact processes on networks is often determined by the spectral radius of the networks adjacency matrices. A decrease of the spectral radius can prevent the outbreak of an epidemic, or impact the synchronization among systems of coupled oscillators. The spectral radius is thus tightly linked to network dynamics and function. As such, finding the minimal change in network structure necessary to reach the intended spectral radius is important theoretically and practically. Given contemporary big data resources such as large scale communication or social networks, this problem should be solved with a low runtime complexity. We introduce a novel method for the minimal decrease in weights of edges required to reach a given spectral radius. The problem is formulated as a convex optimization problem, where a global optimum is guaranteed. The method can be easily adjusted to an efficient discrete removal of edges. We introduce a variant of the method which finds optimal decrease with a focus on weights of vertices. The proposed algorithm is exceptionally scalable, solving the problem for real networks of tens of millions of edges in a short time.

Purchasing Networks as Clues to Assessing Educational Psychology Textbooks

ERIC Educational Resources Information Center

Seifert, Kelvin

2008-01-01

Recently the analysis of social networks has proved successful for understanding many educational processes, and has led to dozens of papers on a variety of education-related topics and problems (Natriello, 2005; Watts, 2005), as well as to entire books explaining network research methods both to specialists and to wider audiences (e.g. Barbabasi,…

Theory of mind mediates the prospective relationship between abnormal social brain network morphology and chronic behavior problems after pediatric traumatic brain injury.

PubMed

Ryan, Nicholas P; Catroppa, Cathy; Beare, Richard; Silk, Timothy J; Crossley, Louise; Beauchamp, Miriam H; Yeates, Keith Owen; Anderson, Vicki A

2016-04-01

Childhood and adolescence coincide with rapid maturation and synaptic reorganization of distributed neural networks that underlie complex cognitive-affective behaviors. These regions, referred to collectively as the 'social brain network' (SBN) are commonly vulnerable to disruption from pediatric traumatic brain injury (TBI); however, the mechanisms that link morphological changes in the SBN to behavior problems in this population remain unclear. In 98 children and adolescents with mild to severe TBI, we acquired 3D T1-weighted MRIs at 2-8 weeks post-injury. For comparison, 33 typically developing controls of similar age, sex and education were scanned. All participants were assessed on measures of Theory of Mind (ToM) at 6 months post-injury and parents provided ratings of behavior problems at 24-months post-injury. Severe TBI was associated with volumetric reductions in the overall SBN package, as well as regional gray matter structural change in multiple component regions of the SBN. When compared with TD controls and children with milder injuries, the severe TBI group had significantly poorer ToM, which was associated with more frequent behavior problems and abnormal SBN morphology. Mediation analysis indicated that impaired theory of mind mediated the prospective relationship between abnormal SBN morphology and more frequent chronic behavior problems. Our findings suggest that sub-acute alterations in SBN morphology indirectly contribute to long-term behavior problems via their influence on ToM. Volumetric change in the SBN and its putative hub regions may represent useful imaging biomarkers for prediction of post-acute social cognitive impairment, which may in turn elevate risk for chronic behavior problems. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Social capital, friendship networks, and youth unemployment.

PubMed

Hällsten, Martin; Edling, Christofer; Rydgren, Jens

2017-01-01

Youth unemployment is a contemporary social problem in many societies. Youths often have limited access to information about jobs and limited social influence, yet little is known about the relationship between social capital and unemployment risk among youth. We study the effect of social capital on unemployment risk in a sample of 19 year olds of Swedish, Iranian, and Yugoslavian origin living in Sweden (N = 1590). We distinguish between two dimensions of social capital: occupational contact networks and friendship networks. First, ego's unemployment is found to be strongly associated with friends' unemployment among individuals of Yugoslavian origins and individuals of Swedish origin, but not Iranian origin. Second, occupational contact networks reduce unemployment risks for all groups, but especially so for Iranians. The effect sizes of the two dimensions are similar and substantial: going from low to high values on these measures is associated with a difference of some 60-70 percent relative difference in unemployment risk. The findings are robust to a number of different model specifications, including a rich set of social origin controls, personality traits, educational performance, friends' characteristics, and friendship network characteristics, as well as controls for geographical employment patterns. A sensitivity simulation shows that homogeneity bias need to be very strong to explain away the effect. Copyright © 2016 Elsevier Inc. All rights reserved.

Social network activation: The role of health discussion partners in recovery from mental illness

PubMed Central

Perry, Brea L.; Pescosolido, Bernice A.

2014-01-01

In response to health problems, individuals may strategically activate their social network ties to help manage crisis and uncertainty. While it is well-established that social relationships provide a crucial safety net, little is known about who is chosen to help during an episode of illness. Guided by the Network Episode Model, two aspects of consulting others in the face of mental illness are considered. First, we ask who activates ties, and what kinds of ties and networks they attempt to leverage for discussing health matters. Second, we ask about the utility of activating health-focused network ties. Specifically, we examine the consequences of network activation at time of entry into treatment for individuals' quality of life, social satisfaction, ability to perform social roles, and mental health functioning nearly one year later. Using interview data from the longitudinal Indianapolis Network Mental Health Study (INMHS, N = 171), we focus on a sample of new patients with serious mental illness and a group with less severe disorders who are experiencing their first contact with the mental health treatment system. Three findings stand out. First, our results reveal the nature of agency in illness response. Whether under a rational choice or habitus logic, individuals appear to evaluate support needs, identifying the best possible matches among a larger group of potential health discussants. These include members of the core network and those with prior mental health experiences. Second, selective activation processes have implications for recovery. Those who secure adequate network resources report better outcomes than those who injudiciously activate network ties. Individuals who activate weaker relationships and those who are unsupportive of medical care experience poorer functioning, limited success in fulfilling social roles, and lower social satisfaction and quality of life later on. Third, the evidence suggests that social networks matter above and beyond the influence of any particular individual or relationship. People whose networks can be characterized as having a pro-medical culture report better recovery outcomes. PMID:24525260

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

Additional Insights Into Problem Definition and Positioning From Social Science Comment on "Four Challenges That Global Health Networks Face".

PubMed

Quissell, Kathryn

2017-09-10

Commenting on a recent editorial in this journal which presented four challenges global health networks will have to tackle to be effective, this essay discusses why this type of analysis is important for global health scholars and practitioners, and why it is worth understanding and critically engaging with the complexities behind these challenges. Focusing on the topics of problem definition and positioning, I outline additional insights from social science theory to demonstrate how networks and network researchers can evaluate these processes, and how these processes contribute to better organizing, advocacy, and public health outcomes. This essay also raises multiple questions regarding these processes for future research. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Influence of network topology on cooperative problem-solving systems.

PubMed

Fontanari, José F; Rodrigues, Francisco A

2016-09-01

The idea of a collective intelligence behind the complex natural structures built by organisms suggests that the organization of social networks is selected so as to optimize problem-solving competence at the group level. Here we study the influence of the social network topology on the performance of a group of agents whose task is to locate the global maxima of NK fitness landscapes. Agents cooperate by broadcasting messages informing on their fitness and use this information to imitate the fittest agent in their influence networks. In the case those messages convey accurate information on the proximity of the solution (i.e., for smooth fitness landscapes), we find that high connectivity as well as centralization boosts the group performance. For rugged landscapes, however, these characteristics are beneficial for small groups only. For large groups, it is advantageous to slow down the information transmission through the network to avoid local maximum traps. Long-range links and modularity have marginal effects on the performance of the group, except for a very narrow region of the model parameters.

Interacting with Users in Social Networks: The Follow-back Problem

DTIC Science & Technology

2016-05-02

interacting with the friends of the target(s). Because forming a connection is known as following in social networks such as Twitter , we refer to this as...of an interaction resulting in a follow-back, we conduct an empirical analysis of several thousand interactions in Twitter . We build a model of the...define as the followback score. We show through simulation that these heuristic policies perform well on real Twitter graphs. Thesis Supervisor: Dr

Information spread of emergency events: path searching on social networks.

PubMed

Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

Using the D-Wave 2X Quantum Computer to Explore the Formation of Global Terrorist Networks

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

Ambrosiano, John Joseph; Roberts, Randy Mark; Sims, Benjamin Hayden

Social networks with signed edges (+/-) play an important role in an area of social network theory called structural balance. In these networks, edges represent relationships that are labeled as either friendly (+) or hostile (-). A signed social network is balanced only if all cycles of three or more nodes in the graph have an odd number of hostile edges. A fundamental property of a balanced network is that it can be cleanly divided into 2 factions, where all relationships within each faction are friendly, and all relationships between members of different factions are hostile. The more unbalanced amore » network is, the more edges will fail to adhere to this rule, making factions more ambiguous. Social theory suggests unbalanced networks should be unstable, a finding that has been supported by research on gangs, which shows that unbalanced relationships are associated with greater violence, possibly due to this increased ambiguity about factional allegiances (Nakamura et al). One way to estimate the imbalance in a network, if only edge relationships are known, is to assign nodes to factions that minimize the number of violations of the edge rule described above. This problem is known to be computationally NP-hard. However, Facchetti et al. have pointed out that it is equivalent to an Ising model with a Hamiltonian that effectively counts the number of edge rule violations. Therefore, finding the assignment of factions that minimizes energy of the equivalent Ising system yields an estimate of the imbalance in the network. Based on the Ising model equivalence of the signed-social network balance problem, we have used the D-Wave 2X quantum annealing computer to explore some aspects of signed social networks. Because connectivity in the D-Wave computer is limited to its particular native topology, arbitrary networks cannot be represented directly. Rather, they must be “embedded” using a technique in which multiple qubits are chained together with special weights to simulate a collection of nodes with the required connectivity. This limits the size of a fully connected network in the D-Wave to about 50 simulated nodes, using all of the approximately 1150 qubits in the machine. In order to keep within this limitation, while exploring a problem of potential social relevance, we constructed time series of historical network snapshots from Stanford’s Mapping Militants Project, where nodes represent militant organizations, and edges represent either alliances or rivalries between organizations. We constructed two series from different theaters – Iraq and Syria – spanning timelines from about 2000 to 2016, each with networks whose maximum size was in the 20-30 node range. Computationally, our experience suggests D-Wave technology is promising, providing fast, nearly constant scaling of computational effort in the main part of the calculation that relies on the quantum annealing cycle. However, the cost of embedding an arbitrary network of interest in the D-Wave native topology scales poorly. If the embedding cost can be amortized relative to the annealing cycle, it may be possible to gain a substantial advantage over classical computing methods, provided a large enough network can be accommodated by partitioning into subnetworks or some similar strategy. In terms of our application to networks of militant organizations, we found a rise in network imbalance in the Syrian theater that appears to correspond roughly with the entrance of the Islamic State into a milieu already populated with other groups, a phenomenon we plan to explore in more detail. In these very preliminary results, we also noticed that during at least one period where both the size and imbalance of the network increased substantially, the imbalance per edge seemed to remain fairly steady. This may suggest some adaptive behavior among the participating factions, which may also warrant further exploration.« less

[Physician's anxiety and physician's elegance. Problems in dealing with cost reduction, education of general practitioners and optimal size of practice networks in a cross-national comparison].

PubMed

Behrens, J

2000-03-01

The key reason for physicians networking in managed care is to get a better coping with uncertainty on action (treatment) decisions. The second reason for networking in managed care are financial benefits grounds. But this reason is very ambivalent. Three different action problems (role conflicts) in managed care network are to solved, which was also in single practices. In the lecture the decision strategies and decision resources has been compared. Observations are done using expert interviews, patient interviews and analysis of documents in USA, Germany and Switzerland. The first problem is the choosing of a cost reduction strategy which is not reducing the effectiveness. Such "ugly" solution strategies like exclusion of "expensive" patients and a rationing of necessary medical services in a kind of McDonalds network of physicians will fail the target. The optimost way is a saving of all unnecessary medical even injourious performances. The chosen cost reduction strategy is not real visible from outside but in fact limited cognizable and controllable. Evidence based health care can be a resource of treatment decisions and could train such decisions but it will not substitute these decisions. The second problem is the making of real family practitioners as gatekeepers. Knowledge about the care system is still not making a real family practitioner, even if this is the minimum condition of their work. Also contractual relationships between insurance and doctor as a gatekeeper or financial incentives for patients are still making not a real family practitioner as a gatekpeeper. Only throughout the trust of patients supported by second opinions is making the real family practitioner as a gatekeeper. "Doctor hopping" could be the reaction by scarcity of trustworthy family practitioners as gatekeepers. The third problem is the choosing of the optimal scale of a network due to the very different optimal size of networks regarding the requirement of risk spreeds, of the motivated engagement, of competition, incentives of inclusion of insurantes, they always need other net sizes. But it is possible, for each requirement there could function different networks. A practice (doctor's office) can be a member in different networks in several levels. The social transition from a small office to a network of offices is in all business lines a cultural shock involving not only benefits also psychical and social distress. In this there is no difference between health or agriculture or each other business of trade and industry. The destiny of the joint doctor's offices in Germany suggest due to a very serious power to scatter this networks. The comparative analysis of conflicts, strains, resources and strategies of associations and networks could yield from a developed methodical repository in sociology and social psychology what exists since 40 years (see also Meyer--in this journal). But therefore must be included also the action problems, which are only mentioned in passing of the according profession horizon.

Social influences on corporate political donations in Britain.

PubMed

Bond, Matthew

2004-03-01

It is argued that institutional features of the British state create collective action problems for the mobilization of corporations as donors to the Conservative Party. Social factors are necessary for overcoming these problems. Using social network analyses, the effect that interlocking directorates have on 250 large British corporations' decisions to donate are analysed. Instead of the central mobilizing factor being diffuse inner circle mechanisms positively influencing the decision to make a donation, the results show that more particularistic mechanisms such as information bias and control are equally important.

Cooperative networks overcoming defectors by social influence

NASA Astrophysics Data System (ADS)

Gomez Portillo, Ignacio

2014-01-01

We address the cooperation problem in structured populations by considering the prisoner’s dilemma game as a metaphor of the social interactions between individuals with imitation capacity. We present a new strategy update rule called democratic weighted update where the individual’s behavior is socially influenced by each one of their neighbors. In particular, the capacity of an individual to socially influence other ones is proportional to its accumulated payoff. When in a neighborhood there are cooperators and defectors, the focal player is contradictorily influenced by them and, therefore, the effective social influence is given by the difference of the accumulated payoff of each strategy in its neighborhood. First, by considering the growing process of the network and neglecting mutations, we show the evolution of highly cooperative systems. Then, we broadly show that the social influence allows to overcome the emergence of defectors into highly cooperative systems. In this way, we conclude that in a structured system formed by a growing process, the cooperation evolves if the individuals have an imitation capacity socially influenced by each one of their neighbors. Therefore, here we present a theoretical solution of the cooperation problem among genetically unrelated individuals.

Social support and intellectual disabilities: a comparison between social networks of adults with intellectual disability and those with physical disability.

PubMed

Lippold, T; Burns, J

2009-05-01

Social support has been identified as a major protective factor in preventing mental health problems and also as a major contributor to quality of life. People with intellectual disabilities (ID) have been identified as having limited social support structures. Interventions have been focused on promoting their social presence and integration. However, previous studies have shown that this does not always lead to the formation of social relationships. To date few studies have looked at how having an ID leads to impoverished social networks. This study aimed to do this by contrasting the social relationships of people with physical disabilities (PD) and people with ID. Two groups of participants were recruited; 30 people with mild ID and 17 people with PD. Social and functional support networks were assessed, in addition to life experiences. Between and within group differences were then explored statistically. Adults with ID had more restricted social networks than PD, despite being involved in more activities. Social support for adults with ID was mainly provided by family and carers and few relationships with non-disabled people were identified. In contrast adults with PD had larger social networks than had been reported in the mainstream literature and had a balance of relationships with disabled and non-disabled people. The results suggest that there are additional processes attached to having an ID, which lead to continued impoverished lifestyles. The findings also endorse other work that suggests being physically integrated and engaged in a wide range of activities does not guarantee good social and emotional support.

Increasing Scalability of Researcher Network Extraction from the Web

NASA Astrophysics Data System (ADS)

Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

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

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

NASA Astrophysics Data System (ADS)

Lawless, William F.

2017-08-01

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

Determinants of quality of life in children with psychiatric disorders.

PubMed

Bastiaansen, Dennis; Koot, Hans M; Ferdinand, Robert F

2005-08-01

To assess factors that, in addition to childhood psychopathology, are associated with Quality of Life (QoL) in children with psychiatric problems. In a referred sample of 252 8 to 18-year-olds, information concerning QoL, psychopathology and a broad range of child, parent, and family/ social network factors was obtained from children, parents, teachers and clinicians. Poor child, parent, and clinician reported QoL was associated with child psychopathology, but given the presence of psychopathology, also with child factors, such as low self-esteem, and poor social skills, and family/social network factors, such as poor family functioning, and poor social support. In multiple linear regression analyses the importance of parent factors, such as parenting stress, was almost negligible. To increase QoL of children with psychiatric problems, treatment of symptoms is important, but outcome might improve if treatment is also focussed on other factors that may affect QoL. Results are discussed in relation to current treatment programs.

Pigeons, Facebook and the Birthday Problem

ERIC Educational Resources Information Center

Russell, Matthew

2013-01-01

The unexpectedness of the birthday problem has long been used by teachers of statistics in discussing basic probability calculation. An activity is described that engages students in understanding probability and sampling using the popular Facebook social networking site. (Contains 2 figures and 1 table.)

The Transmission of Gun and Other Weapon-Involved Violence Within Social Networks.

PubMed

Tracy, Melissa; Braga, Anthony A; Papachristos, Andrew V

2016-01-01

Fatal and nonfatal injuries resulting from gun violence remain a persistent problem in the United States. The available research suggests that gun violence diffuses among people and across places through social relationships. Understanding the relationship between gun violence within social networks and individual gun violence risk is critical in preventing the spread of gun violence within populations. This systematic review examines the existing scientific evidence on the transmission of gun and other weapon-related violence in household, intimate partner, peer, and co-offending networks. Our review identified 16 studies published between 1996 and 2015 that suggest that exposure to a victim or perpetrator of violence in one's interpersonal relationships and social networks increases the risk of individual victimization and perpetration. Formal network analyses find high concentrations of gun violence in small networks and that exposure to gun violence in one's networks is highly correlated with one's own probability of being a gunshot victim. Physical violence by parents and weapon use by intimate partners also increase risk for victimization and perpetration. Additional work is needed to better characterize the mechanisms through which network exposures increase individual risk for violence and to evaluate interventions aimed at disrupting the spread of gun and other weapon violence in high-risk social networks. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Information filtering via biased random walk on coupled social network.

PubMed

Nie, Da-Cheng; Zhang, Zi-Ke; Dong, Qiang; Sun, Chongjing; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.

Information Filtering via Biased Random Walk on Coupled Social Network

PubMed Central

Dong, Qiang; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods. PMID:25147867

Social competence promotion with inner-city and suburban young adolescents: effects on social adjustment and alcohol use.

PubMed

Caplan, M; Weissberg, R P; Grober, J S; Sivo, P J; Grady, K; Jacoby, C

1992-02-01

This study assessed the impact of school-based social competence training on skills, social adjustment, and self-reported substance use of 282 sixth and seventh graders. Training emphasized broad-based competence promotion in conjunction with domain-specific application to substance abuse prevention. The 20-session program comprised six units: stress management, self-esteem, problem solving, substances and health information, assertiveness, and social networks. Findings indicated positive training effects on Ss' skills in handling interpersonal problems and coping with anxiety. Teacher ratings revealed improvements in Ss' constructive conflict resolution with peers, impulse control, and popularity. Self-report ratings indicated gains in problem-solving efficacy. Results suggest some preventive impact on self-reported substance use intentions and excessive alcohol use. In general, the program was found to be beneficial for both inner-city and suburban students.

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.

Cost effective campaigning in social networks

NASA Astrophysics Data System (ADS)

Kotnis, Bhushan; Kuri, Joy

2016-05-01

Campaigners are increasingly using online social networking platforms for promoting products, ideas and information. A popular method of promoting a product or even an idea is incentivizing individuals to evangelize the idea vigorously by providing them with referral rewards in the form of discounts, cash backs, or social recognition. Due to budget constraints on scarce resources such as money and manpower, it may not be possible to provide incentives for the entire population, and hence incentives need to be allocated judiciously to appropriate individuals for ensuring the highest possible outreach size. We aim to do the same by formulating and solving an optimization problem using percolation theory. In particular, we compute the set of individuals that are provided incentives for minimizing the expected cost while ensuring a given outreach size. We also solve the problem of computing the set of individuals to be incentivized for maximizing the outreach size for given cost budget. The optimization problem turns out to be non trivial; it involves quantities that need to be computed by numerically solving a fixed point equation. Our primary contribution is, that for a fairly general cost structure, we show that the optimization problems can be solved by solving a simple linear program. We believe that our approach of using percolation theory to formulate an optimization problem is the first of its kind.

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 Networks in Improvement of Health Care

PubMed Central

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

2012-01-01

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

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

PubMed

Szczegielniak, Anna; Pałka, Karol; Krysta, Krzysztof

2013-09-01

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

Building Social Networks for Health Promotion: Shout-out Health, New Jersey, 2011

PubMed Central

Jones, Veronica M.; Storm, Deborah S.; Parrott, J. Scott; O’Brien, Kathy Ahearn

2013-01-01

Background Building social networks for health promotion in high-poverty areas may reduce health disparities. Community involvement provides a mechanism to reach at-risk people with culturally tailored health information. Shout-out Health was a feasibility project to provide opportunity and support for women at risk for or living with human immunodeficiency virus infection to carry out health promotion within their informal social networks. Community Context The Shout-out Health project was designed by an academic–community agency team. During 3 months, health promotion topics were chosen, developed, and delivered to community members within informal social networks by participants living in Paterson and Jersey City, New Jersey. Methods We recruited women from our community agency partner’s clients; 57 women participated in in-person or online meetings facilitated by our team. The participants identified and developed the health topics, and we discussed each topic and checked it for message accuracy before the participants provided health promotion within their informal social networks. The primary outcome for evaluating feasibility included the women’s feedback about their experiences and the number of times they provided health promotion in the community. Other data collection included participant questionnaires and community-recipient evaluations. Outcome More than half of the participants reported substantial life challenges, such as unemployment and housing problems, yet with technical support and a modest stipend, women in both groups successfully provided health promotion to 5,861 people within their informal social networks. Interpretation Shout-out Health was feasible and has implications for building social networks to disseminate health information and reduce health disparities in communities. PMID:23987253

Leveraging Social Links for Trust and Privacy in Networks

NASA Astrophysics Data System (ADS)

Cutillo, Leucio Antonio; Molva, Refik; Strufe, Thorsten

Existing on-line social networks (OSN) such as Facebook suffer from several weaknesses regarding privacy and security due to their inherent handling of personal data. As pointed out in [4], a preliminary analysis of existing OSNs shows that they are subject to a number of vulnerabilities, ranging from cloning legitimate users to sybil attacks through privacy violations. Starting from these OSN vulnerabilities as the first step of a broader research activity, we came up with a new approach that is very promising in re-visiting security and privacy problems in distributed systems and networks. We suggest a solution that both aims at avoiding any centralized control and leverages on the real life trust between users, that is part of the social network application itself. An anonymization technique based on multi-hop routing among trusted nodes guarantees privacy in data access and, generally speaking, in all the OSN operations.

Distributed micro-releases of bioterror pathogens : threat characterizations and epidemiology from uncertain patient observables.

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

Wolf, Michael M.; Marzouk, Youssef M.; Adams, Brian M.

2008-10-01

Terrorist attacks using an aerosolized pathogen preparation have gained credibility as a national security concern since the anthrax attacks of 2001. The ability to characterize the parameters of such attacks, i.e., to estimate the number of people infected, the time of infection, the average dose received, and the rate of disease spread in contemporary American society (for contagious diseases), is important when planning a medical response. For non-contagious diseases, we address the characterization problem by formulating a Bayesian inverse problem predicated on a short time-series of diagnosed patients exhibiting symptoms. To keep the approach relevant for response planning, we limitmore » ourselves to 3.5 days of data. In computational tests performed for anthrax, we usually find these observation windows sufficient, especially if the outbreak model employed in the inverse problem is accurate. For contagious diseases, we formulated a Bayesian inversion technique to infer both pathogenic transmissibility and the social network from outbreak observations, ensuring that the two determinants of spreading are identified separately. We tested this technique on data collected from a 1967 smallpox epidemic in Abakaliki, Nigeria. We inferred, probabilistically, different transmissibilities in the structured Abakaliki population, the social network, and the chain of transmission. Finally, we developed an individual-based epidemic model to realistically simulate the spread of a rare (or eradicated) disease in a modern society. This model incorporates the mixing patterns observed in an (American) urban setting and accepts, as model input, pathogenic transmissibilities estimated from historical outbreaks that may have occurred in socio-economic environments with little resemblance to contemporary society. Techniques were also developed to simulate disease spread on static and sampled network reductions of the dynamic social networks originally in the individual-based model, yielding faster, though approximate, network-based epidemic models. These reduced-order models are useful in scenario analysis for medical response planning, as well as in computationally intensive inverse problems.« less

Epidemic spreading in networks with nonrandom long-range interactions

NASA Astrophysics Data System (ADS)

Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

2011-09-01

An “infection,” understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both “close” contacts and “casual” encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called “conductance” controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

Epidemic spreading in networks with nonrandom long-range interactions.

PubMed

Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

2011-09-01

An "infection," understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both "close" contacts and "casual" encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called "conductance" controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

Information Spread of Emergency Events: Path Searching on Social Networks

PubMed Central

Hu, Hongzhi; Wu, Tunan

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Cooperative Networks: Altruism, Group Solidarity, Reciprocity, and Sanctioning in Ugandan Producer Organizations.

PubMed

Baldassarri, Delia

2015-09-01

Repeated interaction and social networks are commonly considered viable solutions to collective action problems. This article identifies and systematically measures four general mechanisms--that is, generalized altruism, group solidarity, reciprocity, and the threat of sanctioning--and tests which of them brings about cooperation in the context of Ugandan producer organizations. Using an innovative methodological framework that combines "lab-in-the-field" experiments with survey interviews and complete social networks data, the article goes beyond the assessment of a relationship between social networks and collective outcomes to study the mechanisms that favor cooperative behavior. The article first establishes a positive relationship between position in the network structure and propensity to cooperate in the producer organization and then uses farmers' behavior in dictator and public goods games to test different mechanisms that may account for such a relationship. Results show that cooperation is induced by patterns of reciprocity that emerge through repeated interaction rather than other-regarding preferences like altruism or group solidarity.

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

NASA Astrophysics Data System (ADS)

Grewe, L.

2013-05-01

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

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

PubMed

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

2015-06-11

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

Supporting wellbeing in motor neurone disease for patients, carers, social networks, and health professionals: A scoping review and synthesis.

PubMed

Harris, Melanie; Thomas, Geoff; Thomas, Mary; Cafarella, Paul; Stocks, Allegra; Greig, Julia; McEvoy, R Doug

2018-04-01

ABSTRACTObjective:Disease management in motor neurone disease (MND) is focused on preserving quality of life. However, the emphasis has so far been on physical symptoms and functioning and not psychosocial wellbeing. MND affects the wellbeing of carers, of family and social network members, and of healthcare providers, as well as of the patients. We therefore aimed to assess and synthesize the knowledge about maximizing MND-related psychosocial wellbeing across all these groups. We used a systematic search and selection process to assess the scope of the literature along with a narrative synthesis of recent high-quality reviews. The original studies were mainly observational studies of patients and, to a lesser extent, of carers. There were few interventional studies, mainly of patients. There were very few studies of any type on wellbeing in their wider social network or in healthcare professionals. All the review literature looked at MND patient or carer wellbeing, with some covering both. No reviews were found of wellbeing in other family members, patients' social networks, or their healthcare professionals. The reviews demonstrated wellbeing problems for patients linked to psychosocial issues. Carer wellbeing is also compromised. Psychotherapies, social supports, improved decision supports, and changes to healthcare delivery are among the suggested strategies for improved patient and carer wellbeing, but no proven interventions were identified for either. Early access to palliative care, also not well-tested but recommended, is poorly implemented. Work on interventions to deal with well-established wellbeing problems for patients and carers is now a research priority. Explicit use of current methods for patient and public involvement and for design and testing of interventions provide a toolkit for this research. Observational research is needed in other groups. There is a potential in considering needs across patients' social networks rather than looking individually at particular groups.

Privacy policies for health social networking sites.

PubMed

Li, Jingquan

2013-01-01

Health social networking sites (HSNS), virtual communities where users connect with each other around common problems and share relevant health data, have been increasingly adopted by medical professionals and patients. The growing use of HSNS like Sermo and PatientsLikeMe has prompted public concerns about the risks that such online data-sharing platforms pose to the privacy and security of personal health data. This paper articulates a set of privacy risks introduced by social networking in health care and presents a practical example that demonstrates how the risks might be intrinsic to some HSNS. The aim of this study is to identify and sketch the policy implications of using HSNS and how policy makers and stakeholders should elaborate upon them to protect the privacy of online health data.

Privacy policies for health social networking sites

PubMed Central

Li, Jingquan

2013-01-01

Health social networking sites (HSNS), virtual communities where users connect with each other around common problems and share relevant health data, have been increasingly adopted by medical professionals and patients. The growing use of HSNS like Sermo and PatientsLikeMe has prompted public concerns about the risks that such online data-sharing platforms pose to the privacy and security of personal health data. This paper articulates a set of privacy risks introduced by social networking in health care and presents a practical example that demonstrates how the risks might be intrinsic to some HSNS. The aim of this study is to identify and sketch the policy implications of using HSNS and how policy makers and stakeholders should elaborate upon them to protect the privacy of online health data. PMID:23599228

Life Events, Social Support, and Immune Response in Elderly Individuals.

ERIC Educational Resources Information Center

McIntosh, William Alex; And Others

1993-01-01

Investigated effects of recent life events, psychological adjustment, and social support on lymphocyte count among 192 older adults. For males, recent sexual dysfunction lowered lymphocyte count, whereas psychological adjustment and percentage kin in intimate network elevated it. For females, family or legal problems elevated count as did frequent…

Understanding Social Support Burden Among Family Caregivers

PubMed Central

Washington, Karla; Demiris, George; Parker Oliver, Debra; Shaunfield, Sara

2014-01-01

Despite the abundance of research on social support, both as a variable in larger studies and as a central focus of examination, there is little consensus about the relationship between social support and health outcomes. Current social support measures typically account only for frequency and size of network and a paucity of research exists that has explained social support burden, defined as the burden associated with accessing and receiving support from others. We analyzed audio-recorded discussions by hospice family caregivers about their caregiving problems and potential solutions to examine social relationships within networks and identify the processes that influence social support seeking and receiving. Using qualitative thematic analysis, we found that caregivers providing hospice care experience social support burden resulting from perceived relational barriers between friends and family, the inclination to remain in control, recognition of the loss of the patient as a source of social support and guidance in decision-making, family dynamics and decreased availability of emotional support. Social support researchers should consider how the quality of communication and relationships within social networks impacts the provision and subsequent outcomes of social support in varying contexts. Findings from this study suggest that hospice social support resources should be tailored to the caregiver’s support needs and include assessment on the type of support to be offered. PMID:24345081

Social network activation: the role of health discussion partners in recovery from mental illness.

PubMed

Perry, Brea L; Pescosolido, Bernice A

2015-01-01

In response to health problems, individuals may strategically activate their social network ties to help manage crisis and uncertainty. While it is well-established that social relationships provide a crucial safety net, little is known about who is chosen to help during an episode of illness. Guided by the Network Episode Model, two aspects of consulting others in the face of mental illness are considered. First, we ask who activates ties, and what kinds of ties and networks they attempt to leverage for discussing health matters. Second, we ask about the utility of activating health-focused network ties. Specifically, we examine the consequences of network activation at time of entry into treatment for individuals' quality of life, social satisfaction, ability to perform social roles, and mental health functioning nearly one year later. Using interview data from the longitudinal Indianapolis Network Mental Health Study (INMHS, N = 171), we focus on a sample of new patients with serious mental illness and a group with less severe disorders who are experiencing their first contact with the mental health treatment system. Three findings stand out. First, our results reveal the nature of agency in illness response. Whether under a rational choice or habitus logic, individuals appear to evaluate support needs, identifying the best possible matches among a larger group of potential health discussants. These include members of the core network and those with prior mental health experiences. Second, selective activation processes have implications for recovery. Those who secure adequate network resources report better outcomes than those who injudiciously activate network ties. Individuals who activate weaker relationships and those who are unsupportive of medical care experience poorer functioning, limited success in fulfilling social roles, and lower social satisfaction and quality of life later on. Third, the evidence suggests that social networks matter above and beyond the influence of any particular individual or relationship. People whose networks can be characterized as having a pro-medical culture report better recovery outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Systematic Review of the Physical, Mental, Social, and Economic Problems of Immigrant Women in the Perinatal Period in Japan.

PubMed

Kita, Sachiko; Minatani, Mariko; Hikita, Naoko; Matsuzaki, Masayo; Shiraishi, Mie; Haruna, Megumi

2015-12-01

The perinatal mortality of immigrants in Japan is higher than that of Japanese women. However, details of the problems of immigrant perinatal women that contribute to worsening of their health are still unknown. This review describes the physical, psychological, social, and economic problems of immigrant women during the perinatal period in Japan. Medline, CINAHL, PsycINFO, and Igaku-Chuo Zasshi were searched and 36 relevant articles were reviewed. The related descriptions were collected and analyzed by using content analysis. The results showed that immigrant perinatal women in Japan experienced the following problems: language barriers, a problematic relationship with a partner, illegal residency, emotional distress, physical distress, adjustment difficulties, lack of utilization of services, social isolation, lack of support, lack of information, low economic status, unsatisfactory health care, and discrimination. These results indicated that multilingual services, strengthening of social and support networks, and political action are necessary to resolve their problems.

An alter-centric perspective on employee innovation: The importance of alters' creative self-efficacy and network structure.

PubMed

Grosser, Travis J; Venkataramani, Vijaya; Labianca, Giuseppe Joe

2017-09-01

While most social network studies of employee innovation behavior examine the focal employees' ("egos'") network structure, we employ an alter-centric perspective to study the personal characteristics of employees' network contacts-their "alters"-to better understand employee innovation. Specifically, we examine how the creative self-efficacy (CSE) and innovation behavior of employees' social network contacts affects their ability to generate and implement novel ideas. Hypotheses were tested using a sample of 144 employees in a U.S.-based product development organization. We find that the average CSE of alters in an employee's problem solving network is positively related to that employee's innovation behavior, with this relationship being mediated by these alters' average innovation behavior. The relationship between the alters' average innovation behavior and the employee's own innovation behavior is strengthened when these alters have less dense social networks. Post hoc results suggest that having network contacts with high levels of CSE also leads to an increase in ego's personal CSE 1 year later in cases where the employee's initial level of CSE was relatively low. Implications for theory and practice are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The effects of social capital and neighborhood characteristics on intimate partner violence: a consideration of social resources and risks.

PubMed

Kirst, Maritt; Lazgare, Luis Palma; Zhang, Yu Janice; O'Campo, Patricia

2015-06-01

Intimate partner violence (IPV) is a growing public health problem, and gaps exist in knowledge with respect to appropriate prevention and treatment strategies. A growing body of research evidence suggests that beyond individual factors (e.g., socio-economic status, psychological processes, substance abuse problems), neighborhood characteristics, such as neighborhood economic disadvantage, high crime rates, high unemployment and social disorder, are associated with increased risk for IPV. However, existing research in this area has focused primarily on risk factors inherent in neighborhoods, and has failed to adequately examine resources within social networks and neighborhoods that may buffer or prevent the occurrence of IPV. This study examines the effects of neighborhood characteristics, such as economic disadvantage and disorder, and individual and neighborhood resources, such as social capital, on IPV among a representative sample of 2412 residents of Toronto, Ontario, Canada. Using a population based sample of 2412 randomly selected Toronto adults with comprehensive neighborhood level data on a broad set of characteristics, we conducted multi-level modeling to examine the effects of individual- and neighborhood-level effects on IPV outcomes. We also examined protective factors through a comprehensive operationalization of the concept of social capital, involving neighborhood collective efficacy, community group participation, social network structure and social support. Findings show that residents who were involved in one or more community groups in the last 12 months and had high perceived neighborhood problems were more likely to have experienced physical IPV. Residents who had high perceived social support and low perceived neighborhood problems were less likely to experience non-physical IPV. These relationships did not differ by neighborhood income or gender. Findings suggest interesting contextual effects of social capital on IPV. Consistent with previous research, higher levels of perceived neighborhood problems can reflect disadvantaged environments that are more challenged in promoting health and regulating disorder, and can create stressors in which IPV is more likely to occur. Such analyses will be helpful to further understanding of the complex, multi-level pathways related to IPV and to inform the development of effective programs and policies with which to address and prevent this serious public health issue.

Money and Mental Illness: A Study of the Relationship Between Poverty and Serious Psychological Problems.

PubMed

Ljungqvist, Ingemar; Topor, Alain; Forssell, Henrik; Svensson, Idor; Davidson, Larry

2016-10-01

Several studies have indicated a co-occurrence between mental problems, a bad economy, and social isolation. Medical treatments focus on reducing the extent of psychiatric problems. Recent research, however, has highlighted the possible effects of social initiatives. The aim of this study was to examine the relation between severe mental illness, economic status, and social relations. a financial contribution per month was granted to 100 individuals with severe mental illnesses for a 9-month period. Assessments of the subjects were made before the start of the intervention and after 7 months' duration. A comparison group including treatment as usual only was followed using the same instruments. Significant improvements were found for depression and anxiety, social networks, and sense of self. No differences in functional level were found. Social initiatives may have treatment and other beneficial effects and should be integrated into working contextually with persons with severe mental illnesses.

Social pressure, coercion, and client engagement at treatment entry: a self-determination theory perspective.

PubMed

Wild, T Cameron; Cunningham, John A; Ryan, Richard M

2006-10-01

Research on coercion in addiction treatment typically investigates objective sources of social pressure among legally mandated clients. Little research has examined the impact of clients' perceptions of social pressures in generalist addiction services. Clients seeking substance abuse treatment (N=300; 221 males and 79 females; M age=36.6 years) rated the extent to which treatment was being sought because of coercive social pressures (external motivation; alpha=.89), guilt about continued substance abuse (introjected motivation; alpha=.84), or a personal choice and commitment to the goals of the program (identified motivation; alpha=.85). External treatment motivation was positively correlated with legal referral, social network pressures to enter treatment, and was inversely related to problem severity. In contrast, identified treatment motivation was positively correlated with self-referral and problem severity, and was inversely related to perceived coercion (ps<.05). Hierarchical multiple regression analyses showed that referral source (i.e., mandated treatment status), legal history, and social network pressures did not predict any of 6 measures of client engagement at the time treatment was sought. However, treatment motivation variables accounted for unique variance in these outcomes when added to each model (DeltaR(2)s=.06-.23, ps<.05). Specifically, identified treatment motivation predicted perceived benefits of reducing substance use, attempts to reduce drinking and drug use, as well as self (and therapist) ratings of interest in the upcoming treatment episode (betas=.18-.31, ps<.05). Results suggest that the presence of legal referral and/or social network pressures to quit, cut down, and/or enter treatment does not affect client engagement at treatment entry.

Getting the complete picture: combining parental and child data to identify the barriers to social inclusion for children living in low socio-economic areas.

PubMed

Davies, B; Davis, E; Cook, K; Waters, E

2008-03-01

Childhood mental health problems are prevalent in Australian children (14-20%). Social exclusion is a risk factor for mental health problems, whereas being socially included can have protective effects. This study aims to identify the barriers to social inclusion for children aged 9-12 years living in low socio-economic status (SES) areas, using both child-report and parent-report interviews. Australian-born English-speaking parents and children aged 9-12 years were sampled from a low SES area to participate in semi-structured interviews. Parents and children were asked questions around three prominent themes of social exclusion; exclusion from school, social activities and social networks. Many children experienced social exclusion at school, from social activities or within social networks. Overall, nine key barriers to social inclusion were identified through parent and child interviews, such as inability to attend school camps and participate in school activities, bullying and being left out, time and transport constraints, financial constraints and safety and traffic concerns. Parents and children often identified different barriers. There are several barriers to social inclusion for children living in low SES communities, many of which can be used to facilitate mental health promotion programmes. Given that parents and children may report different barriers, it is important to seek both perspectives. This study strengthens the evidence base for the investments and action required to bring about the conditions for social inclusion for children living in low SES communities.

Descriptive and Injunctive Network Norms Associated with Non Medical Use of Prescription Drugs among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2016-01-01

Background Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. Methods 1,046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Results Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Conclusions Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths’ perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. PMID:27563741

Descriptive and injunctive network norms associated with nonmedical use of prescription drugs among homeless youth.

PubMed

Barman-Adhikari, Anamika; Al Tayyib, Alia; Begun, Stephanie; Bowen, Elizabeth; Rice, Eric

2017-01-01

Nonmedical use of prescription drugs (NMUPD) among youth and young adults is being increasingly recognized as a significant public health problem. Homeless youth in particular are more likely to engage in NMUPD compared to housed youth. Studies suggest that network norms are strongly associated with a range of substance use behaviors. However, evidence regarding the association between network norms and NMUPD is scarce. We sought to understand whether social network norms of NMUPD are associated with engagement in NMUPD among homeless youth. 1046 homeless youth were recruited from three drop-in centers in Los Angeles, CA and were interviewed regarding their individual and social network characteristics. Multivariate logistic regression was employed to evaluate the significance of associations between social norms (descriptive and injunctive) and self-reported NMUPD. Approximately 25% of youth reported past 30-day NMUPD. However, more youth (32.28%) of youth believed that their network members engage in NMUPD, perhaps suggesting some pluralistic ignorance bias. Both descriptive and injunctive norms were associated with self-reported NMUPD among homeless youth. However, these varied by network type, with presence of NMUPD engaged street-based and home-based peers (descriptive norm) increasing the likelihood of NMUPD, while objections from family-members (injunctive norm) decreasing that likelihood. Our findings suggest that, like other substance use behaviors, NMUPD is also influenced by youths' perceptions of the behaviors of their social network members. Therefore, prevention and interventions programs designed to influence NMUPD might benefit from taking a social network norms approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fast and Accurate Detection of Spread Source in Large Complex Networks

DTIC Science & Technology

the patient one in epidemics, or source of rumor spreading in social network. Pinto, Thiran and Vetterli introduced an algorithm (PTVA) to solve the...important case of this problem in which a limited set of nodes act as observers and report times at which the spread reached them. PTVA uses all

Time development in the early history of social networks: link stabilization, group dynamics, and segregation.

PubMed

Bruun, Jesper; Bearden, Ian G

2014-01-01

Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks' communities show that while student movement between groups are erratic in the beginning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately available to them and on observable personal characteristics.

Social networks and community prevention coalitions.

PubMed

Feinberg, Mark E; Riggs, Nathaniel R; Greenberg, Mark T

2005-07-01

This study investigates the links between community readiness and the social networks among participants in Communities That Care (CTC), community-based prevention coalitions. The coalitions targeted adolescent behavior problems through community risk factor assessments, prioritization of risk factors, and selection/implementation of corresponding evidence-based family, school, and community programs. Key leaders (n = 219) in 23 new CTC sites completed questionnaires focusing on community readiness to implement CTC and the respondents' personal, work, and social organization links to other key leaders in the community. Outside technical assistants also completed ratings of each community's readiness and early CTC functioning. Measures of network cohesion/integration were positively associated with readiness, while centralization was negatively associated. These results suggest that non-centralized networks in which ties between members are close and direct may be an indicator of community readiness. In addition, we found different associations between readiness and different domains of social relations. EDITORS' STRATEGIC IMPLICATIONS: The authors present the promising practice of using social network analysis to characterize the functioning of local prevention coalitions and their readiness to implement a community-based prevention initiative. Researchers and community planners will benefit from the lessons in this article, which capitalizes on a large sample and multiple informants. This work raises interesting questions about how to combine the promotion of coalition functioning while simultaneously encouraging diversity of coalition membership.

A computer-assisted motivational social network intervention to reduce alcohol, drug and HIV risk behaviors among Housing First residents.

PubMed

Kennedy, David P; Hunter, Sarah B; Chan Osilla, Karen; Maksabedian, Ervant; Golinelli, Daniela; Tucker, Joan S

2016-03-15

Individuals transitioning from homelessness to housing face challenges to reducing alcohol, drug and HIV risk behaviors. To aid in this transition, this study developed and will test a computer-assisted intervention that delivers personalized social network feedback by an intervention facilitator trained in motivational interviewing (MI). The intervention goal is to enhance motivation to reduce high risk alcohol and other drug (AOD) use and reduce HIV risk behaviors. In this Stage 1b pilot trial, 60 individuals that are transitioning from homelessness to housing will be randomly assigned to the intervention or control condition. The intervention condition consists of four biweekly social network sessions conducted using MI. AOD use and HIV risk behaviors will be monitored prior to and immediately following the intervention and compared to control participants' behaviors to explore whether the intervention was associated with any systematic changes in AOD use or HIV risk behaviors. Social network health interventions are an innovative approach for reducing future AOD use and HIV risk problems, but little is known about their feasibility, acceptability, and efficacy. The current study develops and pilot-tests a computer-assisted intervention that incorporates social network visualizations and MI techniques to reduce high risk AOD use and HIV behaviors among the formerly homeless. CLINICALTRIALS. NCT02140359.

A networking approach to reduce academic and social isolation for junior doctors working in rural hospitals in India.

PubMed

Vyas, R; Zachariah, A; Swamidasan, I; Doris, P; Harris, I

2012-07-01

Graduates from Christian Medical College (CMC) Vellore face many challenges while doing their service obligation in smaller hospitals, including academic and social isolation. To overcome these challenges, CMC aspired through its Fellowship in Secondary Hospital Medicine (FSHM), a 1-year blended on-site and distance-learning program, to provide academic and social support through networking for junior doctors working in rural areas. The purpose of this paper is to report the evaluation of the networking components of the FSHM program, with a focus on whether it succeeded in providing academic and social support for these junior doctors. A mixed method evaluation was done using written surveys for students and faculty and telephone interviews for students. Evidence for validity was gathered for the written survey. Criteria for validity were also applied for the qualitative data analysis. The major strengths of networking with faculty and peers identified were that it provided social support,, academic support through discussion about patient management problems and a variety of cases seen in the hospital, guidance on projects and reminders about deadlines. Recommendations for improvement included use of videoconferencing and Yahoo Groups. It is useful to incorporate networking into distance-learning educational programs for providing support to junior doctors working in rural hospitals.

Network of time-multiplexed optical parametric oscillators as a coherent Ising machine

NASA Astrophysics Data System (ADS)

Marandi, Alireza; Wang, Zhe; Takata, Kenta; Byer, Robert L.; Yamamoto, Yoshihisa

2014-12-01

Finding the ground states of the Ising Hamiltonian maps to various combinatorial optimization problems in biology, medicine, wireless communications, artificial intelligence and social network. So far, no efficient classical and quantum algorithm is known for these problems and intensive research is focused on creating physical systems—Ising machines—capable of finding the absolute or approximate ground states of the Ising Hamiltonian. Here, we report an Ising machine using a network of degenerate optical parametric oscillators (OPOs). Spins are represented with above-threshold binary phases of the OPOs and the Ising couplings are realized by mutual injections. The network is implemented in a single OPO ring cavity with multiple trains of femtosecond pulses and configurable mutual couplings, and operates at room temperature. We programmed a small non-deterministic polynomial time-hard problem on a 4-OPO Ising machine and in 1,000 runs no computational error was detected.

How risky are social networking sites? A comparison of places online where youth sexual solicitation and harassment occurs.

PubMed

Ybarra, Michele L; Mitchell, Kimberly J

2008-02-01

Recently, public attention has focused on the possibility that social networking sites such as MySpace and Facebook are being widely used to sexually solicit underage youth, consequently increasing their vulnerability to sexual victimization. Beyond anecdotal accounts, however, whether victimization is more commonly reported in social networking sites is unknown. The Growing up With Media Survey is a national cross-sectional online survey of 1588 youth. Participants were 10- to 15-year-old youth who have used the Internet at least once in the last 6 months. The main outcome measures were unwanted sexual solicitation on the Internet, defined as unwanted requests to talk about sex, provide personal sexual information, and do something sexual, and Internet harassment, defined as rude or mean comments, or spreading of rumors. Fifteen percent of all of the youth reported an unwanted sexual solicitation online in the last year; 4% reported an incident on a social networking site specifically. Thirty-three percent reported an online harassment in the last year; 9% reported an incident on a social networking site specifically. Among targeted youth, solicitations were more commonly reported via instant messaging (43%) and in chat rooms (32%), and harassment was more commonly reported in instant messaging (55%) than through social networking sites (27% and 28%, respectively). Broad claims of victimization risk, at least defined as unwanted sexual solicitation or harassment, associated with social networking sites do not seem justified. Prevention efforts may have a greater impact if they focus on the psychosocial problems of youth instead of a specific Internet application, including funding for online youth outreach programs, school antibullying programs, and online mental health services.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness

PubMed Central

Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of “topologically related” nodes, where the resulting topology-based clusters are expected to “correlate” well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data—their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance. PMID:29738568

Energy model for rumor propagation on social networks

NASA Astrophysics Data System (ADS)

Han, Shuo; Zhuang, Fuzhen; He, Qing; Shi, Zhongzhi; Ao, Xiang

2014-01-01

With the development of social networks, the impact of rumor propagation on human lives is more and more significant. Due to the change of propagation mode, traditional rumor propagation models designed for word-of-mouth process may not be suitable for describing the rumor spreading on social networks. To overcome this shortcoming, we carefully analyze the mechanisms of rumor propagation and the topological properties of large-scale social networks, then propose a novel model based on the physical theory. In this model, heat energy calculation formula and Metropolis rule are introduced to formalize this problem and the amount of heat energy is used to measure a rumor’s impact on a network. Finally, we conduct track experiments to show the evolution of rumor propagation, make comparison experiments to contrast the proposed model with the traditional models, and perform simulation experiments to study the dynamics of rumor spreading. The experiments show that (1) the rumor propagation simulated by our model goes through three stages: rapid growth, fluctuant persistence and slow decline; (2) individuals could spread a rumor repeatedly, which leads to the rumor’s resurgence; (3) rumor propagation is greatly influenced by a rumor’s attraction, the initial rumormonger and the sending probability.

Learning Time-Varying Coverage Functions

PubMed Central

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

2015-01-01

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

Learning Time-Varying Coverage Functions.

PubMed

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

2014-12-08

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

Online social networking in adolescence: patterns of use in six European countries and links with psychosocial functioning.

PubMed

Tsitsika, Artemis K; Tzavela, Eleni C; Janikian, Mari; Ólafsson, Kjartan; Iordache, Andreea; Schoenmakers, Tim Michaël; Tzavara, Chara; Richardson, Clive

2014-07-01

Online communication tools, such as social networking sites (SNS), have been comprehensively embraced by adolescents and have become a dominant daily social practice. Recognizing SNS as a key context of adolescent development, this study aimed to investigate associations between heavier SNS use, and adolescent competencies and internalizing problems. Data was collected in six European countries: Greece, Spain, Poland, the Netherlands, Romania, and Iceland. Participants were 10,930 adolescents aged 14-17 years (F/M: 5,719/5,211; mean age 15.8 ± .7 years); 62.3% were aged 14-15.9 years and 37.7% were aged 16-17.9 years. Participants reported on their use of online communication tools, and their general competencies and internalizing problems (Youth Self Report). SNS are both ubiquitous--used by 70% of adolescents--and engaging, given that 40% of users spend 2 or more hours daily on SNS (labeled heavier SNS use). Heavier SNS use was associated with more internalizing problems, and the relation was consistently more pronounced among younger adolescents. Moreover, heavier SNS use was associated with lower academic performance and lower activities scores, especially for younger adolescents. In contrast, among older adolescents heavier SNS use was positively associated with offline social competence. Although heavier SNS use is associated with higher social competence for older adolescents, it is also associated with increased internalizing problems and diminished competencies in academics and activities, especially for younger adolescents. Age, capturing developmental differences in social and regulatory skills, appears to moderate the effects of heavier SNS use on adolescent functioning. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Alumni Relations in Chinese HEIs: Case Studies of Three Major Universities

ERIC Educational Resources Information Center

Zhimin, Luo; Chunlian, Chen; Xian, Wang

2016-01-01

Good alumni relations are key to universities and colleges winning support from their graduates. With reference to social capital theory, an important problem in establishing strong alumni relations is how to turn alumni resources, an important university social network, into productive, public, and abundant capital. Based on the established…

Vulnerability and Gambling Addiction: Psychosocial Benchmarks and Avenues for Intervention

ERIC Educational Resources Information Center

Suissa, Amnon Jacob

2011-01-01

Defined by researchers as "a silent epidemic" the gambling phenomenon is a social problem that has a negative impact on individuals, families and communities. Among these effects, there is exasperating evidence of comprised community networks, a deterioration of family and social ties, psychiatric co-morbidity, suicides and more recently,…

Analysing Students' Interactions through Social Presence and Social Network Metrics

ERIC Educational Resources Information Center

Martins da Silva, Vanessa Cristina; Siqueira, Sean Wolfgand Matsui

2016-01-01

In online learning environments, tutors have several problems to carry out their activities, such as evaluating the student, knowing the right way to guide each student, promoting discussions, and knowing the right time to interact or let students build knowledge alone. We consider scenarios in which teaching and learning occurs in online social…

Social Networking Sites, Literacy, and the Authentic Identity Problem

ERIC Educational Resources Information Center

Kimmons, Royce

2014-01-01

Current interest in social media for educational purposes has led many to consider the importance of literacy development in online spaces (e.g., new media literacies, digital literacies, etc.). Relying heavily upon New Literacy Studies (NLS) as a base, these approaches treat literacy expansively to include socio-cultural factors beyond mere skill…

Information dynamics algorithm for detecting communities in networks

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

PubMed

Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L

2017-04-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

USGS Publications Warehouse

Haak, Danielle M.; Fath, Brian D.; Forbes, Valery E.; Martin, Dustin R.; Pope, Kevin L.

2017-01-01

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensisalters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Leveraging socially networked mobile ICT platforms for the last-mile delivery problem.

PubMed

Suh, Kyo; Smith, Timothy; Linhoff, Michelle

2012-09-04

Increasing numbers of people are managing their social networks on mobile information and communication technology (ICT) platforms. This study materializes these social relationships by leveraging spatial and networked information for sharing excess capacity to reduce the environmental impacts associated with "last-mile" package delivery systems from online purchases, particularly in low population density settings. Alternative package pickup location systems (PLS), such as a kiosk on a public transit platform or in a grocery store, have been suggested as effective strategies for reducing package travel miles and greenhouse gas emissions, compared to current door-to-door delivery models (CDS). However, our results suggest that a pickup location delivery system operating in a suburban setting may actually increase travel miles and emissions. Only once a social network is employed to assist in package pickup (SPLS) are significant reductions in the last-mile delivery distance and carbon emissions observed across both urban and suburban settings. Implications for logistics management's decades-long focus on improving efficiencies of dedicated distribution systems through specialization, as well as for public policy targeting carbon emissions of the transport sector are discussed.

Spreading paths in partially observed social networks

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Spreading paths in partially observed social networks.

PubMed

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

A national cross-sectional survey of social networking practices of U.S. anesthesiology residency program directors.

PubMed

Barker, Andrew L; Wehbe-Janek, Hania; Bhandari, Naumit S; Bittenbinder, Timothy M; Jo, ChanHee; McAllister, Russell K

2012-12-01

To determine the social networking practices of directors of anesthesiology residency programs. Cross-sectional survey. Online and paper survey tool. 132 anesthesiology residency program directors in the United States. A 13-item survey including dichotomous and multiple choice responses was administered using an online survey tool and a paper survey. Data analysis was conducted by descriptive and analytical statistics (chi-square test). A P-value < 0.05 indicated statistical significance. 50% of anesthesiology program directors responded to the survey (66/132). Policies governing social networking practices were in place for 30.3% (n=20) of the programs' hospitals. The majority of program directors (81.8%, 54) reported never having had an incident involving reprimand of a resident or fellow for inappropriate social networking practices. The majority (66.7%, n=44) of responding programs reported that departments did not provide lectures or educational activities related to appropriate social networking practices. Monitoring of social networking habits of residents/fellows by program directors mainly occurs if they are alerted to a problem (54.5%, n=36). Frequent use of the Internet for conducting searches on a resident applicant was reported by 12.1% (n=8) of program directors, 30.3% (n=20) reported use a few times, and 57.6% (n=38) reported never using the Internet in this capacity. Residency programs should have a written policy related to social media use. Residency program directors should be encouraged to become familiar with the professionalism issues related to social media use in order to serve as adequate resident mentors within this new and problematic aspect of medical ethics and professionalism. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

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

PubMed Central

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

2015-01-01

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

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

PubMed Central

Wu, Kai; Liu, Jing; Wang, Shuai

2016-01-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy. PMID:27886244

Reconstructing Networks from Profit Sequences in Evolutionary Games via a Multiobjective Optimization Approach with Lasso Initialization

NASA Astrophysics Data System (ADS)

Wu, Kai; Liu, Jing; Wang, Shuai

2016-11-01

Evolutionary games (EG) model a common type of interactions in various complex, networked, natural and social systems. Given such a system with only profit sequences being available, reconstructing the interacting structure of EG networks is fundamental to understand and control its collective dynamics. Existing approaches used to handle this problem, such as the lasso, a convex optimization method, need a user-defined constant to control the tradeoff between the natural sparsity of networks and measurement error (the difference between observed data and simulated data). However, a shortcoming of these approaches is that it is not easy to determine these key parameters which can maximize the performance. In contrast to these approaches, we first model the EG network reconstruction problem as a multiobjective optimization problem (MOP), and then develop a framework which involves multiobjective evolutionary algorithm (MOEA), followed by solution selection based on knee regions, termed as MOEANet, to solve this MOP. We also design an effective initialization operator based on the lasso for MOEA. We apply the proposed method to reconstruct various types of synthetic and real-world networks, and the results show that our approach is effective to avoid the above parameter selecting problem and can reconstruct EG networks with high accuracy.

Social factors predictive of social integration for adults with brain injury.

PubMed

Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole

2018-08-01

Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength-based psychosocial rehabilitation should optimally balance an individual's abilities with areas requiring compensation, focusing on how to approach rather than avoid problems as well as strategies to cultivate emotional social support.

Combining Computational and Social Effort for Collaborative Problem Solving

PubMed Central

Wagy, Mark D.; Bongard, Josh C.

2015-01-01

Rather than replacing human labor, there is growing evidence that networked computers create opportunities for collaborations of people and algorithms to solve problems beyond either of them. In this study, we demonstrate the conditions under which such synergy can arise. We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others’ designs to focus creative and computational effort on good designs. This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving. PMID:26544199

Synchronization in complex networks

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

Arenas, A.; Diaz-Guilera, A.; Moreno, Y.

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analyticalmore » approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.« less

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

NASA Astrophysics Data System (ADS)

Bruun, Jesper; Brewe, Eric

2013-12-01

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

The Influence of Social Media on Addictive Behaviors in College Students.

PubMed

Steers, Mai-Ly N; Moreno, Megan A; Neighbors, Clayton

2016-12-01

Social media has become a primary way for college students to communicate aspects of their daily lives to those within their social network. Such communications often include substance use displays (e.g., selfies of college students drinking). Furthermore, students' substance use displays have been found to robustly predict not only the posters' substance use-related outcomes (e.g., consumption, problems) but also that of their social networking peers. The current review summarizes findings of recent literature exploring the intersection between social media and substance use. Specifically, we examine how and why such substance use displays might shape college students' internalized norms surrounding substance use and how it impacts their substance use-related behaviors. Additional social media-related interventions are needed in order to target reduction of consumption among this at-risk group. We discuss the technological and methodological challenges inherent to conducting research and devising interventions in this domain.

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

PubMed Central

Vadillo, Miguel A; Curcin, Vasa

2017-01-01

Background Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. Objective The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research. Methods We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals. Results The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis. Conclusions Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques. PMID:28663166

Social support and well-being at mid-life among mothers of adolescents and adults with autism spectrum disorders.

PubMed

Smith, Leann E; Greenberg, Jan S; Seltzer, Marsha Mailick

2012-09-01

The present study investigated the impact of social support on the psychological well-being of mothers of adolescents and adults with ASD (n = 269). Quantity of support (number of social network members) as well as valence of support (positive support and negative support) were assessed using a modified version of the "convoy model" developed by Antonucci and Akiyama (1987). Having a larger social network was associated with improvements in maternal well-being over an 18-month period. Higher levels of negative support as well as increases in negative support over the study period were associated with increases in depressive symptoms and negative affect and decreases in positive affect. Social support predicted changes in well-being above and beyond the impact of child behavior problems. Implications for clinical practice are discussed.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Multicultural Mastery Scale for Youth: Multidimensional Assessment of Culturally Mediated Coping Strategies

ERIC Educational Resources Information Center

Fok, Carlotta Ching Ting; Allen, James; Henry, David; Mohatt, Gerald V.

2012-01-01

Self-mastery refers to problem-focused coping facilitated through personal agency. Communal mastery describes problem solving through an interwoven social network. This study investigates an adaptation of self- and communal mastery measures for youth. Given the important distinction between family and peers in the lives of youth, these adaptation…

A Solution to the Mysteries of Morality

ERIC Educational Resources Information Center

DeScioli, Peter; Kurzban, Robert

2013-01-01

We propose that moral condemnation functions to guide bystanders to choose the same side as other bystanders in disputes. Humans interact in dense social networks, and this poses a problem for bystanders when conflicts arise: which side, if any, to support. Choosing sides is a difficult strategic problem because the outcome of a conflict…

A study of knowledge supernetworks and network robustness in different business incubators

NASA Astrophysics Data System (ADS)

Zhang, Haihong; Wu, Wenqing; Zhao, Liming

2016-04-01

As the most important intangible resource of the new generation of business incubators, knowledge has been studied extensively, particularly with respect to how it spreads among incubating firms through knowledge networks. However, these homogeneous networks do not adequately describe the heterogeneity of incubating firms in different types of business incubators. To solve the problem of heterogeneity, the notion of a knowledge supernetwork has been used both to construct a knowledge interaction model among incubating firms and to distinguish social network relationships from knowledge network relationships. The process of knowledge interaction and network evolution can then be simulated with a few rules for incubating firms regarding knowledge innovation/absorption, social network connection, and entry and exit, among other aspects. Knowledge and networks have been used as performance indicators to evaluate the evolution of knowledge supernetworks. Moreover, we study the robustness of incubating firms' social networks by employing four types of attack strategies. Based on our simulation results, we conclude that there have been significant knowledge interaction and network evolution among incubating firms on a periodic basis and that both specialized and diversified business incubators have every advantage necessary in terms of both knowledge and networks to cultivate start-up companies. As far as network robustness is concerned, there is no obvious difference between the two types of business incubators with respect to the stability of their network structures, but specialized business incubators have stronger network communication abilities than diversified business incubators.

Gender moderates the effects of independence and dependence desires during the social support process.

PubMed

Nagumey, Alexander J; Reich, John W; Newsom, Jason

2004-03-01

This investigation examined the roles of gender and desires for independence and dependence in the support process. We assessed 118 older adults who reported needing help with at least 1 activity of daily living as a result of illness or health problems. Men with a high desire to be independent responded negatively to receiving support from their social network. Women's outcomes were generally unaffected by their independence and dependence desires. These results indicate that gender and desires for independence and dependence should be taken into account when examining the social support process, especially in men with health problems.

The psychological adjustment of children from separated families: The role of selected social support variables.

PubMed

Bouchard, C; Drapeau, S

1991-06-01

This study investigates the impact of social support on children's psychological adjustment following the divorce of their parents. Seventy-one (71) children from separated families and 120 children from intact families participated in the study. Data were collected twice. Children from separated families listed support networks of lower density with more sitters and teachers contributing both to emotional support and to negative interactions. Social support variables contribute more in predicting the psychological status of children from separated families than of children from intact families. Insufficient income, dissatisfaction with family life, lower density of the support network and higher ratio of negative interactions are predictive of children behavior problems.

Using System Dynamic Model and Neural Network Model to Analyse Water Scarcity in Sudan

NASA Astrophysics Data System (ADS)

Li, Y.; Tang, C.; Xu, L.; Ye, S.

2017-07-01

Many parts of the world are facing the problem of Water Scarcity. Analysing Water Scarcity quantitatively is an important step to solve the problem. Water scarcity in a region is gauged by WSI (water scarcity index), which incorporate water supply and water demand. To get the WSI, Neural Network Model and SDM (System Dynamic Model) that depict how environmental and social factors affect water supply and demand are developed to depict how environmental and social factors affect water supply and demand. The uneven distribution of water resource and water demand across a region leads to an uneven distribution of WSI within this region. To predict WSI for the future, logistic model, Grey Prediction, and statistics are applied in predicting variables. Sudan suffers from severe water scarcity problem with WSI of 1 in 2014, water resource unevenly distributed. According to the result of modified model, after the intervention, Sudan’s water situation will become better.

[Integration of new psychosocial facilities into the health care system: considerations on a social ecological evaluation concept exemplified by ambulatory crisis care].

PubMed

Leferink, K; Bergold, J B

1996-11-01

With respect to the methodological problems concerning the outcome evaluation of crisis intervention centers the outlines of a social-ecological research approach are developed. It is suggested that this approach is more suitable to take into account the role of the network of mental health services. The data come from a research project which was designed to explain the historical and social aspects of the process of integration of a crisis intervention service. The results indicate that on the one hand the practice of the service strongly depends on what other services do and on the other hand influences them. The social integration of an institution into the network of other services is discussed as an alternative criterion of evaluation.

Complex Dynamics in Information Sharing Networks

NASA Astrophysics Data System (ADS)

Cronin, Bruce

This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

The Pivotal Role of Women in Informal Care

ERIC Educational Resources Information Center

Bracke, Piet; Christiaens, Wendy; Wauterickx, Naomi

2008-01-01

Supporting and caring for each other are crucial parts of the social tissue that binds people together. In these networks, men and women hold different positions: Women more often care more for others, listen more to the problems of others, and, as kin keepers, hold families together. Is this true for all life stages? And are social conditions,…

Documentation for Students in Residential Care: Network of Relations of Human and Non-Human Actants

ERIC Educational Resources Information Center

Severinsson, Susanne

2016-01-01

Swedish and international research points to serious problems for the education of students with social, emotional and behavioural difficulties (SEBD) in the care of social welfare, for example, in residential care. The aim of this article is to elucidate how documentation, care plans (CPs) and individual educational plans (IEPs) outline the…

"Elven Elder LVL59 LFP/RB. Please PM Me": Immersion, Collaborative Tasks and Problem-Solving in Massively Multiplayer Online Games

ERIC Educational Resources Information Center

Voulgari, Iro; Komis, Vassilis

2010-01-01

Although there is strong evidence that massively multiplayer online games (MMOGs) constitute environments of social interactions and effective learning, we currently lack the tools for investigating the effectiveness of the social networks emerging as well as the cognitive aspects and knowledge acquisition such environments involve. Within this…

The Relationships between Cyber Bullying, Academic Constructs, and Extracurricular Participation among Middle Schoolers

ERIC Educational Resources Information Center

Shamel, Kimberly A.

2013-01-01

Bullying is a large scale social problem impacting educational systems nationwide, and has been linked to negative outcomes for both bullies and targets. Bullying has become more highly technological and is most often referred to as cyber bullying. Bullies have begun to use the internet, social networking sites, e-mail, instant messaging (IM),…

Mining Learning Social Networks for Cooperative Learning with Appropriate Learning Partners in a Problem-Based Learning Environment

ERIC Educational Resources Information Center

Chen, Chih-Ming; Chang, Chia-Cheng

2014-01-01

Many studies have identified web-based cooperative learning as an increasingly popular educational paradigm with potential to increase learner satisfaction and interactions. However, peer-to-peer interaction often suffers barriers owing to a failure to explore useful social interaction information in web-based cooperative learning environments.…

Avatars, First Impressions and Self-Presentation Tactics: Influences on a Participant Social Network

ERIC Educational Resources Information Center

Lusher, Tammy J.

2012-01-01

Even as higher education institutions offer more distance education courses, the attrition rate in these courses remains higher than face-to-face courses. One of the most cited reason by students who drop out of distance education classes is the lack of social interaction. Educational technology researchers have studied this problem from a sense…

Inferring Social Influence of Anti-Tobacco Mass Media Campaign.

PubMed

Zhan, Qianyi; Zhang, Jiawei; Yu, Philip S; Emery, Sherry; Xie, Junyuan

2017-07-01

Anti-tobacco mass media campaigns are designed to influence tobacco users. It has been proved that campaigns will produce users' changes in awareness, knowledge, and attitudes, and also produce meaningful behavior change of audience. Anti-smoking television advertising is the most important part in the campaign. Meanwhile, nowadays, successful online social networks are creating new media environment, however, little is known about the relation between social conversations and anti-tobacco campaigns. This paper aims to infer social influence of these campaigns, and the problem is formally referred to as the Social Influence inference of anti-Tobacco mass mEdia campaigns (Site) problem. To address the Site problem, a novel influence inference framework, TV advertising social influence estimation (Asie), is proposed based on our analysis of two real anti-tobacco campaigns. Asie divides audience attitudes toward TV ads into three distinct stages: 1) cognitive; 2) affective; and 3) conative. Audience online reactions at each of these three stages are depicted by Asie with specific probabilistic models based on the synergistic influences from both online social friends and offline TV ads. Extensive experiments demonstrate the effectiveness of Asie.

A randomised controlled feasibility trial of family and social network intervention for young people who misuse alcohol and drugs: study protocol (Y-SBNT).

PubMed

Watson, Judith; Back, Donna; Toner, Paul; Lloyd, Charlie; Day, Ed; Brady, Louca-Mai; Templeton, Lorna; Ambegaokar, Sangeeta; Parrott, Steve; Torgerson, David; Cocks, Kim; Gilvarry, Eilish; McArdle, Paul; Copello, Alex

2015-01-01

A growing body of research has identified family interventions to be effective in treating young people's substance use problems. However, despite this evidence, take-up of family-based approaches in the UK has been low. Key factors for this appear to include the resource-intensive nature of most family interventions which challenges implementation and delivery in many service settings and the cultural adaptation of approaches developed in the USA to a UK setting. This study aims to demonstrate the feasibility of recruiting young people to a specifically developed family- and wider social network-based intervention by testing an adapted version of adult social behaviour and network therapy (SBNT). A pragmatic, randomised controlled, open feasibility trial delivered in two services for young people in the UK. Potential participants are aged 12-18 years referred for drug or alcohol problems to either service. The main purpose of this study is to demonstrate the feasibility of recruiting young people to a specifically developed family and social network-based intervention. The feasibility and acceptability of this intervention will be measured by recruitment rates, treatment retention, follow-up rates and qualitative interviews. The feasibility of training staff from existing services to deliver this intervention will be explored. Using this opportunity to compare the effectiveness of the intervention against treatment as usual, Timeline Follow-Back interviews will document the proportion of days on which the main problem substance was used in the preceding 90-day period at each assessment point. The economic component will examine the feasibility of conducting a full incremental cost-effectiveness analysis of the two treatments. The study will also explore and develop models of patient and public involvement which support the involvement of young people in a study of this nature. An earlier phase of work adapted social behaviour and network therapy (adult approach) to produce a purpose-designed youth version supported by a therapy manual and associated resources. This was achieved by consultation with young people with experience of services and professionals working in services for young people. This feasibility trial alongside ongoing consultations with young people will offer a meaningful understanding of processes of delivery and implementation. ISRCTN93446265; Date ISRCTN assigned 31/05/2013.

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.

Conditions for Viral Influence Spreading through Multiplex Correlated Social Networks

NASA Astrophysics Data System (ADS)

Hu, Yanqing; Havlin, Shlomo; Makse, Hernán A.

2014-04-01

A fundamental problem in network science is to predict how certain individuals are able to initiate new networks to spring up "new ideas." Frequently, these changes in trends are triggered by a few innovators who rapidly impose their ideas through "viral" influence spreading, producing cascades of followers and fragmenting an old network to create a new one. Typical examples include the rise of scientific ideas or abrupt changes in social media, like the rise of Facebook to the detriment of Myspace. How this process arises in practice has not been conclusively demonstrated. Here, we show that a condition for sustaining a viral spreading process is the existence of a multiplex-correlated graph with hidden "influence links." Analytical solutions predict percolation-phase transitions, either abrupt or continuous, where networks are disintegrated through viral cascades of followers, as in empirical data. Our modeling predicts the strict conditions to sustain a large viral spreading via a scaling form of the local correlation function between multilayers, which we also confirm empirically. Ultimately, the theory predicts the conditions for viral cascading in a large class of multiplex networks ranging from social to financial systems and markets.

Social networking sites and mental health problems in adolescents: The mediating role of cyberbullying victimization.

PubMed

Sampasa-Kanyinga, H; Hamilton, H A

2015-11-01

Previous research has suggested an association between the use of social networking sites (SNSs) and mental health problems such as psychological distress, suicidal ideation and attempts in adolescents. However, little is known about the factors that might mediate these relationships. The present study examined the link between the use of social networking sites and psychological distress, suicidal ideation and suicide attempts, and tested the mediating role of cyberbullying victimization on these associations in adolescents. The sample consisted of a group of 11-to-20-year-old individuals (n=5126, 48% females; mean±SD age: 15.2±1.9 years) who completed the mental health portion of the Ontario Student Drug Use and Health Survey (OSDUHS) in 2013. Multiple logistic regression analyses were used to test the mediation models. After adjustment for age, sex, ethnicity, subjective socioeconomic status (SES), and parental education, use of SNSs was associated with psychological distress (adjusted odds ratio, 95% confidence interval=2.03, 1.22-3.37), suicidal ideation (3.44, 1.54-7.66) and attempts (5.10, 1.45-17.88). Cyberbullying victimization was found to fully mediate the relationships between the use of SNSs with psychological distress and attempts; whereas, it partially mediated the link between the use of SNSs and suicidal ideation. Findings provide supporting evidence that addressing cyberbullying victimization and the use of SNSs among adolescents may help reduce the risk of mental health problems. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion.

PubMed

Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D

2015-04-14

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.

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

PubMed Central

Sayles, Jesse S.

2017-01-01

Resource management boundaries seldom align with environmental systems, which can lead to social and ecological problems. Mapping and analyzing how resource management organizations in different areas collaborate can provide vital information to help overcome such misalignment. Few quantitative approaches exist, however, to analyze social collaborations alongside environmental patterns, especially among local and regional organizations (i.e., in multilevel governance settings). This paper develops and applies such an approach using social–ecological network analysis (SENA), which considers relationships among and between social and ecological units. The framework and methods are shown using an estuary restoration case from Puget Sound, United States. Collaboration patterns and quality are analyzed among local and regional organizations working in hydrologically connected areas. These patterns are correlated with restoration practitioners’ assessments of the productivity of their collaborations to inform network theories for natural resource governance. The SENA is also combined with existing ecological data to jointly consider social and ecological restoration concerns. Results show potentially problematic areas in nearshore environments, where collaboration networks measured by density (percentage of possible network connections) and productivity are weakest. Many areas also have high centralization (a few nodes hold the network together), making network cohesion dependent on key organizations. Although centralization and productivity are inversely related, no clear relationship between density and productivity is observed. This research can help practitioners to identify where governance capacity needs strengthening and jointly consider social and ecological concerns. It advances SENA by developing a multilevel approach to assess social–ecological (or social–environmental) misalignments, also known as scale mismatches. PMID:28223529

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

PubMed Central

Rosenthal, Sara Brin; Twomey, Colin R.; Hartnett, Andrew T.; Wu, Hai Shan; Couzin, Iain D.

2015-01-01

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion. PMID:25825752

Urban elders and casino gambling: Are they at risk of a gambling problem?

PubMed

Zaranek, Rochelle R; Lichtenberg, Peter A

2008-01-01

This study examined gambling among older adults and explored the critical predictors of problem gambling behaviors. Relatively unknown and understudied is the extent, or prevalence, of problem gambling behaviors among urban elders and the factors associated with problem gambling. The sample consisted of 1410 randomly selected participants, aged 60 and older, who reside in the City of Detroit. Mental health, health, demographics, social activities, senior optimism, social support network, and frequency of casino visits were examined in order to predict problem gambling behaviors among elders. The survey implemented the Lie/Bet Questionnaire for Screening Probable pathological Gamblers. The results showed that the prevalence of problem gambling behaviors was 10.4% overall, and 18% of persons reporting any casino visitation. Predictors accounted for 16% of problem gambling behaviors. The findings from this study confirmed that gambling has the potential to become a serious health problem among elders. Copyright © 2007 Elsevier Inc. All rights reserved.

Use of Social Media for Professional Development by Health Care Professionals: A Cross-Sectional Web-Based Survey

PubMed Central

2016-01-01

Background Social media can be used in health care settings to enhance professional networking and education; patient communication, care, and education; public health programs; organizational promotion; and research. Objective The aim of this study was to explore the use of social media networks for the purpose of professional development among health care professionals in Saudi Arabia using a purpose-designed Web-based survey. Methods A cross-sectional web-based survey was undertaken. A link to the survey was posted on the investigator’s personal social media accounts including Twitter, LinkedIn, and WhatsApp. Results A total of 231 health care professionals, who are generally social media users, participated in the study. Of these professionals, 70.6% (163/231) use social media for their professional development. The social media applications most frequently used, in the descending order, for professional development were Twitter, YouTube, Instagram, Facebook, Snapchat, and LinkedIn. The majority of respondents used social media for professional development irrespective of their age group, with the highest proportion seen in those aged 20-30 years. Social media were perceived as being most beneficial for professional development in terms of their impact on the domains of knowledge and problem solving and least helpful for enhancing clinical skills. Twitter was perceived as the most helpful type of social media for all domains listed. Respondents most frequently reported that social media were useful for professional development for the reasons of knowledge exchange and networking. Conclusions Social media are frequently used by health care professionals in Saudi Arabia for the purposes of professional development, with Twitter most frequently used for this purpose. These findings suggest that social media networks can be powerful tools for engaging health care professionals in their professional development. PMID:27731855

Use of Social Media for Professional Development by Health Care Professionals: A Cross-Sectional Web-Based Survey.

PubMed

Alsobayel, Hana

2016-09-12

Social media can be used in health care settings to enhance professional networking and education; patient communication, care, and education; public health programs; organizational promotion; and research. The aim of this study was to explore the use of social media networks for the purpose of professional development among health care professionals in Saudi Arabia using a purpose-designed Web-based survey. A cross-sectional web-based survey was undertaken. A link to the survey was posted on the investigator's personal social media accounts including Twitter, LinkedIn, and WhatsApp. A total of 231 health care professionals, who are generally social media users, participated in the study. Of these professionals, 70.6% (163/231) use social media for their professional development. The social media applications most frequently used, in the descending order, for professional development were Twitter, YouTube, Instagram, Facebook, Snapchat, and LinkedIn. The majority of respondents used social media for professional development irrespective of their age group, with the highest proportion seen in those aged 20-30 years. Social media were perceived as being most beneficial for professional development in terms of their impact on the domains of knowledge and problem solving and least helpful for enhancing clinical skills. Twitter was perceived as the most helpful type of social media for all domains listed. Respondents most frequently reported that social media were useful for professional development for the reasons of knowledge exchange and networking. Social media are frequently used by health care professionals in Saudi Arabia for the purposes of professional development, with Twitter most frequently used for this purpose. These findings suggest that social media networks can be powerful tools for engaging health care professionals in their professional development.

PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs

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

Slota, George M; Rajamanickam, Sivasankaran; Madduri, Kamesh

2017-09-21

PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.

Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

ERIC Educational Resources Information Center

Duan, Lian

2012-01-01

Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

NASA Astrophysics Data System (ADS)

Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

2017-05-01

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

Evolution of extortion in the social-influenced prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Wang, Zhipeng; Li, Miao; Wang, Dan; Chen, Qinghe

2016-01-01

The introduction of extortion strategy has attracted much attention since it dominates any evolutionary opponent in iterated prisoner’s dilemma games. Despite several studies argue that extortion is difficult to survive under strategy imitation and birth-death updating rules in well-mixed populations, it has recently been proven that a myopic best response rule facilitate the evolution of cooperation and extortion. However, such updating rules require a strong assumption of complete knowledge of all players, which is unlikely to hold in social networks in reality. To solve this problem, we introduce the concept of social influence into the model to limit players’ knowledge within their neighborhood. It turns out that this myopia initiated by social influence prevents players from observing superior strategies and therefore enables cooperators and extortioners to be evolutionarily stable. We also suggest that heterogeneous networks contribute to the evolution of cooperation and extortion under such social influence.

Resistance, Resilience and Social Identities: Reframing "Problem Youth" and the Problem of Schooling

ERIC Educational Resources Information Center

Bottrell, Dorothy

2007-01-01

This paper explores the experiences of young people on a public housing estate in inner-city Sydney. Their relations to schooling, truancy and participation in the illicit activities of the local youth network are framed as resistances, as necessary identity work, given the context of their marginalisation. In their explication of the dynamics of…

Social Support Networks Among Diverse Sexual Minority Populations

PubMed Central

Frost, David M.; Meyer, Ilan H.; Schwartz, Sharon

2016-01-01

This paper reports a study of the function and composition of social support networks among diverse lesbian, gay and bisexual (LGB) men and women (n = 396) in comparison to their heterosexual peers (n = 128). Data were collected using a structured social support network matrix in a community sample recruited in New York City. Our findings show that gay and bisexual men may rely on “chosen families” within LGBT communities more so than lesbian and bisexual women. Both heterosexuals and LGBs relied less on family and more on other people (e.g., friends, co-workers) for everyday social support (e.g., recreational and social activities, talking about problems). Providers of everyday social support were most often of the same sexual orientation and race/ethnicity as participants. In seeking major support (e.g., borrowing large sums of money), heterosexual men and women along with lesbian and bisexual women relied primarily on their families, but gay and bisexual men relied primarily on other LGB individuals. Racial/ethnic minority LGBs relied on LGB similar others at the same rate at White LGBs but, notably, racial/ethnic minority LGBs reported receiving fewer dimensions of support. PMID:26752447

Data reliability in complex directed networks

NASA Astrophysics Data System (ADS)

Sanz, Joaquín; Cozzo, Emanuele; Moreno, Yamir

2013-12-01

The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimerá and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way.

Leveraging percolation theory to single out influential spreaders in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2016-06-01

Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.

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

PubMed

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

2018-05-01

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

Mental health consequences of international migration for Vietnamese Americans and the mediating effects of physical health and social networks: results from a natural experiment approach.

PubMed

Fu, Hongyun; VanLandingham, Mark J

2012-05-01

Although the existing literature on immigrant mental health is extensive, major substantive and methodological gaps remain. Substantively, there is little population-based research that focuses on the mental health consequences of migration for Vietnamese Americans. More generally, although a wide range of mental health problems among immigrants has been identified, the potential causal or mediating mechanisms underlying these problems remain elusive. This latter substantive shortcoming is related to a key methodological challenge involving the potentially confounding effects of selection on migration-related outcomes. This article addresses these challenges by employing a "natural experiment" design, involving comparisons among three population-based samples of Vietnamese immigrants, never-leavers, and returnees (N=709). Data were collected in Ho Chi Minh City and in New Orleans between 2003 and 2005. The study investigates the long-term impact of international migration on Vietnamese mental health, and the potential mediating effects of social networks and physical health on these migration-related outcomes. The results reveal both mental health advantages and disadvantages among Vietnamese immigrants relative to the two groups of Vietnamese nationals. Selection can be ruled out for some of these differences, and both social networks and physical health are found to play important explanatory roles.

Social networks and substance use among at-risk emerging adults living in disadvantaged urban areas in the southern United States: a cross-sectional naturalistic study.

PubMed

Tucker, Jalie A; Cheong, JeeWon; Chandler, Susan D; Crawford, Scott M; Simpson, Cathy A

2015-09-01

Substance use and risk-taking are common during emerging adulthood, a transitional period when peer influences often increase and family influences decrease. Investigating relationships between social network features and substance use can inform community-based prevention programs. This study investigated whether substance use among emerging adults living in disadvantaged urban areas was influenced by peer and family social network messages that variously encouraged and discouraged substance use. Cross-sectional, naturalistic field study. Lower-income neighborhoods in Birmingham, Alabama, USA with 344 participants (110 males, 234 females, ages 15-25 years; mean = 18.86 years), recruited via respondent-driven sampling. During structured interviews conducted in community locations, the Alcohol, Smoking and Substance Involvement Screening Test assessed substance use and related problems. Predictor variables were network characteristics, including presence of substance-using peers, messages from friends and family members about substance use and network sources for health information. Higher substance involvement was associated with friend and family encouragement of use and having close peer network members who used substances (Ps < 0.001). Peer discouragement of substance use was associated with reduced risk (b = - 1.46, P < 0.05), whereas family discouragement had no protective association. Social networks appear to be important in both promoting and preventing substance use in disadvantaged young adults in the United States. © 2015 Society for the Study of Addiction.

Selection Strategies for Social Influence in the Threshold Model

NASA Astrophysics Data System (ADS)

Karampourniotis, Panagiotis; Szymanski, Boleslaw; Korniss, Gyorgy

The ubiquity of online social networks makes the study of social influence extremely significant for its applications to marketing, politics and security. Maximizing the spread of influence by strategically selecting nodes as initiators of a new opinion or trend is a challenging problem. We study the performance of various strategies for selection of large fractions of initiators on a classical social influence model, the Threshold model (TM). Under the TM, a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. The strategies we study are of two kinds: strategies based solely on the initial network structure (Degree-rank, Dominating Sets, PageRank etc.) and strategies that take into account the change of the states of the nodes during the evolution of the cascade, e.g. the greedy algorithm. We find that the performance of these strategies depends largely on both the network structure properties, e.g. the assortativity, and the distribution of the thresholds assigned to the nodes. We conclude that the optimal strategy needs to combine the network specifics and the model specific parameters to identify the most influential spreaders. Supported in part by ARL NS-CTA, ARO, and ONR.

Online Social Networks and Smoking Cessation: A Scientific Research Agenda

PubMed Central

Graham, Amanda L; Byron, M. Justin; Niaura, Raymond S; Abrams, David B

2011-01-01

Background Smoking remains one of the most pressing public health problems in the United States and internationally. The concurrent evolution of the Internet, social network science, and online communities offers a potential target for high-yield interventions capable of shifting population-level smoking rates and substantially improving public health. Objective Our objective was to convene leading practitioners in relevant disciplines to develop the core of a strategic research agenda on online social networks and their use for smoking cessation, with implications for other health behaviors. Methods We conducted a 100-person, 2-day, multidisciplinary workshop in Washington, DC, USA. Participants worked in small groups to formulate research questions that could move the field forward. Discussions and resulting questions were synthesized by the workshop planning committee. Results We considered 34 questions in four categories (advancing theory, understanding fundamental mechanisms, intervention approaches, and evaluation) to be the most pressing. Conclusions Online social networks might facilitate smoking cessation in several ways. Identifying new theories, translating these into functional interventions, and evaluating the results will require a concerted transdisciplinary effort. This report presents a series of research questions to assist researchers, developers, and funders in the process of efficiently moving this field forward. PMID:22182518

Researching Mental Health Disorders in the Era of Social Media: Systematic Review.

PubMed

Wongkoblap, Akkapon; Vadillo, Miguel A; Curcin, Vasa

2017-06-29

Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research. We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals. The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis. Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques. ©Akkapon Wongkoblap, Miguel A Vadillo, Vasa Curcin. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.06.2017.

Environmental factors during adolescence associated with later development of psychotic disorders - a nested case-control study.

PubMed

Bratlien, Unni; Øie, Merete; Haug, Elisabeth; Møller, Paul; Andreassen, Ole A; Lien, Lars; Melle, Ingrid

2014-03-30

Etiologies of psychotic disorders (schizophrenia and bipolar disorder) are conceptualized as interplay between genetic and environmental factors. The adolescent period is characterized by changes in social roles and expectations that may interact with biological changes or psychosocial stressors. Few studies focus on the adolescents' own reports of perceived risk factors. To assess differences at age 16 between persons who later develop psychotic disorders ("Confirmed Psychosis", CP) and their class-mates ("Population Controls", PC) we collected information on: (1) Social support factors (size of social network and expectancies of social support from friends), (2) Cognitive functioning (concentrating in the classroom, actual grades and expectancies of own academic achievements) and (3) Problems and stressors in families (illness or loss of work for parents), and in relationship with others (exposure to bullying, violence or sexual violation). Self-reported data from students at 15-16 years of age were linked to the case-registers from the "Thematically Organized Psychosis (TOP) Study". The CP group reported more economic problems in their families, smaller social network and lower academic expectation than the PC group. The results support the notion that long-term socioeconomic stressors in adolescence may serve as risk factors for the development of psychotic disorders. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

[Complexity of social and healthcare coordination in addictions and the role of the nurse].

PubMed

Molina Fernández, Antonio Jesús; González Riera, Javier; Montero Bancalero, Francisco José; Gómez-Salgado, Juan

2016-01-01

The present article discusses the psychosocial impact of basic and advanced concepts, such as social support and prevention, as well as to establish a link between theoretical models related to the social sphere on one side, and the health aspects on the other. This work is based on the context of the influence on health shared by community psychology and social psychology. Starting from the historical background of current approaches, a review is presented of those first actions focused on the care plan and they are framed in a reaction model to the drug problem, which progressed to the current healthcare network model, through the creation of Spanish National Action Plan on Drugs. The complexity of the problem is then broken down into the following key elements: Multifactorial Model of Drugs and Addictions, importance of prevention, and social support. Subsequently, a description is presented on the different levels of the healthcare network, with their different resources. This is also illustrated using a coordination protocol. Finally, it features the nursing approach to drugs, with its contributions, particularly as regards the coordination of resources, and aspects that must be developed for improvement in this area. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

A View from Japan. Citizenship for the 21st Century: The Role of the Social Studies. Fourth in a Series.

ERIC Educational Resources Information Center

Nakayama, Shuichi

1989-01-01

Points out problems in planning a social studies curriculum that will prepare Japanese society for the 21st Century. Claiming that the current curricula is ethnocentric, looks at objectives and teaching strategies for developing a global approach. Recommends development of a global information network to increase awareness of the interrelatedness…

New Students' Peer Integration and Exposure to Deviant Peers: Spurious Effects of School Moves?

ERIC Educational Resources Information Center

Siennick, Sonja E.; Widdowson, Alex O.; Ragan, Daniel T.

2017-01-01

School moves during adolescence predict lower peer integration and higher exposure to delinquent peers. Yet mobility and peer problems have several common correlates, so differences in movers' and non-movers' social adjustment may be due to selection rather than causal effects of school moves. Drawing on survey and social network data from a…

Social Capital and Youth Transitions: Do Young People's Networks Improve Their Participation in Education and Training? Occasional Paper

ERIC Educational Resources Information Center

Semo, Ronnie; Karmel, Tom

2011-01-01

In recent times social capital has received considerable attention because it is seen as having the potential to address many of the problems facing modern society, including the poor educational outcomes of considerable numbers of young people. This paper uses data from the Longitudinal Surveys of Australian Youth (LSAY) to explore the…

Herbert Simon and the GSIA: building an interdisciplinary community.

PubMed

Crowther-Heyck, Hunter

2006-01-01

This article explores Herbert Simon's attempts to build Carnegie Tech's Graduate School of Industrial Administration into a center for interdisciplinary social research. It shows that despite the pressures toward disciplinary specialization created by the rapid growth of the postwar social sciences, there were strong countercurrents supporting interdisciplinary work. Support for interdisciplinary work came from a network of powerful new patrons that were interested in transforming social science into behavioral science and that supported mathematical, behavioral-functional analysis whatever the topic of study. These patrons deliberately defined their goals in terms of solving problems, not building disciplines, and the networks of advisory committees they created enabled certain entrepreneurial researchers, such as Simon, to exert influence across a range of fields and institutions. (c) 2006 Wiley Periodicals, Inc.

The concerned significant others of people with gambling problems in a national representative sample in Sweden - a 1 year follow-up study.

PubMed

Svensson, Jessika; Romild, Ulla; Shepherdson, Emma

2013-11-21

Research into the impact of problem gambling on close social networks is scarce with the majority of studies only including help-seeking populations. To date only one study has examined concerned significant others (CSOs) from an epidemiological perspective and it did not consider gender. The aim of this study is to examine the health, social support, and financial situations of CSOs in a Swedish representative sample and to examine gender differences. A population study was conducted in Sweden in 2008/09 (n = 15,000, response rate 63%). Respondents were defined as CSOs if they reported that someone close to them currently or previously had problems with gambling. The group of CSOs was further examined in a 1-year follow up (weighted response rate 74% from the 8,165 respondents in the original sample). Comparisons were also made between those defined as CSOs only at baseline (47.7%, n = 554) and those defined as CSOs at both time points. In total, 18.2% of the population were considered CSOs, with no difference between women and men. Male and female CSOs experienced, to a large extent, similar problems including poor mental health, risky alcohol consumption, economic hardship, and arguments with those closest to them. Female CSOs reported less social support than other women and male CSOs had more legal problems and were more afraid of losing their jobs than other men. One year on, several problems remained even if some improvements were found. Both male and female CSOs reported more negative life events in the 1 year follow-up. Although some relationships are unknown, including between the CSOs and the individuals with gambling problems and the causal relationships between being a CSO and the range of associated problems, the results of this study indicate that gambling problems not only affect the gambling individual and their immediate close family but also the wider social network. A large proportion of the population can be defined as a CSO, half of whom are men. While male and female CSOs share many common problems, there are gender differences which need to be considered in prevention and treatment.

Network reconstructions with partially available data

NASA Astrophysics Data System (ADS)

Zhang, Chaoyang; Chen, Yang; Hu, Gang

2017-06-01

Many practical systems in natural and social sciences can be described by dynamical networks. Day by day we have measured and accumulated huge amounts of data from these networks, which can be used by us to further our understanding of the world. The structures of the networks producing these data are often unknown. Consequently, understanding the structures of these networks from available data turns to be one of the central issues in interdisciplinary fields, which is called the network reconstruction problem. In this paper, we considered problems of network reconstructions using partially available data and some situations where data availabilities are not sufficient for conventional network reconstructions. Furthermore, we proposed to infer subnetwork with data of the subnetwork available only and other nodes of the entire network hidden; to depict group-group interactions in networks with averages of groups of node variables available; and to perform network reconstructions with known data of node variables only when networks are driven by both unknown internal fast-varying noises and unknown external slowly-varying signals. All these situations are expected to be common in practical systems and the methods and results may be useful for real world applications.

Who do you know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Entrepreneurial Environment of Kampala, Uganda

DTIC Science & Technology

2013-11-04

the Army Research Office. vii 1 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 May 2013 “Who do...own specific centrality metrics. 2 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 Background The...of the world’s social and economic problems. Major international organizations such as the World Bank , International Monetary Fund, and the United

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Theory of mind mediates the prospective relationship between abnormal social brain network morphology and chronic behavior problems after pediatric traumatic brain injury

PubMed Central

Ryan, Nicholas P.; Catroppa, Cathy; Beare, Richard; Silk, Timothy J.; Crossley, Louise; Beauchamp, Miriam H.; Yeates, Keith Owen; Anderson, Vicki A.

2016-01-01

Childhood and adolescence coincide with rapid maturation and synaptic reorganization of distributed neural networks that underlie complex cognitive-affective behaviors. These regions, referred to collectively as the ‘social brain network’ (SBN) are commonly vulnerable to disruption from pediatric traumatic brain injury (TBI); however, the mechanisms that link morphological changes in the SBN to behavior problems in this population remain unclear. In 98 children and adolescents with mild to severe TBI, we acquired 3D T1-weighted MRIs at 2–8 weeks post-injury. For comparison, 33 typically developing controls of similar age, sex and education were scanned. All participants were assessed on measures of Theory of Mind (ToM) at 6 months post-injury and parents provided ratings of behavior problems at 24-months post-injury. Severe TBI was associated with volumetric reductions in the overall SBN package, as well as regional gray matter structural change in multiple component regions of the SBN. When compared with TD controls and children with milder injuries, the severe TBI group had significantly poorer ToM, which was associated with more frequent behavior problems and abnormal SBN morphology. Mediation analysis indicated that impaired theory of mind mediated the prospective relationship between abnormal SBN morphology and more frequent chronic behavior problems. Our findings suggest that sub-acute alterations in SBN morphology indirectly contribute to long-term behavior problems via their influence on ToM. Volumetric change in the SBN and its putative hub regions may represent useful imaging biomarkers for prediction of post-acute social cognitive impairment, which may in turn elevate risk for chronic behavior problems. PMID:26796967

Can social networking be used to promote engagement in child maltreatment prevention programs? Two pilot studies.

PubMed

Edwards-Gaura, Anna; Whitaker, Daniel; Self-Brown, Shannon

2014-08-01

Child maltreatment is one of the United States' most significant public health problems. In efforts to prevent maltreatment experts recommend use of Behavioral Parent Training Programs (BPTs), which focus on teaching skills that will replace and prevent maltreating behavior. While there is research to support the effectiveness of BPTs in maltreatment prevention, the reach of such programs is still limited by several barriers, including poor retention of families in services. Recently, new technologies have emerged that offer innovative opportunities to improve family engagement. These technologies include smartphones and social networking; however, very little is known about the potential of these to aid in maltreatment prevention. The primary goal of this study was to conduct 2 pilot exploratory projects. The first project administered a survey to parents and providers to gather data about at-risk parents' use of smartphones and online social networking technologies. The second project tested a social networking-enhanced brief parenting program with 3 intervention participants and evaluated parental responses. Seventy-five percent of parents surveyed reported owning a computer that worked. Eighty-nine percent of parents reported that they had reliable Internet access at home, and 67% said they used the Internet daily. Three parents participated in the intervention with all reporting improvement in parent-child interaction skills and a positive experience participating in the social networking-enhanced SafeCare components. In general, findings suggest that smartphones, social networking, and Facebook, in particular, are now being used by individuals who show risk factors for maltreatment. Further, the majority of parents surveyed in this study said that they like Facebook, and all parents surveyed said that they use Facebook and have a Facebook account. As well, all saw it as a potentially beneficial supplement for future parents enrolling in parenting programs.

Social-Professional Networks in Long-Term Care Settings With People With Dementia: An Approach to Better Care? A Systematic Review.

PubMed

Mitchell, Janet I; Long, Janet C; Braithwaite, Jeffrey; Brodaty, Henry

2016-02-01

Dementia is a syndrome associated with stigma and social isolation. Forty-two percent of people with dementia in the United States and almost 40% in the United Kingdom live in assisted living and residential care facilities. Up to 90% of residents with dementia experience behavioral and psychological symptoms of dementia (BPSD). Currently psychotropic drugs are often used to manage BPSD, despite the drugs' limited efficacy and adverse effects. Even though psychosocial approaches are as effective as medical ones without side effects, their uptake has been slow. Social networks that investigate the structure of relationships among residents and staff may represent an important resource to increase the uptake of psychosocial approaches and facilitate improvements in care. To conduct a systematic review of social network studies set in long-term care (LTC), including residents with dementia, and identify network factors influencing the care available to residents. Peer-reviewed articles across CINAHL, EMBASE, IBSS, Medline, PsychInfo, Scopus, and Web of Science were searched from January 1994 to December 2014 inclusive, using PRISMA guidelines. Studies included those examining social networks of residents or staff in LTC. Nine articles from studies in the United States, Europe, Asia, and Australia met search criteria. Resident networks had few social connections. One study proposed that residents with high centrality be encouraged to welcome new residents and disseminate information. The high density in 2 staff network studies was associated with the cooperation needed to provide care to residents with dementia. Staff's boundary-spanning led to higher-status nurses becoming more involved in decision-making and problem-solving in one study. In another, the outcome was staff treating residents with more respect and actively caring for them. These studies suggest interventions using a network approach may improve care services in LTC. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Finding the probability of infection in an SIR network is NP-Hard

PubMed Central

Shapiro, Michael; Delgado-Eckert, Edgar

2012-01-01

It is the purpose of this article to review results that have long been known to communications network engineers and have direct application to epidemiology on networks. A common approach in epidemiology is to study the transmission of a disease in a population where each individual is initially susceptible (S), may become infective (I) and then removed or recovered (R) and plays no further epidemiological role. Much of the recent work gives explicit consideration to the network of social interactions or disease-transmitting contacts and attendant probability of transmission for each interacting pair. The state of such a network is an assignment of the values {S, I, R} to its members. Given such a network, an initial state and a particular susceptible individual, we would like to compute their probability of becoming infected in the course of an epidemic. It turns out that this and related problems are NP-hard. In particular, it belongs in a class of problems for which no efficient algorithms for their solution are known. Moreover, finding an efficient algorithm for the solution of any problem in this class would entail a major breakthrough in theoretical computer science. PMID:22824138

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.

Alcohol Use and HIV Risk Within Social Networks of MSM Sex Workers in the Dominican Republic.

PubMed

Tan, Diane; Holloway, Ian W; Gildner, Jennifer; Jauregui, Juan C; Garcia Alvarez, Rafael; Guilamo-Ramos, Vincent

2017-11-01

To examine how alcohol-related HIV risk behaviors within MSM sex workers' social networks (SN) may be associated with individual risk behaviors, respondent-driven and venue-based sampling were used to collect demographic, behavioral and SN characteristics among MSM sex workers in Santo Domingo and Boca Chica (N = 220). The majority of participants reported problem drinking (71.0%) or alcohol use at their last sexual encounter (71.4%). Self-reported problem drinking was associated with SN characteristics (at least one member who recently got drunk aOR = 7.5, no religious/spiritual adviser aOR = 3.0, non-sexual network density aOR = 0.9), while self-reported alcohol use at last sex was associated with individual (drug use at last sex aOR = 4.4) and SN characteristics (at least one member with previous HIV/STI testing aOR = 4.7). Dominican MSM sex workers reported high alcohol use, which may increase their risk for HIV. A better understanding of SN factors associated with individual risk behaviors can help guide appropriate intervention development.

Trust estimation of the semantic web using semantic web clustering

NASA Astrophysics Data System (ADS)

Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

2017-05-01

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

Designing a CTSA‐Based Social Network Intervention to Foster Cross‐Disciplinary Team Science

PubMed Central

McCarty, Christopher; Conlon, Michael; Nelson, David R.

2015-01-01

Abstract This paper explores the application of network intervention strategies to the problem of assembling cross‐disciplinary scientific teams in academic institutions. In a project supported by the University of Florida (UF) Clinical and Translational Science Institute, we used VIVO, a semantic‐web research networking system, to extract the social network of scientific collaborations on publications and awarded grants across all UF colleges and departments. Drawing on the notion of network interventions, we designed an alteration program to add specific edges to the collaboration network, that is, to create specific collaborations between previously unconnected investigators. The missing collaborative links were identified by a number of network criteria to enhance desirable structural properties of individual positions or the network as a whole. We subsequently implemented an online survey (N = 103) that introduced the potential collaborators to each other through their VIVO profiles, and investigated their attitudes toward starting a project together. We discuss the design of the intervention program, the network criteria adopted, and preliminary survey results. The results provide insight into the feasibility of intervention programs on scientific collaboration networks, as well as suggestions on the implementation of such programs to assemble cross‐disciplinary scientific teams in CTSA institutions. PMID:25788258

Parallel and Distributed Systems for Probabilistic Reasoning

DTIC Science & Technology

2012-12-01

work at CMU I had the opportunity to work with Andreas Krause on Gaussian process models for signal quality estimation in wireless sensor networks ...we reviewed the natural parallelization of the belief propagation algorithm using the synchronous schedule and demonstrated both theoretically and...problem is that the power-law sparsity structure, commonly found in graphs derived from natural phenomena (e.g., social networks and the web

Female College Students’ Media Use and Academic Outcomes: Results from a Longitudinal Cohort Study

PubMed Central

Walsh, Jennifer L.; Fielder, Robyn L.; Carey, Kate B.; Carey, Michael P.

2013-01-01

This longitudinal study describes women’s media use during their first year of college and examines associations between media use and academic outcomes. Female students (N = 483, Mage = 18.1 years) reported on their use of 11 media forms and their grade point average, academic behaviors, academic confidence, and problems affecting schoolwork. Allowing for multi-tasking, women reported nearly 12 hours of media use per day; use of texting, music, the Internet, and social networking was heaviest. In general, media use was negatively associated with academic outcomes after controlling for prior academics and demographics. Exceptions were newspaper reading and music listening, which were positively associated with academic outcomes. There were significant indirect effects of magazine reading and social networking on GPA via academic behaviors, confidence, and problems. Results show that female college students are heavy users of new media, and that some forms of media use may adversely impact academic performance. PMID:24505554

Illuminating the dark matter of social neuroscience: Considering the problem of social interaction from philosophical, psychological, and neuroscientific perspectives.

PubMed

Przyrembel, Marisa; Smallwood, Jonathan; Pauen, Michael; Singer, Tania

2012-01-01

Successful human social interaction depends on our capacity to understand other people's mental states and to anticipate how they will react to our actions. Despite its importance to the human condition, the exact mechanisms underlying our ability to understand another's actions, feelings, and thoughts are still a matter of conjecture. Here, we consider this problem from philosophical, psychological, and neuroscientific perspectives. In a critical review, we demonstrate that attempts to draw parallels across these complementary disciplines is premature: The second-person perspective does not map directly to Interaction or Simulation theories, online social cognition, or shared neural network accounts underlying action observation or empathy. Nor does the third-person perspective map onto Theory-Theory (TT), offline social cognition, or the neural networks that support Theory of Mind (ToM). Moreover, we argue that important qualities of social interaction emerge through the reciprocal interplay of two independent agents whose unpredictable behavior requires that models of their partner's internal state be continually updated. This analysis draws attention to the need for paradigms in social neuroscience that allow two individuals to interact in a spontaneous and natural manner and to adapt their behavior and cognitions in a response contingent fashion due to the inherent unpredictability in another person's behavior. Even if such paradigms were implemented, it is possible that the specific neural correlates supporting such reciprocal interaction would not reflect computation unique to social interaction but rather the use of basic cognitive and emotional processes combined in a unique manner. Finally, we argue that given the crucial role of social interaction in human evolution, ontogeny, and every-day social life, a more theoretically and methodologically nuanced approach to the study of real social interaction will nevertheless help the field of social cognition to evolve.

[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.

Aberrant neural networks for the recognition memory of socially relevant information in patients with schizophrenia.

PubMed

Oh, Jooyoung; Chun, Ji-Won; Kim, Eunseong; Park, Hae-Jeong; Lee, Boreom; Kim, Jae-Jin

2017-01-01

Patients with schizophrenia exhibit several cognitive deficits, including memory impairment. Problems with recognition memory can hinder socially adaptive behavior. Previous investigations have suggested that altered activation of the frontotemporal area plays an important role in recognition memory impairment. However, the cerebral networks related to these deficits are not known. The aim of this study was to elucidate the brain networks required for recognizing socially relevant information in patients with schizophrenia performing an old-new recognition task. Sixteen patients with schizophrenia and 16 controls participated in this study. First, the subjects performed the theme-identification task during functional magnetic resonance imaging. In this task, pictures depicting social situations were presented with three words, and the subjects were asked to select the best theme word for each picture. The subjects then performed an old-new recognition task in which they were asked to discriminate whether the presented words were old or new. Task performance and neural responses in the old-new recognition task were compared between the subject groups. An independent component analysis of the functional connectivity was performed. The patients with schizophrenia exhibited decreased discriminability and increased activation of the right superior temporal gyrus compared with the controls during correct responses. Furthermore, aberrant network activities were found in the frontopolar and language comprehension networks in the patients. The functional connectivity analysis showed aberrant connectivity in the frontopolar and language comprehension networks in the patients with schizophrenia, and these aberrations possibly contribute to their low recognition performance and social dysfunction. These results suggest that the frontopolar and language comprehension networks are potential therapeutic targets in patients with schizophrenia.

The Influence of Social Media on Addictive Behaviors in College Students

PubMed Central

Steers, Mai-Ly N.; Moreno, Megan A.; Neighbors, Clayton

2016-01-01

Social media has become a primary way for college students to communicate aspects of their daily lives to those within their social network. Such communications often include substance use displays (e.g., selfies of college students drinking). Furthermore, students’ substance use displays have been found to robustly predict not only the posters’ substance use-related outcomes (e.g., consumption, problems) but also that of their social networking peers. Purpose of review The current review summarizes findings of recent literature exploring the intersection between social media and substance use. Recent findings Specifically, we examine how and why such substance use displays might shape college students’ internalized norms surrounding substance use and how it impacts their substance use-related behaviors. Summary Additional social media-related interventions are needed in order to target reduction of consumption among this at-risk group. We discuss the technological and methodological challenges inherent to conducting research and devising interventions in this domain. PMID:28458990

Neuroticism, social network, stressful life events: association with mood disorders, depressive symptoms and suicidal ideation in a community sample of women.

PubMed

Mandelli, Laura; Nearchou, Finiki A; Vaiopoulos, Chrysostomos; Stefanis, Costas N; Vitoratou, Silia; Serretti, Alessandro; Stefanis, Nicholas C

2015-03-30

According to the stress-diathesis hypothesis, depression and suicidal behavior may be precipitated by psychosocial stressors in vulnerable individuals. However, risk factors for mental health are often gender-specific. In the present study, we evaluated common risk factors for female depression in association with depressive symptoms and suicidal ideation in a community sample of women. The sample was composed by 415 women evaluated for mood disorders (MDs), depressive symptoms and suicidal ideation by structured interviews and the Beck depression inventory II (BDI II). All women also filled in the Eysenck personality questionnaire to evaluate neuroticism and were interviewed for social contact frequency and stressful life events (SLEs). In the whole sample, 19% of the women satisfied criteria for MD and suicidal ideation was reported by 12% of the women. Though stressful life events, especially personal and interpersonal problems, and poor social network were associated with all the outcome variables (mood disorder, depressive symptomatology and suicidal ideation), neuroticism survived to all multivariate analyses. Social network, together with neuroticism, also showed strong association with depressive severity, independently from current depressive state. Though we were unable to compare women and men, data obtained from the present study suggest that in women neurotic traits are strongly related to depression and suicidal ideation, and potentially mediate reporting of stressful life events and impaired social network. Independently from a current diagnosis of depression, impaired social network increases depressive symptoms in the women. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

NETWORK POSITION AND SEXUAL DYSFUNCTION: IMPLICATIONS OF PARTNER BETWEENNESS FOR MEN*

PubMed Central

Cornwell, Benjamin; Laumann, Edward O.

2013-01-01

This paper combines relational perspectives on gender identity with social network structural perspectives on health to understand men’s sexual functioning. We argue that network positions that afford independence and control over social resources are consistent with traditional masculine roles and may therefore affect men’s sexual performance. For example, when a heterosexual man’s female partner has more frequent contact with his confidants than he does–a situation that we refer to as partner betweenness – his relational autonomy, privacy, and control are constrained. Analyses of data from the National Social Life, Health, and Aging Project (NSHAP) show that about a quarter of men experience partner betweenness, and that these men are 92 percent more likely to report problems getting and/or maintaining an erection (95% CI: 1.274, 2.881). This association is strongest among the youngest men in the sample, which may reflect changing conceptions of masculinity in later life. We close by considering several explanations for these findings, and urge additional research on the linkages between health, gender, and network structure. PMID:22003520

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

PubMed Central

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

2016-01-01

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

A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

NASA Astrophysics Data System (ADS)

Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

2017-01-01

Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

Differences in social relations between persons with type 2 diabetes and the general population.

PubMed

Hempler, Nana Folmann; Ekholm, Ola; Willaing, Ingrid

2013-06-01

Poor social support and lack of social network are well-established risk factors for morbidity and mortality in general populations. Good social relations, such as social support and network contacts, are associated with better self-management and fewer psychosocial problems in persons with type 2 diabetes. The aim of this study was to investigate whether persons with type 2 diabetes have poorer social relations than the general population. We conducted a cross-sectional survey in three settings: a specialist diabetes clinic (SDC) (n = 1084), a web panel (WP) consisting of persons with type 2 diabetes (n = 1491) and a sample from the 2010 Danish Health and Morbidity Survey, representative of the general population (n = 15,165). We compared social relations using multivariate logistic regression. Compared to the general population, persons with type 2 diabetes more often lived without a partner (SDC, OR 1.75, 95% CI 1.49-2.06; WP, OR 1.64, 95% CI 1.43-1.87), met with family less than once a month (SDC, OR 1.78, 95% CI 1.40-2.27; WP, OR 2.35, 95% CI 1.94-2.84) and were less certain they could count on help from others in case of illness (WP, OR 1.23, 95% CI 1.08-1.41). Our findings suggest that persons with type 2 diabetes have poorer social relations than the general population. From a public health point of view, special attention is needed with regards to strengthening existing networks and establishing alternative networks among persons with type 2 diabetes.

Reducing racial disparities in obesity: simulating the effects of improved education and social network influence on diet behavior.

PubMed

Orr, Mark G; Galea, Sandro; Riddle, Matt; Kaplan, George A

2014-08-01

Understanding how to mitigate the present black-white obesity disparity in the United States is a complex issue, stemming from a multitude of intertwined causes. An appropriate but underused approach to guiding policy approaches to this problem is to account for this complexity using simulation modeling. We explored the efficacy of a policy that improved the quality of neighborhood schools in reducing racial disparities in obesity-related behavior and the dependence of this effect on social network influence and norms. We used an empirically grounded agent-based model to generate simulation experiments. We used a 2 × 2 × 2 factorial design that represented the presence or absence of improved neighborhood school quality, the presence or absence of social influence, and the type of social norm (healthy or unhealthy). Analyses focused on time trends in sociodemographic variables and diet quality. First, the quality of schools and social network influence had independent and interactive effects on diet behavior. Second, the black-white disparity in diet behavior was considerably reduced under some conditions, but never completely eliminated. Third, the degree to which the disparity in diet behavior was reduced was a function of the type of social norm that was in place; the reduction was the smallest when the type of social norm was healthy. Improving school quality can reduce, but not eliminate racial disparities in obesity-related behavior, and the degree to which this is true depends partly on social network effects. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysing collaboration among HIV agencies through combining network theory and relational coordination.

PubMed

Khosla, Nidhi; Marsteller, Jill Ann; Hsu, Yea Jen; Elliott, David L

2016-02-01

Agencies with different foci (e.g. nutrition, social, medical, housing) serve people living with HIV (PLHIV). Serving needs of PLHIV comprehensively requires a high degree of coordination among agencies which often benefits from more frequent communication. We combined Social Network theory and Relational Coordination theory to study coordination among HIV agencies in Baltimore. Social Network theory implies that actors (e.g., HIV agencies) establish linkages amongst themselves in order to access resources (e.g., information). Relational Coordination theory suggests that high quality coordination among agencies or teams relies on the seven dimensions of frequency, timeliness and accuracy of communication, problem-solving communication, knowledge of agencies' work, mutual respect and shared goals. We collected data on frequency of contact from 57 agencies using a roster method. Response options were ordinal ranging from 'not at all' to 'daily'. We analyzed data using social network measures. Next, we selected agencies with which at least one-third of the sample reported monthly or more frequent interaction. This yielded 11 agencies whom we surveyed on seven relational coordination dimensions with questions scored on a Likert scale of 1-5. Network density, defined as the proportion of existing connections to all possible connections, was 20% when considering monthly or higher interaction. Relational coordination scores from individual agencies to others ranged between 1.17 and 5.00 (maximum possible score 5). The average scores for different dimensions across all agencies ranged between 3.30 and 4.00. Shared goals (4.00) and mutual respect (3.91) scores were highest, while scores such as knowledge of each other's work and problem-solving communication were relatively lower. Combining theoretically driven analyses in this manner offers an innovative way to provide a comprehensive picture of inter-agency coordination and the quality of exchange that underlies collaborative ties. These methods together can identify areas that could be targeted to promote closer ties. Copyright © 2015 Elsevier Ltd. All rights reserved.

School Absenteeism: An Online Survey via Social Networks.

PubMed

Pflug, Verena; Schneider, Silvia

2016-06-01

School absenteeism is a significant social and public health problem. However, existing prevalence rates are often not representative due to biased assessment processes at schools. The present study assessed school absenteeism in Germany using a nationwide online self-report survey. Although our definition of school absenteeism was more conservative than in previous studies, nearly 9 % of the 1359 high school students reported school absenteeism within the past 7 days. Absent students lived less often with both parents, were on average of lower socioeconomic status, and reported more emotional problems, behavioral problems and less prosocial behavior than attending students. Being an indicator of a wide variety of problems in children and adolescents, school absenteeism deserves much more attention. Future directions for research and implications for prevention and intervention programs are discussed.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-01

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.

PubMed

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-28

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

So what exactly are social-ecological network studies? Findings from a literature review

EPA Science Inventory

To solve most environmental management problems academics and practitioners must work across traditionally compartmentalized management arenas (e.g., food, water, and wildlife) and among spatially distant ecosystems and resource users. Managing interdependent ecosystem services, ...

Social Context and Problem Factors among Youth with Juvenile Justice Involvement Histories.

PubMed

Voisin, Dexter R; Sales, Jessica M; Hong, Jun Sung; Jackson, Jerrold M; Rose, Eve S; DiClemente, Ralph J

2017-01-01

Youth with juvenile justice histories often reside in poorly resourced communities and report high rates of depression, gang involved networks, and STI-sexual related risk behaviors, compared to their counterparts. The primary aim of this study was to examine the relationship between social context (ie, a combined index score comprised of living in public housing, being a recipient of free school lunch, and witnessing community violence) and risk factors that are disproportionately worse for juvenile justice youth such as depression, gang involved networks and STI sexual risk behaviors. Data were collected from a sample of detained youth ages 14 to 16 (N = 489). Questions assessed demographics, social context, depression, gang-involved networks, and STI risk behaviors. Multiple logistic regression models, controlling for age, gender, race, school enrollment, and family social support, indicated that participants who reported poorer social context had double the odds of reporting being depressed; three times higher odds of being in a gang; three times higher odds of personally knowing a gang member; and double the odds of having engaged in STI-risk behaviors. These results provide significant information that can help service providers target certain profiles of youth with juvenile justice histories for early intervention initiatives.

Social isolation, drunkenness, and cigarette use among adolescents.

PubMed

Niño, Michael D; Cai, Tianji; Ignatow, Gabe

2016-02-01

This study compares isolated to sociable youth to investigate the relations between different network types of social isolation and alcohol and cigarette use. Using data from the National Longitudinal Study of Adolescent to Adult Health we developed a network measure that includes various types of social isolation. Types of social isolation were operationalized as socially avoidant, actively isolated, and socially disinterested, with sociable youth as the reference category. Random effects ordinal logit models were fit to estimate the association between different types of social isolation and drunkenness and cigarette use. Different types of social isolation had varying effects on drunkenness and cigarette use. On the one hand, socially disinterested youth were at an increased risk for drunkenness and cigarette use. On the other hand, socially avoidant youth had lower odds of drunkenness and no significant differences in cigarette use when compared to sociable youth. Actively isolated youth showed no differences in drunkenness and cigarette use. The role played by marginalized social positions in youth substance use is an important yet overlooked problem. This study can contribute to better targeted and more effective health behavior prevention efforts for vulnerable adolescents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ontological security and connectivity provided by pets: a study in the self-management of the everyday lives of people diagnosed with a long-term mental health condition.

PubMed

Brooks, Helen; Rushton, Kelly; Walker, Sandra; Lovell, Karina; Rogers, Anne

2016-12-09

Despite evidence that connecting people to relevant wellbeing-related resources brings therapeutic benefit, there is limited understanding, in the context of mental health recovery, of the potential value and contribution of pet ownership to personal support networks for self-management. This study aimed to explore the role of pets in the support and management activities in the personal networks of people with long-term mental health problems. Semi-structured interviews centred on 'ego' network mapping were conducted in two locations (in the North West and in the South of England) with 54 participants with a diagnosis of a long-term mental health problem. Interviews explored the day-to-day experience of living with a mental illness, informed by the notion of illness work undertaken by social network members within personal networks. Narratives were elicited that explored the relationship, value, utility and meaning of pets in the context of the provision of social support and management provided by other network members. Interviews were recorded, then transcribed verbatim before being analysed using a framework analysis. The majority of pets were placed in the central, most valued circle of support within the network diagrams. Pets were implicated in relational work through the provision of secure and intimate relationships not available elsewhere. Pets constituted a valuable source of illness work in managing feelings through distraction from symptoms and upsetting experiences, and provided a form of encouragement for activity. Pets were of enhanced salience where relationships with other network members were limited or difficult. Despite these benefits, pets were unanimously neither considered nor incorporated into individual mental health care plans. Drawing on a conceptual framework built on Corbin and Strauss's notion of illness 'work' and notions of a personal workforce of support undertaken within whole networks of individuals, this study contributes to our understanding of the role of pets in the daily management of long-term mental health problems. Pets should be considered a main rather than a marginal source of support in the management of long-term mental health problems, and this has implications for the planning and delivery of mental health services.

"Please Don't Make Me Ask for Help": Implicit Social Support and Mental Health in Chinese Individuals Living with HIV.

PubMed

Yang, Joyce P; Leu, Janxin; Simoni, Jane M; Chen, Wei Ti; Shiu, Cheng-Shi; Zhao, Hongxin

2015-08-01

China faces a growing HIV epidemic; psychosocial needs of HIV-positive individuals remain largely unaddressed. Research is needed to consider the gap between need for mental healthcare and lack of sufficiently trained professionals, in a culturally acceptable manner. This study assessed explicit and implicit forms of social support and mental health symptoms in 120 HIV-positive Chinese. Explicit social support refers to interactions involving active disclosure and discussion of problems and request for assistance, whereas implicit social support refers to the emotional comfort one obtains from social networks without disclosing problems. We hypothesized and found using multiple linear regression, that after controlling for demographics, only implicit, but not explicit social support positively predicted mental health. Future research is warranted on the effects of utilizing implicit social support to bolster mental health, which has the potential to circumvent the issues of both high stigma and low professional resources in this population.

Effective monitoring of agriculture: a response.

PubMed

Sachs, Jeffrey D; Remans, Roseline; Smukler, Sean M; Winowiecki, Leigh; Andelman, Sandy J; Cassman, Kenneth G; Castle, David; DeFries, Ruth; Denning, Glenn; Fanzo, Jessica; Jackson, Louise E; Leemans, Rik; Lehmann, Johannes; Milder, Jeffrey C; Naeem, Shahid; Nziguheba, Generose; Palm, Cheryl A; Pingali, Prabhu L; Reganold, John P; Richter, Daniel D; Scherr, Sara J; Sircely, Jason; Sullivan, Clare; Tomich, Thomas P; Sanchez, Pedro A

2012-03-01

The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. We welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on our earlier paper, "Monitoring the World's Agriculture" (Sachs et al., Nature, 2010, 466, 558-560). In this response, we address their three main critiques labeled as 'the passive approach', 'the problem with uniform metrics' and 'the problem with composite metrics'. We expand on specific research questions at the core of the network design, on the distinction between key universal and site-specific metrics to detect change over time and across scales, and on the need for composite metrics in decision-making. We believe that simultaneously measuring indicators of the three pillars of sustainability (environmentally sound, social responsible and economically viable) in an effectively integrated monitoring system will ultimately allow scientists and land managers alike to find solutions to the most pressing problems facing global food security. This journal is © The Royal Society of Chemistry 2012

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

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

Network dynamics of social influence in the wisdom of crowds

PubMed Central

Brackbill, Devon; Centola, Damon

2017-01-01

A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton’s discovery of the “wisdom of crowds” [Galton F (1907) Nature 75:450–451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals’ estimates became more similar when subjects observed each other’s beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020–9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error. PMID:28607070

Network dynamics of social influence in the wisdom of crowds.

PubMed

Becker, Joshua; Brackbill, Devon; Centola, Damon

2017-06-27

A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton's discovery of the "wisdom of crowds" [Galton F (1907) Nature 75:450-451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies ]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals' estimates became more similar when subjects observed each other's beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020-9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error.

[Internet addiction disorder and social networks: statistical analysis of correlation and study of the association with social interaction anxiousness].

PubMed

Rusconi, Anna Carlotta; Valeriani, Giuseppe; Carlone, Cristiano; Raimondo, Pasquale; Quartini, Adele; Coccanari de' Fornari, Maria Antonietta; Biondi, Massimo

2012-01-01

Internet Addiction Disorder (IAD) is an emerging psychiatric disorder, assimilable to impulse control problems and related to maladaptive use of new networks and social and virtual technologies. Our study aims to analyze the presence of IAD among adolescents and to study the correlation with social interaction anxiousness. We investigated also the possibility that the Social Network (SN) represent a source of risk for the development of IAD. The test group was composed of 250 subjects, aged between 14 and 18 years. They were administered: Young's IAT; IAS (Interaction Anxiousness Scale), AAS (Audience Anxiousness Scale) and SISST (Social Interaction Self-Statement Test) to analyze the dimension of social interaction anxiousness. We found a rate of 2% of the IAD. The SN are the most common use of the Net in our sample, but not the most clicked sites by subjects with IAD. It should be noted, finally, a correlation between social interaction anxiety and IAD, but not a significant difference in scores of social anxiousness scales based on the SN use/non-use. The use of SN intended as single variable doesn't correlate with increased risk for IAD, or for increased social interaction anxiousness. However, if associated with prolonged use of the net for 5-6 hours or more, or concomitant use of chat rooms and/or net gambling, we find a more significant risk of psychopathology. The data presented require further investigations, in order to guide new pathogenetic models and appropriate intervention strategies.

Emotion-Bracelet: A Web Service for Expressing Emotions through an Electronic Interface.

PubMed

Martinez, Alicia; Estrada, Hugo; Molina, Alejandra; Mejia, Manuel; Perez, Joaquin

2016-11-24

The mechanisms to communicate emotions have dramatically changed in the last 10 years with social networks, where users massively communicate their emotional states by using the Internet. However, people with socialization problems have difficulty expressing their emotions verbally or interpreting the environment and providing an appropriate emotional response. In this paper, a novel solution called the Emotion-Bracelet is presented that combines a hardware device and a software system. The proposed approach identifies the polarity and emotional intensity of texts published on a social network site by performing real-time processing using a web service. It also shows emotions with a LED matrix using five emoticons that represent positive, very positive, negative, very negative, and neutral states. The Emotion-Bracelet is designed to help people express their emotions in a non-intrusive way, thereby expanding the social aspect of human emotions.

Emotion-Bracelet: A Web Service for Expressing Emotions through an Electronic Interface

PubMed Central

Martinez, Alicia; Estrada, Hugo; Molina, Alejandra; Mejia, Manuel; Perez, Joaquin

2016-01-01

The mechanisms to communicate emotions have dramatically changed in the last 10 years with social networks, where users massively communicate their emotional states by using the Internet. However, people with socialization problems have difficulty expressing their emotions verbally or interpreting the environment and providing an appropriate emotional response. In this paper, a novel solution called the Emotion-Bracelet is presented that combines a hardware device and a software system. The proposed approach identifies the polarity and emotional intensity of texts published on a social network site by performing real-time processing using a web service. It also shows emotions with a LED matrix using five emoticons that represent positive, very positive, negative, very negative, and neutral states. The Emotion-Bracelet is designed to help people express their emotions in a non-intrusive way, thereby expanding the social aspect of human emotions. PMID:27886130

Complexity in Nature and Society: Complexity Management in the Age of Globalization

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. What are the laws of sociodynamics? Is there a socio-engineering of nonlinear problem solving? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the challenges of complexity in firms, institutions and other organizations? It is a main thesis of the talk that nature and society are basically governed by nonlinear and complex information dynamics. How computational is sociodynamics? What can we hope for social, economic and political problem solving in the age of globalization?.

Assessing new patient access to mental health providers in HMO networks.

PubMed

Barry, Colleen L; Venkatesh, Mohini; Busch, Susan H

2008-12-01

This study examined access to mental health providers in health maintenance organization (HMO) networks. A telephone survey was conducted with a stratified random sample of mental health providers listed as being in a network for at lease one of six HMOs operating in Connecticut (response rate=72%; N=366). Data were collected between December 2006 and March 2007. Measures included the accuracy of network listings, acceptance rates of new patients, and reasons for not accepting new patients. Acceptance of new patients was defined as scheduling an appointment within two weeks from the time of the initial contact. Logistic regression was used to examine acceptance rates of new patients while controlling for type of provider (social worker, nurse, psychologist, or psychiatrist) and practice characteristics. Findings indicate that 17% of sampled HMO network listings were inaccurate. Among the providers with an accurate listing, 73% were accepting new HMO patients and 76% were accepting new self-pay patients. These aggregate acceptance rates of new patients mask differences among providers, with psychiatrists significantly less likely than other providers to accept new patients (55% of psychiatrists were accepting new patients). The most common reason for not accepting new patients was the lack of available appointments. Results indicate that access to mental health providers in HMO networks varied by type of provider. For HMO enrollees seeking treatment for mental health problems from a provider with a master's degree in social work (M.S.W. degree), network access was not a major problem. Scheduling an appointment with a psychiatrist, particularly a psychiatrist treating children only, was more difficult.

Reducing Adverse Childhood Experiences (ACE) by Building Community Capacity: A Summary of Washington Family Policy Council Research Findings

PubMed Central

Hall, Judy; Porter, Laura; Longhi, Dario; Becker-Green, Jody; Dreyfus, Susan

2012-01-01

Community capacity for organization and collaboration has been shown to be a powerful tool for improving the health and well-being of communities. Since 1994 the Washington State Family Policy Council has supported the development of community capacity in 42 community public health and safety networks. Community networks bring local communities together to restructure natural supports and local resources to meet the needs of families and children, and increase cross-system coordination and flexible funding streams to improve local services and policy. In this study, researchers sought to demonstrate the strong impact of the community networks’ capacity to interrupt health and social problems. Findings suggest that community networks reduce health and safety problems for the entire community population. Further, community networks with high community capacity reduced adverse childhood experiences (ACE) in young adults ages 18–34. PMID:22970785

S68. SYMPTOMS, NEUROCOGNITION, SOCIAL COGNITION AND METACOGNITION IN SCHIZOPHRENIA: A NETWORK ANALYSIS

PubMed Central

Hasson-Ohayon, Ilanit; Goldzweig, Gil; Lavie, Adi; Luther, Lauren; Lysaker, Paul

2018-01-01

Abstract Background Schizophrenia is associated with broad range of phenomena which affect function and represent significant barriers to recovery. These include semi-independent forms of psychopathology, disturbances in neurocognition, social cognition and metacognition. The current study explores the paths through which these constructs affect each other and whether some of these phenomena play a relatively more or less central role than others as they interact. Answers to these questions seem essential to choosing which of a dizzying array of problems should be targeted by treatment. Methods Data was collected from 81 adult outpatients with schizophrenia or schizoaffective disorder, recruited at a Veterans’ Affairs Medical Center and a community mental health center in Indiana, USA. Network analysis which explored the relative relationships of five groups of symptoms (positive, negative, disorganization, hostility and emotional discomfort), six domains of neurocognition, four domains of social cognition and four domains of metacognition with one another was conducted. The analysis produces the following centrality measures: 1) strength of items within a network according to their sum weighted connections; 2) closeness between items that reflect the distance from a particular item to all others; 3) betweenness which reflect the number of times that an item appears on the shortest path between two other items. Results A clear differentiation between metacognition, social cognition, neurocognition and symptoms was observed. The only outliers were social cognition attribution, which was close to the symptoms area, and the cognitive symptoms factor that was found close to the neuro-cognition area. The social cognition was found in an “intermediate” area between the metacognition and neurocognition. Metacognition variables were the closest to the symptoms variables. The strongest nodes are: metacognition-self reflectivity, theory of mind measures of social cognition and visual memory. The nodes with the highest closeness measure were self-reflectivity sub-scale of metacognition and theory of mind of social cognition. The node with the highest betweenness measure was metacognition self-reflectivity. Discussion The centrality of the self-experience in schizophrenia is emphasized in phenomenological, theoretical as well as empirical literature and can be traced back to earlier writing on schizophrenia. Accordingly, a sense of barren or diminished self, problems in self-reflection and self-clarity as well as difficulties in agency and ownership over one’s thoughts, feelings and sensations which is necessary for creating meaning were reported and discussed. The current study adds to this body of literature the finding that in a network which includes symptoms, social cognition, neuro cognition and metacognition variables, self-reflection is standing out as being a central connector that has the strongest relationship with other variables. As such it impacts all the network, and interventions targeting metacognitive self-reflection are expected to have secondary effects on additional constructs in the network- i.e additional elements of metacognition, social cognition, neurocognition and symptoms.

CP-ABE Based Privacy-Preserving User Profile Matching in Mobile Social Networks

PubMed Central

Cui, Weirong; Du, Chenglie; Chen, Jinchao

2016-01-01

Privacy-preserving profile matching, a challenging task in mobile social networks, is getting more attention in recent years. In this paper, we propose a novel scheme that is based on ciphertext-policy attribute-based encryption to tackle this problem. In our scheme, a user can submit a preference-profile and search for users with matching-profile in decentralized mobile social networks. In this process, no participant’s profile and the submitted preference-profile is exposed. Meanwhile, a secure communication channel can be established between the pair of successfully matched users. In contrast to existing related schemes which are mainly based on the secure multi-party computation, our scheme can provide verifiability (both the initiator and any unmatched user cannot cheat each other to pretend to be matched), and requires few interactions among users. We provide thorough security analysis and performance evaluation on our scheme, and show its advantages in terms of security, efficiency and usability over state-of-the-art schemes. PMID:27337001

CP-ABE Based Privacy-Preserving User Profile Matching in Mobile Social Networks.

PubMed

Cui, Weirong; Du, Chenglie; Chen, Jinchao

2016-01-01

Privacy-preserving profile matching, a challenging task in mobile social networks, is getting more attention in recent years. In this paper, we propose a novel scheme that is based on ciphertext-policy attribute-based encryption to tackle this problem. In our scheme, a user can submit a preference-profile and search for users with matching-profile in decentralized mobile social networks. In this process, no participant's profile and the submitted preference-profile is exposed. Meanwhile, a secure communication channel can be established between the pair of successfully matched users. In contrast to existing related schemes which are mainly based on the secure multi-party computation, our scheme can provide verifiability (both the initiator and any unmatched user cannot cheat each other to pretend to be matched), and requires few interactions among users. We provide thorough security analysis and performance evaluation on our scheme, and show its advantages in terms of security, efficiency and usability over state-of-the-art schemes.

Inferring the mesoscale structure of layered, edge-valued, and time-varying networks

NASA Astrophysics Data System (ADS)

Peixoto, Tiago P.

2015-10-01

Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.

Understanding The Decision Context: DPSIR, Decision Landscape, And Social Network Analysis

EPA Science Inventory

Establishing the decision context for a management problem is the critical first step for effective decision analysis. Understanding the decision context allow stakeholders and decision-makers to integrate the societal, environmental, and economic considerations that must be con...

Network collaboration of organisations for homeless individuals in the Montreal region

PubMed Central

Fleury, Marie-Josée; Grenier, Guy; Lesage, Alain; Ma, Nan; Ngui, André Ngamini

2014-01-01

Introduction We know little about the intensity and determinants of interorganisational collaboration within the homeless network. This study describes the characteristics and relationships (along with the variables predicting their degree of interorganisational collaboration) of 68 organisations of such a network in Montreal (Quebec, Canada). Theory and methods Data were collected primarily through a self-administered questionnaire. Descriptive analyses were conducted followed by social network and multivariate analyses. Results The Montreal homeless network has a high density (50.5%) and a decentralised structure and maintains a mostly informal collaboration with the public and cross-sectorial sectors. The network density showed more frequent contacts among four types of organisations which could point to the existence of cliques. Four variables predicted interorganisational collaboration: organisation type, number of services offered, volume of referrals and satisfaction with the relationships with public organisations. Conclusions and discussion The Montreal homeless network seems adequate to address non-complex homelessness problems. Considering, however, that most homeless individuals present chronic and complex profiles, it appears necessary to have a more formal and better integrated network of homeless organisations, particularly in the health and social service sectors, in order to improve services. PMID:24520216

Networks in Social Policy Problems

NASA Astrophysics Data System (ADS)

Vedres, Balázs; Scotti, Marco

2012-08-01

1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.

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

PubMed

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

2017-06-22

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

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

PubMed Central

Fagan, Jesse M; Collins, Tom

2017-01-01

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

Prognostic significance of social network, social support and loneliness for course of major depressive disorder in adulthood and old age.

PubMed

van den Brink, R H S; Schutter, N; Hanssen, D J C; Elzinga, B M; Rabeling-Keus, I M; Stek, M L; Comijs, H C; Penninx, B W J H; Oude Voshaar, R C

2018-06-01

Poor recovery from depressive disorder has been shown to be related to low perceived social support and loneliness, but not to social network size or frequency of social interactions. Some studies suggest that the significance of social relationships for depression course may be greater in younger than in older patients, and may differ between men and women. None of the studies examined to what extent the different aspects of social relationships have unique or overlapping predictive values for depression course. It is the aim of the present study to examine the differential predictive values of social network characteristics, social support and loneliness for the course of depressive disorder, and to test whether these predictive associations are modified by gender or age. Two naturalistic cohort studies with the same design and overlapping instruments were combined to obtain a study sample of 1474 patients with a major depressive disorder, of whom 1181 (80.1%) could be studied over a 2-year period. Social relational variables were assessed at baseline. Two aspects of depression course were studied: remission at 2-year follow-up and change in depression severity over the follow-up period. By means of logistic regression and random coefficient analysis, the individual and combined predictive values of the different social relational variables for depression course were studied, controlling for potential confounders and checking for effect modification by age (below 60 v. 60 years or older) and gender. Multiple aspects of the social network, social support and loneliness were related to depression course, independent of potential confounders - including depression severity - but when combined, their predictive values were found to overlap to a large extent. Only the social network characteristic of living in a larger household, the social support characteristic of few negative experiences with the support from a partner or close friend, and limited feelings of loneliness proved to have unique predictive value for a favourable course of depression. Little evidence was found for effect modification by gender or age. If depressed persons experience difficulties in their social relationships, this may impede their recovery. Special attention for interpersonal problems, social isolation and feelings of loneliness seems warranted in depression treatment and relapse prevention. It will be of great interest to test whether social relational interventions can contribute to better recovery and relapse prevention of depressive disorder.

The effects of maternal alcohol use disorders on childhood relationships and mental health.

PubMed

Wolfe, Joseph D

2016-10-01

Despite millions of children living in the turmoil of their parents' active alcoholism or the aftermath of past abuse, research to date has not (1) provided a comprehensive examination of the effects of maternal alcohol use disorders (AUDs) on children's social ties outside of their relationships with parents, or (2) considered whether the number and quality of childhood social ties alter the effects of maternal AUDs on children's mental health. Using data from the National Longitudinal Surveys of Youth 1979 Children and Young Adults, analysis examined the influence of maternal AUDs on the number and quality of children's ties with siblings, extended family and family friends, peers, and neighborhood members. The analysis also considered how children's social ties influenced the association between maternal AUDs and children's internalizing and externalizing problems. Children of alcoholic mothers had similarly sized networks but more distant relationships with siblings and friends, negative interactions with classmates, and isolating neighborhoods. Controlling for these aspects of children's social ties substantially reduced mental health disparities between children of alcoholic mothers and other children. Findings support the view that maternal alcohol use disorders have the potential to damage children's mental health while also setting into motion long-term relationship problems. Future research should examine the networks of children who experience parental AUDs to further clarify the social processes that link parental AUDs to children's mental health.

Cascade phenomenon against subsequent failures in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liu, Zhi-Quan; He, Xuan; Ma, Jian-Feng

2018-06-01

Cascade phenomenon may lead to catastrophic disasters which extremely imperil the network safety or security in various complex systems such as communication networks, power grids, social networks and so on. In some flow-based networks, the load of failed nodes can be redistributed locally to their neighboring nodes to maximally preserve the traffic oscillations or large-scale cascading failures. However, in such local flow redistribution model, a small set of key nodes attacked subsequently can result in network collapse. Then it is a critical problem to effectively find the set of key nodes in the network. To our best knowledge, this work is the first to study this problem comprehensively. We first introduce the extra capacity for every node to put up with flow fluctuations from neighbors, and two extra capacity distributions including degree based distribution and average distribution are employed. Four heuristic key nodes discovering methods including High-Degree-First (HDF), Low-Degree-First (LDF), Random and Greedy Algorithms (GA) are presented. Extensive simulations are realized in both scale-free networks and random networks. The results show that the greedy algorithm can efficiently find the set of key nodes in both scale-free and random networks. Our work studies network robustness against cascading failures from a very novel perspective, and methods and results are very useful for network robustness evaluations and protections.

Social capital in settings with a high concentration of road traffic injuries. The case of Cuernavaca, Mexico.

PubMed

Inclán, Cristina; Hijar, Martha; Tovar, Victor

2005-11-01

There exists a differential ability within local communities to maintain effective social controls to prevent road traffic injuries (RTIs) in high risks areas. In 2002 we conducted a cross-sectional study in Cuernavaca, Mexico which incorporated 339 adults living in three areas which were characterized by high RTI concentrations. Multivariate analyses demonstrated that even when participants perceived RTIs as a local problem, they expressed no expectations that community members would exert social control through their involvement in local issues and law adherence. The study revealed four key conclusions regarding the association between the low levels of social capital and RTIs: (a) public roads are used solely for transportation, are not viewed as a communal space, and consequently reciprocity is not viewed as a relevant way of controlling behaviors in public places; (b) "strong immediate personal networks" bring about a lack of reciprocity between those sharing the public space which generates uncooperative behavior; (c) high levels of residential instability hinders the identification of common problems; (d) when there exists a low level of civic commitment and a scarcity of social resources directed towards the problem, the possibilities of social control over RTIs are low.

Aberrant within- and between-network connectivity of the mirror neuron system network and the mentalizing network in first episode psychosis.

PubMed

Choe, Eugenie; Lee, Tae Young; Kim, Minah; Hur, Ji-Won; Yoon, Youngwoo Bryan; Cho, Kang-Ik K; Kwon, Jun Soo

2018-03-26

It has been suggested that the mentalizing network and the mirror neuron system network support important social cognitive processes that are impaired in schizophrenia. However, the integrity and interaction of these two networks have not been sufficiently studied, and their effects on social cognition in schizophrenia remain unclear. Our study included 26 first-episode psychosis (FEP) patients and 26 healthy controls. We utilized resting-state functional connectivity to examine the a priori-defined mirror neuron system network and the mentalizing network and to assess the within- and between-network connectivities of the networks in FEP patients. We also assessed the correlation between resting-state functional connectivity measures and theory of mind performance. FEP patients showed altered within-network connectivity of the mirror neuron system network, and aberrant between-network connectivity between the mirror neuron system network and the mentalizing network. The within-network connectivity of the mirror neuron system network was noticeably correlated with theory of mind task performance in FEP patients. The integrity and interaction of the mirror neuron system network and the mentalizing network may be altered during the early stages of psychosis. Additionally, this study suggests that alterations in the integrity of the mirror neuron system network are highly related to deficient theory of mind in schizophrenia, and this problem would be present from the early stage of psychosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Designing a CTSA-Based Social Network Intervention to Foster Cross-Disciplinary Team Science.

PubMed

Vacca, Raffaele; McCarty, Christopher; Conlon, Michael; Nelson, David R

2015-08-01

This paper explores the application of network intervention strategies to the problem of assembling cross-disciplinary scientific teams in academic institutions. In a project supported by the University of Florida (UF) Clinical and Translational Science Institute, we used VIVO, a semantic-web research networking system, to extract the social network of scientific collaborations on publications and awarded grants across all UF colleges and departments. Drawing on the notion of network interventions, we designed an alteration program to add specific edges to the collaboration network, that is, to create specific collaborations between previously unconnected investigators. The missing collaborative links were identified by a number of network criteria to enhance desirable structural properties of individual positions or the network as a whole. We subsequently implemented an online survey (N = 103) that introduced the potential collaborators to each other through their VIVO profiles, and investigated their attitudes toward starting a project together. We discuss the design of the intervention program, the network criteria adopted, and preliminary survey results. The results provide insight into the feasibility of intervention programs on scientific collaboration networks, as well as suggestions on the implementation of such programs to assemble cross-disciplinary scientific teams in CTSA institutions. © 2015 Wiley Periodicals, Inc.

Social management of laboratory rhesus macaques housed in large groups using a network approach: A review.

PubMed

McCowan, Brenda; Beisner, Brianne; Hannibal, Darcy

2017-12-07

Biomedical facilities across the nation and worldwide aim to develop cost-effective methods for the reproductive management of macaque breeding groups, typically by housing macaques in large, multi-male multi-female social groups that provide monkey subjects for research as well as appropriate socialization for their psychological well-being. One of the most difficult problems in managing socially housed macaques is their propensity for deleterious aggression. From a management perspective, deleterious aggression (as opposed to less intense aggression that serves to regulate social relationships) is undoubtedly the most problematic behavior observed in group-housed macaques, which can readily escalate to the degree that it causes social instability, increases serious physical trauma leading to group dissolution, and reduces psychological well-being. Thus for both welfare and other management reasons, aggression among rhesus macaques at primate centers and facilities needs to be addressed with a more proactive approach.Management strategies need to be instituted that maximize social housing while also reducing problematic social aggression due to instability using efficacious methods for detection and prevention in the most cost effective manner. Herein we review a new proactive approach using social network analysis to assess and predict deleterious aggression in macaque groups. We discovered three major pathways leading to instability, such as unusually high rates and severity of trauma and social relocations.These pathways are linked either directly or indirectly to network structure in rhesus macaque societies. We define these pathways according to the key intrinsic and extrinsic variables (e.g., demographic, genetic or social factors) that influence network and behavioral measures of stability (see Fig. 1). They are: (1) presence of natal males, (2) matrilineal genetic fragmentation, and (3) the power structure and conflict policing behavior supported by this power structure. We discuss how these three major pathways leading to greater understanding and predictability of deleterious aggression in macaque social groups. Copyright © 2017. Published by Elsevier B.V.

Mental Health and Social Networks After Disaster.

PubMed

Bryant, Richard A; Gallagher, H Colin; Gibbs, Lisa; Pattison, Philippa; MacDougall, Colin; Harms, Louise; Block, Karen; Baker, Elyse; Sinnott, Vikki; Ireton, Greg; Richardson, John; Forbes, David; Lusher, Dean

2017-03-01

Although disasters are a major cause of mental health problems and typically affect large numbers of people and communities, little is known about how social structures affect mental health after a disaster. The authors assessed the extent to which mental health outcomes after disaster are associated with social network structures. In a community-based cohort study of survivors of a major bushfire disaster, participants (N=558) were assessed for probable posttraumatic stress disorder (PTSD) and probable depression. Social networks were assessed by asking participants to nominate people with whom they felt personally close. These nominations were used to construct a social network map that showed each participant's ties to other participants they nominated and also to other participants who nominated them. This map was then analyzed for prevailing patterns of mental health outcomes. Depression risk was higher for participants who reported fewer social connections, were connected to other depressed people, or were connected to people who had left their community. PTSD risk was higher if fewer people reported being connected with the participant, if those who felt close to the participant had higher levels of property loss, or if the participant was linked to others who were themselves not interconnected. Interestingly, being connected to other people who in turn were reciprocally close to each other was associated with a lower risk of PTSD. These findings provide the first evidence of disorder-specific patterns in relation to one's social connections after disaster. Depression appears to co-occur in linked individuals, whereas PTSD risk is increased with social fragmentation. These patterns underscore the need to adopt a sociocentric perspective of postdisaster mental health in order to better understand the potential for societal interventions in the wake of disaster.

Learning To Live with Complexity.

ERIC Educational Resources Information Center

Dosa, Marta

Neither the design of information systems and networks nor the delivery of library services can claim true user centricity without an understanding of the multifaceted psychological environment of users and potential users. The complexity of the political process, social problems, challenges to scientific inquiry, entrepreneurship, and…

Ensemble method: Community detection based on game theory

NASA Astrophysics Data System (ADS)

Zhang, Xia; Xia, Zhengyou; Xu, Shengwu; Wang, J. D.

2014-08-01

Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

A Virtual Reality Exposure Therapy Application for Iraq War Post Traumatic Stress Disorder

DTIC Science & Technology

2006-01-01

denial of social problems. Prior to the availability of VR therapy applications, the existing standard of care for PTSD was imaginal exposure...The application is built on ICT’s FlatWorld Simulation Control Architecture (FSCA) [13]. The FSCA enables a network -centric system of client displays...client-side interaction despite potential network delays. FCSA scripting is based on the Lua programming language [14] and provides facilities for real

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

PubMed

Gibbs, David L; Shmulevich, Ilya

2017-06-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

Detecting network communities beyond assortativity-related attributes

NASA Astrophysics Data System (ADS)

Liu, Xin; Murata, Tsuyoshi; Wakita, Ken

2014-07-01

In network science, assortativity refers to the tendency of links to exist between nodes with similar attributes. In social networks, for example, links tend to exist between individuals of similar age, nationality, location, race, income, educational level, religious belief, and language. Thus, various attributes jointly affect the network topology. An interesting problem is to detect community structure beyond some specific assortativity-related attributes ρ, i.e., to take out the effect of ρ on network topology and reveal the hidden community structures which are due to other attributes. An approach to this problem is to redefine the null model of the modularity measure, so as to simulate the effect of ρ on network topology. However, a challenge is that we do not know to what extent the network topology is affected by ρ and by other attributes. In this paper, we propose a distance modularity, which allows us to freely choose any suitable function to simulate the effect of ρ. Such freedom can help us probe the effect of ρ and detect the hidden communities which are due to other attributes. We test the effectiveness of distance modularity on synthetic benchmarks and two real-world networks.

Discussion on the Technology and Method of Computer Network Security Management

NASA Astrophysics Data System (ADS)

Zhou, Jianlei

2017-09-01

With the rapid development of information technology, the application of computer network technology has penetrated all aspects of society, changed people's way of life work to a certain extent, brought great convenience to people. But computer network technology is not a panacea, it can promote the function of social development, but also can cause damage to the community and the country. Due to computer network’ openness, easiness of sharing and other characteristics, it had a very negative impact on the computer network security, especially the loopholes in the technical aspects can cause damage on the network information. Based on this, this paper will do a brief analysis on the computer network security management problems and security measures.

Emergence of consensus as a modular-to-nested transition in communication dynamics

NASA Astrophysics Data System (ADS)

Borge-Holthoefer, Javier; Baños, Raquel A.; Gracia-Lázaro, Carlos; Moreno, Yamir

2017-01-01

Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources -visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems.

Emergence of consensus as a modular-to-nested transition in communication dynamics.

PubMed

Borge-Holthoefer, Javier; Baños, Raquel A; Gracia-Lázaro, Carlos; Moreno, Yamir

2017-01-30

Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources -visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems.

Emergence of consensus as a modular-to-nested transition in communication dynamics

PubMed Central

Borge-Holthoefer, Javier; Baños, Raquel A.; Gracia-Lázaro, Carlos; Moreno, Yamir

2017-01-01

Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources –visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems. PMID:28134358

Overview of Aro Program on Network Science for Human Decision Making

NASA Astrophysics Data System (ADS)

West, Bruce J.

This program brings together researchers from disparate disciplines to work on a complex research problem that defies confinement within any single discipline. Consequently, not only are new and rewarding solutions sought and obtained for a problem of importance to society and the Army, that is, the human dimension of complex networks, but, in addition, collaborations are established that would not otherwise have formed given the traditional disciplinary compartmentalization of research. This program develops the basic research foundation of a science of networks supporting the linkage between the physical and human (cognitive and social) domains as they relate to human decision making. The strategy is to extend the recent methods of non-equilibrium statistical physics to non-stationary, renewal stochastic processes that appear to be characteristic of the interactions among nodes in complex networks. We also pursue understanding of the phenomenon of synchronization, whose mathematical formulation has recently provided insight into how complex networks reach accommodation and cooperation. The theoretical analyses of complex networks, although mathematically rigorous, often elude analytic solutions and require computer simulation and computation to analyze the underlying dynamic process.

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Controlling nosocomial infection based on structure of hospital social networks.

PubMed

Ueno, Taro; Masuda, Naoki

2008-10-07

Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.

Prediction of employer-employee relationships from sociodemographic variables and social values in Brunei public and private sector workers.

PubMed

Mundia, Lawrence; Mahalle, Salwa; Matzin, Rohani; Nasir Zakaria, Gamal Abdul; Abdullah, Nor Zaiham Midawati; Abdul Latif, Siti Norhedayah

2017-01-01

The purpose of the study was to identify the sociodemographic variables and social value correlates and predictors of employer-employee relationship problems in a random sample of 860 Brunei public and private sector workers of both genders. A quantitative field survey design was used and data were analyzed by correlation and logistic regression. The rationale and justification for using this approach is explained. The main sociodemographic correlates and predictors of employer-employee relationship problems in this study were educational level and the district in which the employee resided and worked. Other correlates, but not necessarily predictors, of employer-employee relationship problems were seeking help from the Bomo (traditional healer); obtaining help from online social networking; and workers with children in the family. The two best and most significant social value correlates and predictors of employer-employee relationship problems included interpersonal communications; and self-regulation and self-direction. Low scorers on the following variables were also associated with high likelihood for possessing employer-employee relationship problems: satisfaction with work achievements; and peace and security, while low scorers on work stress had lower odds of having employer-employee relationship problems. Other significant social value correlates, but not predictors of employer-employee relationship problems were self-presentation; interpersonal trust; peace and security; and general anxiety. Consistent with findings of relevant previous studies conducted elsewhere, there were the variables that correlated with and predicted employer-employee relationship problems in Brunei public and private sector workers. Having identified these, the next step, efforts and priority should be directed at addressing the presenting issues via counseling and psychotherapy with affected employees. Further research is recommended to understand better the problem and its possible solutions.

Prediction of employer–employee relationships from sociodemographic variables and social values in Brunei public and private sector workers

PubMed Central

Mundia, Lawrence; Mahalle, Salwa; Matzin, Rohani; Nasir Zakaria, Gamal Abdul; Abdullah, Nor Zaiham Midawati; Abdul Latif, Siti Norhedayah

2017-01-01

The purpose of the study was to identify the sociodemographic variables and social value correlates and predictors of employer–employee relationship problems in a random sample of 860 Brunei public and private sector workers of both genders. A quantitative field survey design was used and data were analyzed by correlation and logistic regression. The rationale and justification for using this approach is explained. The main sociodemographic correlates and predictors of employer–employee relationship problems in this study were educational level and the district in which the employee resided and worked. Other correlates, but not necessarily predictors, of employer–employee relationship problems were seeking help from the Bomo (traditional healer); obtaining help from online social networking; and workers with children in the family. The two best and most significant social value correlates and predictors of employer–employee relationship problems included interpersonal communications; and self-regulation and self-direction. Low scorers on the following variables were also associated with high likelihood for possessing employer–employee relationship problems: satisfaction with work achievements; and peace and security, while low scorers on work stress had lower odds of having employer–employee relationship problems. Other significant social value correlates, but not predictors of employer–employee relationship problems were self-presentation; interpersonal trust; peace and security; and general anxiety. Consistent with findings of relevant previous studies conducted elsewhere, there were the variables that correlated with and predicted employer–employee relationship problems in Brunei public and private sector workers. Having identified these, the next step, efforts and priority should be directed at addressing the presenting issues via counseling and psychotherapy with affected employees. Further research is recommended to understand better the problem and its possible solutions. PMID:28769597

Community Interagency Connections for Immigrant Worker Health Interventions, King County, Washington State, 2012-2013.

PubMed

Tsai, Jenny Hsin-Chin; Petrescu-Prahova, Miruna

2016-06-02

Cross-sector community partnerships are a potentially powerful strategy to address population health problems, including health disparities. US immigrants - commonly employed in low-wage jobs that pose high risks to their health - experience such disparities because of hazardous exposures in the workplace. Hazardous exposures contribute to chronic health problems and complicate disease management. Moreover, prevention strategies such as worksite wellness programs are not effective for low-wage immigrant groups. The purpose of this article was to describe an innovative application of social network analysis to characterize interagency connections and knowledge needed to design and deliver a comprehensive community-based chronic disease prevention program for immigrant workers. Using iterative sample expansion, we identified 42 agencies representing diverse community sectors (service agencies, faith-based organizations, unions, nonprofits, government agencies) pertinent to the health of Chinese immigrant workers. To capture data on shared information, resources, and services as well as organizational characteristics, we jointly interviewed 2 representatives from each agency. We used social network analysis to describe interagency network structure and the positions of agencies within the networks. Agency interconnections were established primarily for information sharing. In the overall interagency network, a few service-oriented agencies held central or gatekeeper positions. Strong interconnectedness occurred predominately across service, public, and nonprofit sectors. The Chinese and Pan-Asian service sectors showed the strongest interconnectedness. Network analysis yields critical understanding of community structural links and assets needed to inform decisions about actual and potential community collaborations. Alternative intervention strategies may be needed to address health disparities among immigrant workers.

Drug use disorders and post-traumatic stress disorder over 25 adult years: role of psychopathology in relational networks.

PubMed

Balan, Sundari; Widner, Greg; Shroff, Manan; van den Berk-Clark, Carissa; Scherrer, Jeffrey; Price, Rumi Kato

2013-11-01

In traumatized populations, drug use disorders and post-traumatic stress disorder (PTSD) persist for many years. Relational factors that mediate this persistence have rarely been systematically examined. Our aim is to examine the relative effects of psychopathology in familial and non-familial networks on the persistence of both disorders over adulthood. We utilized longitudinal data from an epidemiologically ascertained sample of male Vietnam veterans (n=642). Measures included DSM-IV drug use disorders, other psychiatric disorders, network problem history and time-varying marital and employment characteristics. Longitudinal measures of veterans' psychopathology and social functioning were retrospectively obtained for each year over a 25 year period. We used generalized estimating equations (GEE) to estimate the relative effects of network problems on veteran's drug use disorders and PTSD after adjusting for covariates. Veterans' mean age was 47 years in 1996. Prevalence of illicit drug disorders declined from 29.8% in 1972 to 8.3% in 1996, but PTSD remained at 11.7% from 13.2% in 1972. While 17.0% of veterans reported a familial drug use problem, 24.9% reported a non-familial drug use problem. In full GEE models, a non-familial drug problem was a significant predictor of illicit drug use disorders over 25 years (OR=2.21, CI=1.59-3.09), while both familial depression (OR=1.69, CI=1.07-2.68) and non-familial drinking problem (OR=1.66, CI=1.08-2.54) were significant predictors of PTSD over 25 years. Familial and non-familial problems in networks differentially affect the persistence of drug use disorders and PTSD in traumatized male adults. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Brain State Differentiation and Behavioral Inflexibility in Autism†

PubMed Central

Uddin, Lucina Q.; Supekar, Kaustubh; Lynch, Charles J.; Cheng, Katherine M.; Odriozola, Paola; Barth, Maria E.; Phillips, Jennifer; Feinstein, Carl; Abrams, Daniel A.; Menon, Vinod

2015-01-01

Autism spectrum disorders (ASDs) are characterized by social impairments alongside cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been characterized, the neurobiological basis of inflexibility and its relation to core clinical symptoms of the disorder are unknown. We acquired functional neuroimaging data from 2 cohorts, each consisting of 17 children with ASDs and 17 age- and IQ-matched typically developing (TD) children, during stimulus-evoked brain states involving performance of social attention and numerical problem solving tasks, as well as during intrinsic, resting brain states. Effective connectivity between key nodes of the salience network, default mode network, and central executive network was used to obtain indices of functional organization across evoked and intrinsic brain states. In both cohorts examined, a machine learning algorithm was able to discriminate intrinsic (resting) and evoked (task) functional brain network configurations more accurately in TD children than in children with ASD. Brain state discriminability was related to severity of restricted and repetitive behaviors, indicating that weak modulation of brain states may contribute to behavioral inflexibility in ASD. These findings provide novel evidence for a potential link between neurophysiological inflexibility and core symptoms of this complex neurodevelopmental disorder. PMID:25073720

Measurement and visualization of face-to-face interaction among community-dwelling older adults using wearable sensors.

PubMed

Masumoto, Kouhei; Yaguchi, Takaharu; Matsuda, Hiroshi; Tani, Hideaki; Tozuka, Keisuke; Kondo, Narihiko; Okada, Shuichi

2017-10-01

A number of interventions have been undertaken to develop and promote social networks among community-dwelling older adults. However, it has been difficult to examine the effects of these interventions, because of problems in assessing interactions. The present study was designed to quantitatively measure and visualize face-to-face interactions among elderly participants in an exercise program. We also examined relationships among interactional variables, personality and interest in community involvement, including interactions with the local community. Older adults living in the same community were recruited to participate in an exercise program that consisted of four sessions. We collected data on face-to-face interactions of the participants by using a wearable sensor technology device. Network analysis identified the communication networks of participants in the exercise program, as well as changes in these networks. Additionally, there were significant correlations between the number of people involved in face-to-face interactions and changes in both interest in community involvement and interactions with local community residents, as well as personality traits, including agreeableness. Social networks in the community are essential for solving problems caused by the aging society. We showed the possible applications of face-to-face interactional data for identifying core participants having many interactions, and isolated participants having only a few interactions within the community. Such data would be useful for carrying out efficient interventions for increasing participants' involvement with their community. Geriatr Gerontol Int 2017; 17: 1752-1758. © 2017 Japan Geriatrics Society.

Propagation and immunization of infection on general networks with both homogeneous and heterogeneous components

NASA Astrophysics Data System (ADS)

Liu, Zonghua; Lai, Ying-Cheng; Ye, Nong

2003-03-01

We consider the entire spectrum of architectures of general networks, ranging from being heterogeneous (scale-free) to homogeneous (random), and investigate the infection dynamics by using a three-state epidemiological model that does not involve the mechanism of self-recovery. This model is relevant to realistic situations such as the propagation of a flu virus or information over a social network. Our heuristic analysis and computations indicate that (1) regardless of the network architecture, there exists a substantial fraction of nodes that can never be infected and (2) heterogeneous networks are relatively more robust against spreads of infection as compared with homogeneous networks. We have also considered the problem of immunization for preventing wide spread of infection, with the result that targeted immunization is effective for heterogeneous networks.

Dynamical networks of influence in small group discussions.

PubMed

Moussaïd, Mehdi; Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network-a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences.

Loneliness as the cause and the effect of problematic Internet use: the relationship between Internet use and psychological well-being.

PubMed

Kim, Junghyun; LaRose, Robert; Peng, Wei

2009-08-01

The current research started from the assumption that one of the major motives driving individuals' Internet use is to relieve psychosocial problems (e.g., loneliness, depression). This study showed that individuals who were lonely or did not have good social skills could develop strong compulsive Internet use behaviors resulting in negative life outcomes (e.g., harming other significant activities such as work, school, or significant relationships) instead of relieving their original problems. Such augmented negative outcomes were expected to isolate individuals from healthy social activities and lead them into more loneliness. Even though previous research suggests that social use of the Internet (e.g., social networking sites, instant messaging) could be more problematic than entertainment use (e.g., downloading files), the current study showed that the former did not show stronger associations than the latter in the key paths leading to compulsive Internet use.

Social capital and health: implication for health promotion by lay citizens in Japan.

PubMed

Miyamoto, Keiko; Iwakuma, Miho; Nakayama, Takeo

2015-12-01

A non-profit organization was formed in 2009 by lay citizens of Nagahama, Japan in response to a community-based genome-epidemiologic study, the 'Nagahama Zero(0)-ji Prevention Cohort Project (N0PCP)'. This organization aims to promote health by taking advantage of citizens' social networks. The Ottawa Charter for Health Promotion affirms the importance of creating supportive environments and coordinating social relationships. Supportive environments (infrastructure) and social relationships (resources) work together as aspects of social capital. This study sought to examine the association between self-rated health and social capital, at both individual and neighborhood levels, and to discuss suitable health promotion strategies for local circumstances.A cross-sectional survey was conducted in 2011, using a self-administered postal questionnaire. Social capital indicators included aspects of support in the environment (social support, neighborhood connectedness, informal social controls, neighborhood trust, general trust, and attachment to place) and social relationships (number of activities; participation in neighborhood activities; participation in recreational activities; and social leverage regarding physical health, mental health, and acquisition of health information). Neighborhood-level social capital was calculated as the percentage of individuals in a neighborhood in the 'high social capital' category. At the individual level, participation in recreational activities, high general trust, and discussion regarding mental health problems with family members were associated with self-rated health positively, whereas discussion of mental health problems with acquaintances had a negative correlation. At the neighborhood level, a highly supportive environment did not contribute to good health, whereas aggregated attachment to place had a positive correlation. There were no significant inter-regional health differences.The results of this study suggest that health promotion activities should aim at promoting the formation of empathetic friendships through individual networks, based on bringing individuals who need support to compatible places. Attachment to place should be incorporated into activities as an important and effective tool. © The Author(s) 2014.

Social capital and health: implication for health promotion by lay citizens in Japan

PubMed Central

Miyamoto, Keiko; Iwakuma, Miho; Nakayama, Takeo

2015-01-01

A non-profit organization was formed in 2009 by lay citizens of Nagahama, Japan in response to a community-based genome-epidemiologic study, the ‘Nagahama Zero(0)-ji Prevention Cohort Project (N0PCP)’. This organization aims to promote health by taking advantage of citizens’ social networks. The Ottawa Charter for Health Promotion affirms the importance of creating supportive environments and coordinating social relationships. Supportive environments (infrastructure) and social relationships (resources) work together as aspects of social capital. This study sought to examine the association between self-rated health and social capital, at both individual and neighborhood levels, and to discuss suitable health promotion strategies for local circumstances. A cross-sectional survey was conducted in 2011, using a self-administered postal questionnaire. Social capital indicators included aspects of support in the environment (social support, neighborhood connectedness, informal social controls, neighborhood trust, general trust, and attachment to place) and social relationships (number of activities; participation in neighborhood activities; participation in recreational activities; and social leverage regarding physical health, mental health, and acquisition of health information). Neighborhood-level social capital was calculated as the percentage of individuals in a neighborhood in the ‘high social capital’ category. At the individual level, participation in recreational activities, high general trust, and discussion regarding mental health problems with family members were associated with self-rated health positively, whereas discussion of mental health problems with acquaintances had a negative correlation. At the neighborhood level, a highly supportive environment did not contribute to good health, whereas aggregated attachment to place had a positive correlation. There were no significant inter-regional health differences. The results of this study suggest that health promotion activities should aim at promoting the formation of empathetic friendships through individual networks, based on bringing individuals who need support to compatible places. Attachment to place should be incorporated into activities as an important and effective tool. PMID:25319376

Can Social Networking Be Used to Promote Engagement in Child Maltreatment Prevention Programs? Two Pilot Studies

PubMed Central

Edwards-Gaura, Anna; Whitaker, Daniel; Self-Brown, Shannon

2014-01-01

Introduction: Child maltreatment is one of the United States' most significant public health problems. In efforts to prevent maltreatment experts recommend use of Behavioral Parent Training Programs (BPTs), which focus on teaching skills that will replace and prevent maltreating behavior. While there is research to support the effectiveness of BPTs in maltreatment prevention, the reach of such programs is still limited by several barriers, including poor retention of families in services. Recently, new technologies have emerged that offer innovative opportunities to improve family engagement. These technologies include smartphones and social networking; however, very little is known about the potential of these to aid in maltreatment prevention. The primary goal of this study was to conduct 2 pilot exploratory projects. Methods: The first project administered a survey to parents and providers to gather data about at-risk parents' use of smartphones and online social networking technologies. The second project tested a social networking-enhanced brief parenting program with 3 intervention participants and evaluated parental responses. Results: Seventy-five percent of parents surveyed reported owning a computer that worked. Eighty-nine percent of parents reported that they had reliable Internet access at home, and 67% said they used the Internet daily. Three parents participated in the intervention with all reporting improvement in parent-child interaction skills and a positive experience participating in the social networking-enhanced SafeCare components. Conclusion: In general, findings suggest that smartphones, social networking, and Facebook, in particular, are now being used by individuals who show risk factors for maltreatment. Further, the majority of parents surveyed in this study said that they like Facebook, and all parents surveyed said that they use Facebook and have a Facebook account. As well, all saw it as a potentially beneficial supplement for future parents enrolling in parenting programs. PMID:25157304

Retweets as a Predictor of Relationships among Users on Social Media.

PubMed

Tsugawa, Sho; Kito, Kosuke

2017-01-01

Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological analyses. While most existing research on link prediction uses only the social network topology for the prediction, in social media, records of user activities such as posting, replying, and reposting are available. These records are expected to reflect user interest, and so incorporating them should improve link prediction. However, research into link prediction using the records of user activities is still in its infancy, and the effectiveness of such records for link prediction has not been fully explored. In this study, we focus in particular on records of reposting as a promising source that could be useful for link prediction, and investigate their effectiveness for link prediction on the popular social media platform Twitter. Our results show that (1) the prediction accuracy of techniques using reposting records is higher than that of popular topology-based techniques such as common neighbors and resource allocation for actively retweeting users, (2) the accuracy of link prediction techniques that use network topology alone can be improved by incorporating reposting records.

Retweets as a Predictor of Relationships among Users on Social Media

PubMed Central

Kito, Kosuke

2017-01-01

Link prediction is the problem of detecting missing links or predicting future link formation in a network. Application of link prediction to social media, such as Twitter and Facebook, is useful both for developing novel services and for sociological analyses. While most existing research on link prediction uses only the social network topology for the prediction, in social media, records of user activities such as posting, replying, and reposting are available. These records are expected to reflect user interest, and so incorporating them should improve link prediction. However, research into link prediction using the records of user activities is still in its infancy, and the effectiveness of such records for link prediction has not been fully explored. In this study, we focus in particular on records of reposting as a promising source that could be useful for link prediction, and investigate their effectiveness for link prediction on the popular social media platform Twitter. Our results show that (1) the prediction accuracy of techniques using reposting records is higher than that of popular topology-based techniques such as common neighbors and resource allocation for actively retweeting users, (2) the accuracy of link prediction techniques that use network topology alone can be improved by incorporating reposting records. PMID:28107489

Investigating Patterns of Participation in an Online Support Group for Problem Drinking: a Social Network Analysis.

PubMed

Urbanoski, Karen; van Mierlo, Trevor; Cunningham, John

2017-10-01

This study contributes to emerging literature on online health networks by modeling communication patterns between members of a moderated online support group for problem drinking. Using social network analysis, we described members' patterns of joint participation in threads, parsing out the role of site moderators, and explored differences in member characteristics by network position. Posts made to the online support group of Alcohol Help Centre during 2013 were structured as a two-mode network of members (n = 205) connected via threads (n = 506). Metrics included degree centrality, clique membership, and tie strength. The network consisted of one component and no cliques of members, although most made few posts and a small number communicated only with the site's moderators. Highly active members were older and tended to have started posting prior to 2013. The distribution of members across threads varied from threads containing posts by one member to others that connected multiple members. Moderators accounted for sizable proportions of the connectivity between both members and threads. After 5 years of operation, the AHC online support group appears to be fairly cohesive and stable, in the sense that there were no isolated subnetworks comprised of specific types of members or devoted to specific topics. Participation and connectedness at the member-level was varied, however, and tended to be low on average. The moderators were among the most central in the network, although there were also members who emerged as central and dedicated contributors to the online discussions across topics. Study findings highlight a number of areas for consideration by online support group developers and managers.

Measuring the Ability to Cope with Serious Illness

DTIC Science & Technology

1983-09-01

effort to negate a problem or situation; avoidance refers to acceptance of the reality of the threat, but there is deliberate effort not to ’think or... hypnosis or self- hypnosis (Kroger, 1977), mental imagery (Simonton, Simonton, and Creighton, 1978), and relaxation exercises (Jaffe, 1980). Escape/Distra...health and coping. Virtually none of the social network/social support measures were associated \\o;ith. any of the ratings, except people I.’ith

Deep mechanisms of social affect - Plastic parental brain mechanisms for sensitivity versus contempt.

PubMed

Swain, James E; Ho, S Shaun

2017-01-01

Insensitive parental thoughts and affect, similar to contempt, may be mapped onto a network of basic emotions moderated by attitudinal representations of social-relational value. Brain mechanisms that reflect emotional valence of baby signals among parents vary according to individual differences and show plasticity over time. Furthermore, mental health problems and treatments for parents may affect these brain systems toward or away from contempt, respectively.

Can Early Intervention Have an Impact on Future Life? A Study of Life Events, Social Interaction, and Child Behavior among Mothers at Psychosocial Risk and Their Children Eight Years after Interaction Treatment

ERIC Educational Resources Information Center

Wadsby, Marie

2012-01-01

Forty-six mothers at psychosocial risk who had undergone interaction treatment when their children were babies were studied with respect to experienced negative life events, social network, and behavior problems in children. One reference group comprising 45 nontreated mothers at psychosocial risk and one comprising 56 mothers without psychosocial…

A novel time series link prediction method: Learning automata approach

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2017-09-01

Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

Under the influence of Facebook? Excess use of social networking sites and drinking motives, consequences, and attitudes in college students

PubMed Central

Hormes, Julia M.

2016-01-01

Background and aims Excessive use of social networking sites (SNS) has recently been conceptualized as a behavioral addiction (i.e., “disordered SNS use”) using key criteria for the diagnosis of substance dependence and shown to be associated with a variety of impairments in psychosocial functioning, including an increased risk of problem drinking. This study sought to characterize associations between “disordered SNS use” and attitudes towards alcohol, drinking motives, and adverse consequences resulting from alcohol use in young adults. Methods Undergraduate students (n = 537, 64.0% female, mean age = 19.63 years, SD = 4.24) reported on their use of SNSs and completed the Alcohol Use Disorders Identification Test, Temptation and Restraint Inventory, Approach and Avoidance of Alcohol and Drinking Motives Questionnaires, and Drinker Inventory of Consequences. Results Respondents meeting previously established criteria for “disordered SNS use” were significantly more likely to use alcohol to cope with negative affect and to conform to perceived social norms, reported significantly more conflicting (i.e., simultaneous positive and negative) attitudes towards alcohol, and had experienced significantly more, and more frequent adverse consequences from drinking in their inter- and intrapersonal, physical, and social functioning, compared to individuals without problems related to SNS use. Discussion and conclusions Findings add to an emerging body of literature suggesting a link between excess or maladaptive SNS use and problems related to alcohol in young adults and point to emotion dysregulation and coping motives as potential shared risk factors for substance and behavioral addictions in this demographic. PMID:28092186

Under the influence of Facebook? Excess use of social networking sites and drinking motives, consequences, and attitudes in college students.

PubMed

Hormes, Julia M

2016-03-01

Background and aims Excessive use of social networking sites (SNS) has recently been conceptualized as a behavioral addiction (i.e., "disordered SNS use") using key criteria for the diagnosis of substance dependence and shown to be associated with a variety of impairments in psychosocial functioning, including an increased risk of problem drinking. This study sought to characterize associations between "disordered SNS use" and attitudes towards alcohol, drinking motives, and adverse consequences resulting from alcohol use in young adults. Methods Undergraduate students (n = 537, 64.0% female, mean age = 19.63 years, SD = 4.24) reported on their use of SNSs and completed the Alcohol Use Disorders Identification Test, Temptation and Restraint Inventory, Approach and Avoidance of Alcohol and Drinking Motives Questionnaires, and Drinker Inventory of Consequences. Results Respondents meeting previously established criteria for "disordered SNS use" were significantly more likely to use alcohol to cope with negative affect and to conform to perceived social norms, reported significantly more conflicting (i.e., simultaneous positive and negative) attitudes towards alcohol, and had experienced significantly more, and more frequent adverse consequences from drinking in their inter- and intrapersonal, physical, and social functioning, compared to individuals without problems related to SNS use. Discussion and conclusions Findings add to an emerging body of literature suggesting a link between excess or maladaptive SNS use and problems related to alcohol in young adults and point to emotion dysregulation and coping motives as potential shared risk factors for substance and behavioral addictions in this demographic.

Measurement issues in research on social support and health.

PubMed Central

Dean, K; Holst, E; Kreiner, S; Schoenborn, C; Wilson, R

1994-01-01

STUDY OBJECTIVE--The aims were: (1) to identify methodological problems that may explain the inconsistencies and contradictions in the research evidence on social support and health, and (2) to validate a frequently used measure of social support in order to determine whether or not it could be used in multivariate analyses of population data in research on social support and health. DESIGN AND METHODS--Secondary analysis of data collected in a cross sectional survey of a multistage cluster sample of the population of the United States, designed to study relationships in behavioural, social support and health variables. Statistical models based on item response theory and graph theory were used to validate the measure of social support to be used in subsequent analyses. PARTICIPANTS--Data on 1755 men and women aged 20 to 64 years were available for the scale validation. RESULTS--Massive evidence of item bias was found for all items of a group membership subscale. The most serious problems were found in relationship to an item measuring membership in work related groups. Using that item in the social network scale in multivariate analyses would distort findings on the statistical effects of education, employment status, and household income. Evidence of item bias was also found for a sociability subscale. When marital status was included to create what is called an intimate contacts subscale, the confounding grew worse. CONCLUSIONS--The composite measure of social network is not valid and would seriously distort the findings of analyses attempting to study relationships between the index and other variables. The findings show that valid measurement is a methodological issue that must be addressed in scientific research on population health. PMID:8189179

Parenting stress and child behaviour problems among parents with intellectual disabilities: the buffering role of resources.

PubMed

Meppelder, M; Hodes, M; Kef, S; Schuengel, C

2015-07-01

Parents with intellectual disabilities (ID) are at risk for high levels of parenting stress. The present study evaluated resources, including parental adaptive functioning, financial resources and access to a support network, as moderators of the association between child behaviour problems and parenting stress. A total of 134 parents with ID and their children (ages 1-7 years) were recruited from 10 Dutch care organisations. Questionnaires were administered to the parents to obtain information on parenting stress in the parent and child domain, financial resources and their support network. Teachers and care workers reported on child behaviour problems and parental adaptive functioning, respectively. Parents experienced more stress with regard to their children than towards their own functioning and situation. Parenting stress was less in parents who were not experiencing financial hardship. Child behaviour problems were associated with high child-related parenting stress, not parent-related parenting stress. Large support networks decreased the association between child behaviour problems and child-related parenting stress. Financial resources did not significantly moderate the association. Parenting stress among parents with ID is focused on problems with the child, especially when little social support is available. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Exploring patients' health information communication practices with social network members as a foundation for consumer health IT design.

PubMed

Valdez, Rupa Sheth; Brennan, Patricia Flatley

2015-05-01

There is a need to ensure that the growing number of consumer health information technologies designed to support patient engagement account for the larger social context in which health is managed. Basic research on how patients engage this larger social context is needed as a precursor to the development of patient-centered consumer health information technology (IT) solutions. The purpose of this study was to inform the broader design of consumer health IT by characterizing patients' existing health information communication practices with their social network members. This qualitative study took place between 2010 and 2012 in a Midwestern city. Eighteen patients with chronic conditions participated in a semi-structured interview that was analyzed using qualitative content analysis and descriptive statistics. Emphasis was placed on recruiting a sample representing diverse cultural groups and including participants of low socioeconomic status. Participants' social networks included a wide range of individuals, spanning biological relatives, divinities, and second-degree relationships. Participants' rationales for health information communication reflected seven themes: (1) characteristics and circumstances of the person, (2) characteristics and circumstances of the relationship, (3) structure and composition of the social network, (4) content of the message, (5) orientation of the goal, (6) dimensions of the context, and (7) adaptive practices. This study demonstrates that patients' health information communication practices are multidimensional, engaging individuals beyond formal and informal caregivers and driven by characteristics of their personal lives and larger social contexts in addition to their health problem. New models of consumer health IT must be created to better align with the realities of patients' communication routines. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Bridging the gap: the roles of social capital and ethnicity in medical student achievement.

PubMed

Vaughan, Suzanne; Sanders, Tom; Crossley, Nick; O'Neill, Paul; Wass, Val

2015-01-01

Within medical education, there is a discrepancy between the achievement level of White students and that of their ethnic minority peers. The processes underlying this disparity have not been adequately investigated or explained. This study utilises social network analysis to investigate the impact of relationships on medical student achievement by ethnicity, specifically by examining homophily (the tendency to interact with others in the same group) by ethnicity, age and role. Data from a cross-sectional social network study conducted in one UK medical school are presented and are analysed alongside examination records obtained from the medical school. Participants were sampled across the four hospital placement sites; a total of 158 medical students in their clinical phase (Years 3 and 4) completed the survey. The research was designed and analysed using social capital theory. Although significant patterns of ethnic and religious homophily emerged, no link was found between these factors and achievement. Interacting with problem-based learning (PBL) group peers in study-related activities, and having seniors in a wider academic support network were directly linked to better achievement. Students in higher academic quartiles were more likely to be named by members of their PBL group in study activities and to name at least one tutor or clinician in their network. Students from lower-achieving groups were least likely to have the social capital enabling, and resulting from, interactions with members of more expert social groups. Lower levels of the social capital that mediates interaction with peers, tutors and clinicians may be the cause of underperformance by ethnic minority students. Because of ethnic homophily, minority students may be cut off from potential and actual resources that facilitate learning and achievement. © 2014 John Wiley & Sons Ltd.

Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks

PubMed Central

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806

Discovering the influential users oriented to viral marketing based on online social networks

NASA Astrophysics Data System (ADS)

Zhu, Zhiguo

2013-08-01

The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users’ combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.

Decomposition-based multiobjective evolutionary algorithm for community detection in dynamic social networks.

PubMed

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.

Antagonistic neural networks underlying differentiated leadership roles.

PubMed

Boyatzis, Richard E; Rochford, Kylie; Jack, Anthony I

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks - the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

SPIR: The potential spreaders involved SIR model for information diffusion in social networks

NASA Astrophysics Data System (ADS)

Rui, Xiaobin; Meng, Fanrong; Wang, Zhixiao; Yuan, Guan; Du, Changjiang

2018-09-01

The Susceptible-Infective-Removed (SIR) model is one of the most widely used models for the information diffusion research in social networks. Many researchers have devoted themselves to improving the classic SIR model in different aspects. However, on the one hand, the equations of these improved models are regarded as continuous functions, while the corresponding simulation experiments use discrete time, leading to the mismatch between numerical solutions got from mathematical method and experimental results obtained by simulating the spreading behaviour of each node. On the other hand, if the equations of these improved models are solved discretely, susceptible nodes will be calculated repeatedly, resulting in a big deviation from the actual value. In order to solve the above problem, this paper proposes a Susceptible-Potential-Infective-Removed (SPIR) model that analyses the diffusion process based on the discrete time according to simulation. Besides, this model also introduces a potential spreader set which solve the problem of repeated calculation effectively. To test the SPIR model, various experiments have been carried out from different angles on both artificial networks and real world networks. The Pearson correlation coefficient between numerical solutions of our SPIR equations and corresponding simulation results is mostly bigger than 0.95, which reveals that the proposed SPIR model is able to depict the information diffusion process with high accuracy.

Antagonistic neural networks underlying differentiated leadership roles

PubMed Central

Boyatzis, Richard E.; Rochford, Kylie; Jack, Anthony I.

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks – the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success. PMID:24624074

Effective Usage of Social Media for Dark Skies Awareness

NASA Astrophysics Data System (ADS)

Hennig, A. J.; Heenatigala, T.; Walker, C. E.

2012-12-01

Social media has become a daily tool in our culture. Networks such as Facebook with 900 million active users and Twitter with 140 million active users make an ideal platform to create awareness. It helps to generate and share new content and enables multi-communication channels. This presentation will address how effectively social media can be used as an education tool to create awareness of light pollution. As a "green" focus becomes more important in our world the topic of light pollution is also rising as an important issue. Light Pollution affects many aspects of our world ranging from flora and fauna to the economic well-being of many industrialized countries. Mixed among the many important pollutants in our world light pollution can fall by the way-side, forgotten, but it is imperative to bring out awareness of this problem, especially since studies are beginning to show how by fighting light pollution we will also be fighting other pollution such as air pollutants. GLOBE at Night has combined social media tools such as Facebook and Twitter with its educational awareness campaign on light pollution to reach out to social media community. Currently our Facebook reaches citizens of twenty separate countries ranging from the Czech Republic and Peru to the United States and the United Kingdom. On Facebook our reach is estimated at over 800,000 friends of our fans. These networks help us to directly answer users' immediate questions and encourage participation in the GLOBE at Night campaigns. Important news on light pollution appearing in cyberspace is monitored regularly using Google Alerts and Twitter hash tags filters which gets posted regularly on our networks. Social media networking has become a tool for users not only for information about GLOBE at Night but also for information about the overall topic of light pollution itself. Many individuals and organizations struggle with the mass content shared in social networks. It is important to know where to look for the right content and what to share with whom. This presentation will highlight on; the importance of engaging in social media to gain and share new content, how to filter the right content, and best uses of social media to create an awareness of light pollution. We will discuss the proper ways to get the most use out of social media networking.

Increasing the appeal and utilization of services for alcohol and drug problems: what consumers and their social networks prefer.

PubMed

Tucker, Jalie A; Foushee, H Russell; Simpson, Cathy A

2009-01-01

A large gap exists in the United States between population need and the utilization of treatment services for substance-related problems. Surveying consumer preferences may provide valuable information for developing more attractive services with greater reach and impact on population health. A state-level telephone survey using random digit dialling sampling methods assessed preferences for available professional, mutual help, and lay resources, as well as innovative computerized and self-help resources that enhance anonymity (N=439 households in Alabama). Respondents preferred help that involved personal contact compared to computerized help or self-help, but were indifferent whether personalized help was dispensed by professional or lay providers. Attractive service features included lower cost, insurance coverage, confidentiality, rapid and convenient appointments, and addressing functional problems and risks of substance misuse. Respondents in households with a member who misused substances rated services more negatively, especially if services had been used. The findings highlight the utility of viewing substance misusers and their social networks as consumers, and the implications for improving the system of care and for designing and marketing services that are responsive to user preferences are discussed.

Analytical Solutions for Rumor Spreading Dynamical Model in a Social Network

NASA Astrophysics Data System (ADS)

Fallahpour, R.; Chakouvari, S.; Askari, H.

2015-03-01

In this paper, Laplace Adomian decomposition method is utilized for evaluating of spreading model of rumor. Firstly, a succinct review is constructed on the subject of using analytical methods such as Adomian decomposion method, Variational iteration method and Homotopy Analysis method for epidemic models and biomathematics. In continue a spreading model of rumor with consideration of forgetting mechanism is assumed and subsequently LADM is exerted for solving of it. By means of the aforementioned method, a general solution is achieved for this problem which can be readily employed for assessing of rumor model without exerting any computer program. In addition, obtained consequences for this problem are discussed for different cases and parameters. Furthermore, it is shown the method is so straightforward and fruitful for analyzing equations which have complicated terms same as rumor model. By employing numerical methods, it is revealed LADM is so powerful and accurate for eliciting solutions of this model. Eventually, it is concluded that this method is so appropriate for this problem and it can provide researchers a very powerful vehicle for scrutinizing rumor models in diverse kinds of social networks such as Facebook, YouTube, Flickr, LinkedIn and Tuitor.

Salience network response to changes in emotional expressions of others is heightened during early adolescence: relevance for social functioning.

PubMed

Rosen, Maya L; Sheridan, Margaret A; Sambrook, Kelly A; Dennison, Meg J; Jenness, Jessica L; Askren, Mary K; Meltzoff, Andrew N; McLaughlin, Katie A

2018-05-01

Adolescence is a unique developmental period when the salience of social and emotional information becomes particularly pronounced. Although this increased sensitivity to social and emotional information has frequently been considered with respect to risk behaviors and psychopathology, evidence suggests that increased adolescent sensitivity to social and emotional cues may confer advantages. For example, greater sensitivity to shifts in the emotions of others is likely to promote flexible and adaptive social behavior. In this study, a sample of 54 children and adolescents (age 8-19 years) performed a delayed match-to-sample task for emotional faces while undergoing fMRI scanning. Recruitment of the anterior cingulate and anterior insula when the emotion of the probe face did not match the emotion held in memory followed a quadratic developmental pattern that peaked during early adolescence. These findings indicate meaningful developmental variation in the neural mechanisms underlying sensitivity to changes in the emotional expressions. Across all participants, greater activation of this network for changes in emotional expression was associated with less social anxiety and fewer social problems. These results suggest that the heightened salience of social and emotional information during adolescence may confer important advantages for social behavior, providing sensitivity to others' emotions that facilitates flexible social responding. © 2017 John Wiley & Sons Ltd.

Illuminating the dark matter of social neuroscience: Considering the problem of social interaction from philosophical, psychological, and neuroscientific perspectives

PubMed Central

Przyrembel, Marisa; Smallwood, Jonathan; Pauen, Michael; Singer, Tania

2012-01-01

Successful human social interaction depends on our capacity to understand other people's mental states and to anticipate how they will react to our actions. Despite its importance to the human condition, the exact mechanisms underlying our ability to understand another's actions, feelings, and thoughts are still a matter of conjecture. Here, we consider this problem from philosophical, psychological, and neuroscientific perspectives. In a critical review, we demonstrate that attempts to draw parallels across these complementary disciplines is premature: The second-person perspective does not map directly to Interaction or Simulation theories, online social cognition, or shared neural network accounts underlying action observation or empathy. Nor does the third-person perspective map onto Theory-Theory (TT), offline social cognition, or the neural networks that support Theory of Mind (ToM). Moreover, we argue that important qualities of social interaction emerge through the reciprocal interplay of two independent agents whose unpredictable behavior requires that models of their partner's internal state be continually updated. This analysis draws attention to the need for paradigms in social neuroscience that allow two individuals to interact in a spontaneous and natural manner and to adapt their behavior and cognitions in a response contingent fashion due to the inherent unpredictability in another person's behavior. Even if such paradigms were implemented, it is possible that the specific neural correlates supporting such reciprocal interaction would not reflect computation unique to social interaction but rather the use of basic cognitive and emotional processes combined in a unique manner. Finally, we argue that given the crucial role of social interaction in human evolution, ontogeny, and every-day social life, a more theoretically and methodologically nuanced approach to the study of real social interaction will nevertheless help the field of social cognition to evolve. PMID:22737120

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions

PubMed Central

da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Monteiro, Maurílio de Abreu; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

2016-01-01

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants’ municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar characteristics, presented high probability of certification, associated with the highest degree in social networking platform. PMID:26727472

Determinants of Quality of Life in Ageing Populations: Results from a Cross-Sectional Study in Finland, Poland and Spain.

PubMed

Raggi, Alberto; Corso, Barbara; Minicuci, Nadia; Quintas, Rui; Sattin, Davide; De Torres, Laura; Chatterji, Somnath; Frisoni, Giovanni Battista; Haro, Josep Maria; Koskinen, Seppo; Martinuzzi, Andrea; Miret, Marta; Tobiasz-Adamczyk, Beata; Leonardi, Matilde

2016-01-01

To comprehensively identify the determinants of quality of life (QoL) in a population study sample of persons aged 18-50 and 50+. In this observational, cross-sectional study, QoL was measured with the WHOQOL-AGE, a brief instrument designed to measure QoL in older adults. Eight hierarchical regression models were performed to identify determinants of QoL. Variables were entered in the following order: Sociodemographic; Health Habits; Chronic Conditions; Health State description; Vision and Hearing; Social Networks; Built Environment. In the final model, significant variables were retained. The final model was re-run using data from the three countries separately. Complete data were available for 5639 participants, mean age 46.3 (SD 18.4). The final model accounted for 45% of QoL variation and the most relevant contribution was given by sociodemographic data (particularly age, education level and living in Finland: 17.9% explained QoL variation), chronic conditions (particularly depression: 4.6%) and a wide and rich social network (4.6%). Other determinants were presence of disabling pain, learning difficulties and visual problems, and living in usable house that is perceived as non-risky. Some variables were specifically associated to QoL in single countries: age in Poland, alcohol consumption in Spain, angina in Finland, depression in Spain, and self-reported sadness both in Finland and Poland, but not in Spain. Other were commonly associated to QoL: smoking status, bodily aches, being emotionally affected by health problems, good social network and home characteristics. Our results highlight the importance of modifiable determinants of QoL, and provide public health indications that could support concrete actions at country level. In particular, smoking cessation, increasing the level of physical activity, improving social network ties and applying universal design approach to houses and environmental infrastructures could potentially increase QoL of ageing population.

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions.

PubMed

da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Monteiro, Maurílio de Abreu; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

2016-01-01

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants' municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar characteristics, presented high probability of certification, associated with the highest degree in social networking platform.

Mental Health and Head Start: Teaching Adaptive Skills.

ERIC Educational Resources Information Center

Forness, Steven R.; Serna, Loretta A.; Kavale, Kenneth A.; Nielsen, Elizabeth

1998-01-01

Describes the use of a self-determination curriculum for mental-health intervention and primary prevention for Head Start children. The curriculum addresses critical adaptive-skills domains, including social skills, self-evaluation, self-direction, networking or friendship, collaboration or support seeking, problem solving and decision making, and…

Cyber "Pokes": Motivational Antidote for Developmental College Readers

ERIC Educational Resources Information Center

Bowers-Campbell, Joy

2008-01-01

Difficulties characterizing developmental college students are reviewed within the context of motivational theories of learning. The author highlights problems of low self-efficacy and inadequate self-regulated learning for developmental college students. The author argues that the use of Facebook, a widely-used social networking technology, may…

Assessment of Childhood Disorders. Third Edition.

ERIC Educational Resources Information Center

Mash, Eric J., Ed.; Terdal, Leif G., Ed.

This book describes methods and strategies for assessing a comprehensive array of childhood disorders, child health risks, and adolescent problems. It highlights the ongoing interplay among behaviors, cognition, and affects as they unfold within the young person's social network. Each chapter presents a conceptual framework for understanding the…

Test and Evaluation of Architecture-Aware Compiler Environment

DTIC Science & Technology

2011-11-01

biology, medicine, social sciences , and security applications. Challenges include extremely large graphs (the Facebook friend network has over...Operations with Temporal Binning ....................................................................... 32 4.12 Memory behavior and Energy per...five challenge problems empirically, exploring their scaling properties, computation and datatype needs, memory behavior , and temporal behavior

Improving Performance and Predictability of Storage Arrays

ERIC Educational Resources Information Center

Altiparmak, Nihat

2013-01-01

Massive amount of data is generated everyday through sensors, Internet transactions, social networks, video, and all other digital sources available. Many organizations store this data to enable breakthrough discoveries and innovation in science, engineering, medicine, and commerce. Such massive scale of data poses new research problems called big…

College Students' Drinking and Posting About Alcohol: Forwarding a Model of Motivations, Behaviors, and Consequences.

PubMed

Thompson, Charee M; Romo, Lynsey K

2016-06-01

College drinking continues to remain a public health problem that has been exacerbated by alcohol-related posts on social networking sites (SNSs). Although existing research has linked alcohol consumption, alcohol posts, and adverse consequences to one another, comprehensive explanations for these associations have been largely unexplored. Thus, we reasoned that students' personal motivations (i.e., espousing an alcohol identity, needing entertainment, and adhering to social norms) influence their behaviors (i.e., alcohol consumption and alcohol-related posting on SNSs), which can lead to alcohol problems. Using structural equation modeling, we analyzed data from 364 undergraduate students and found general support for our model. In particular, espousing an alcohol identity predicted alcohol consumption and alcohol-related SNS posting, needing entertainment predicted alcohol consumption but not alcohol-related SNS posting, and adhering to social norms predicted alcohol-related SNS posting but not alcohol consumption. In turn, alcohol consumption and alcohol-related SNS posting predicted alcohol problems. It is surprising that alcohol-related SNS posting was a stronger predictor of alcohol problems than alcohol consumption. We discuss the findings within their applied applications for college student health.

Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.

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

PubMed

Rangachari, Pavani

2016-06-01

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

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Substance Use, Distress, and Adolescent School Networks

PubMed Central

McLeod, Jane D.; Uemura, Ryotaro

2012-01-01

This study examined the associations of substance use, psychological distress, and mental health services receipt with the structure and content of adolescent school-based networks. Using data from the National Longitudinal Study of Adolescent Health, we found that substance use was associated with receiving more, but making fewer, peer nominations. It also was associated with less favorable network characteristics, such as low GPA. Services receipt was associated with receiving and making fewer nominations, less favorable network characteristics, and a lower likelihood of reciprocated best friendships. Psychological distress had fewer significant associations. All associations were modest in magnitude. Our results suggest the importance of considering multiple indicators of socioemotional problems and multiple dimensions of social networks in research on adolescent peer relations. PMID:23066337

Rewiring the network. What helps an innovation to diffuse?

NASA Astrophysics Data System (ADS)

Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał; Weron, Tomasz

2014-03-01

A fundamental question related to innovation diffusion is how the structure of the social network influences the process. Empirical evidence regarding real-world networks of influence is very limited. On the other hand, agent-based modeling literature reports different, and at times seemingly contradictory, results. In this paper we study innovation diffusion processes for a range of Watts-Strogatz networks in an attempt to shed more light on this problem. Using the so-called Sznajd model as the backbone of opinion dynamics, we find that the published results are in fact consistent and allow us to predict the role of network topology in various situations. In particular, the diffusion of innovation is easier on more regular graphs, i.e. with a higher clustering coefficient. Moreover, in the case of uncertainty—which is particularly high for innovations connected to public health programs or ecological campaigns—a more clustered network will help the diffusion. On the other hand, when social influence is less important (i.e. in the case of perfect information), a shorter path will help the innovation to spread in the society and—as a result—the diffusion will be easiest on a random graph.

Family and Friendship Networks and Obsessive-Compulsive Disorder Among African Americans and Black Caribbeans.

PubMed

Himle, Joseph A; Taylor, Robert Joseph; Nguyen, Ann W; Williams, Monnica T; Lincoln, Karen D; Taylor, Harry Owen; Chatters, Linda M

2017-03-01

Although there is a large literature on the influence of social support on mental health there is limited research on social support and OCD. This is especially the case for African Americans and Black Caribbeans. This study examines the relationship between family and friendship networks and the prevalence of OCD. The analysis is based on the National Survey of American Life a nationally representative sample of African Americans and Black Caribbeans. Variables included frequency of contact with family and friends, subjective closeness with family and friends, and negative interactions (conflict, criticisms) with family members. The results indicated that only negative interaction with family members was significantly associated with OCD prevalence. African Americans and Black Caribbeans with more frequent negative interactions with family members had a higher likelihood of having OCD. Subjective closeness and frequency of contact with family and friends was not protective of OCD. Overall the findings are consistent with previous work which finds that social support is an inconsistent protective factor of psychiatric disorders, but negative interactions with support network members is more consistently associated with mental health problems.

Family and Friendship Networks and Obsessive-Compulsive Disorder Among African Americans and Black Caribbeans

PubMed Central

Himle, Joseph A.; Taylor, Robert Joseph; Nguyen, Ann W.; Williams, Monnica T.; Lincoln, Karen D.; Taylor, Harry Owen; Chatters, Linda M.

2017-01-01

Although there is a large literature on the influence of social support on mental health there is limited research on social support and OCD. This is especially the case for African Americans and Black Caribbeans. This study examines the relationship between family and friendship networks and the prevalence of OCD. The analysis is based on the National Survey of American Life a nationally representative sample of African Americans and Black Caribbeans. Variables included frequency of contact with family and friends, subjective closeness with family and friends, and negative interactions (conflict, criticisms) with family members. The results indicated that only negative interaction with family members was significantly associated with OCD prevalence. African Americans and Black Caribbeans with more frequent negative interactions with family members had a higher likelihood of having OCD. Subjective closeness and frequency of contact with family and friends was not protective of OCD. Overall the findings are consistent with previous work which finds that social support is an inconsistent protective factor of psychiatric disorders, but negative interactions with support network members is more consistently associated with mental health problems. PMID:28321149

The relationship between optimal parenting, Internet addiction and motives for social networking in adolescence.

PubMed

Floros, Georgios; Siomos, Konstantinos

2013-10-30

This paper presents a cross-sectional study of a large, high-school Greek student sample (N=1971) with the aim to examine adolescent motives for participating in social networking (SN) for a possible link with parenting style and cognitions related to Internet addiction disorder (IAD). Exploratory statistics demonstrate a shift from the prominence of online gaming to social networking for this age group. A regression model provides with the best linear combination of independent variables useful in predicting participation in SN. Results also include a validated model of negative correlation between optimal parenting on the one hand and motives for SN participation and IAD on the other. Examining cognitions linked to SN may assist in a better understanding of underlying adolescent wishes and problems. Future research may focus in the patterns unveiled among those adolescents turning to SN for the gratification of basic unmet psychological needs. The debate on the exact nature of IAD would benefit from the inclusion of SN as a possible online activity where addictive phenomena may occur. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Spreading dynamics in complex networks

NASA Astrophysics Data System (ADS)

Pei, Sen; Makse, Hernán A.

2013-12-01

Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.

A survey of body sensor networks.

PubMed

Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi

2013-04-24

The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives.

A Survey of Body Sensor Networks

PubMed Central

Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi

2013-01-01

The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives. PMID:23615581

Fostering interpersonal trust on social media: physicians' perspectives and experiences.

PubMed

Panahi, Sirous; Watson, Jason; Partridge, Helen

2016-02-01

The problem of developing and sustaining mutual trust is one of the main barriers to knowledge sharing on social media platforms such as blogs, wikis, micro-blogs and social networking websites. While many studies argue that mutual trust is necessary for online communication and knowledge sharing, few have actually explored and demonstrated how physicians can establish and sustain trusted relationships on social media. To identify approaches through which physicians establish interpersonal trust on social media. Twenty-four physicians, who were active users of social media, were interviewed using a semi-structured approach between 2013 and 2014. Snowball sampling was employed for participant recruitment. The data were analysed using a thematic analysis approach. Physicians trust their peers on social media in a slightly different way than in face-to-face communication. The study found that the majority of participants established trust on social media mainly through previous personal interaction, authenticity and relevancy of voice, professional standing, consistency of communication, peer recommendation, and non-anonymous and moderated sites. Healthcare professionals need to approach social media carefully when using it for knowledge sharing, networking and developing trusted relations with like-minded peers. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Pollution source localization in an urban water supply network based on dynamic water demand.

PubMed

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

A Sophisticated Architecture Is Indeed Necessary for the Implementation of Health in All Policies but not Enough

PubMed Central

Breton, Eric

2016-01-01

In this commentary, I argue that beyond a sophisticated supportive architecture to facilitate implementation of actions on the social determinants of health (SDOH) and health inequities, the Health in All Policies (HiAP) project faces two main barriers: lack of awareness within policy networks on the social determinants of population health, and a tendency of health actors to neglect investing in other sectors’ complex problems. PMID:27285517

Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members.

PubMed

Pollet, Thomas V; Roberts, Sam G B; Dunbar, Robin I M

2011-04-01

The effect of Internet use on social relationships is still a matter of intense debate. This study examined the relationships between use of social media (instant messaging and social network sites), network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using social media was associated with a larger number of online social network "friends." However, time spent using social media was not associated with larger offline networks, or feeling emotionally closer to offline network members. Further, those that used social media, as compared to non-users of social media, did not have larger offline networks, and were not emotionally closer to offline network members. These results highlight the importance of considering potential time and cognitive constraints on offline social networks when examining the impact of social media use on social relationships.

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Discovering Network Structure Beyond Communities

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2011-11-01

To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest.

Personalized Recommendations Based on Users' Information-Centered Social Networks

ERIC Educational Resources Information Center

Lee, Danielle

2013-01-01

The overwhelming amount of information available today makes it difficult for users to find useful information and as the solution to this information glut problem, recommendation technologies emerged. Among the several streams of related research, one important evolution in technology is to generate recommendations based on users' own social…

Indirect Aggression, Bullying and Female Teen Victimization: A Literature Review

ERIC Educational Resources Information Center

Catanzaro, Mary F.

2011-01-01

This article assesses the literature in relation to youth bullying in the United Kingdom, Scandinavia and North America, focusing in particular on female aggression as it is expressed in adolescent peer relationships. It addresses the escalating problems of indirect aggression, especially those involving social networking interchanges such as…

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

PubMed

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

2013-06-01

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

Dynamical networks of influence in small group discussions

PubMed Central

Noriega Campero, Alejandro; Almaatouq, Abdullah

2018-01-01

In many domains of life, business and management, numerous problems are addressed by small groups of individuals engaged in face-to-face discussions. While research in social psychology has a long history of studying the determinants of small group performances, the internal dynamics that govern a group discussion are not yet well understood. Here, we rely on computational methods based on network analyses and opinion dynamics to describe how individuals influence each other during a group discussion. We consider the situation in which a small group of three individuals engages in a discussion to solve an estimation task. We propose a model describing how group members gradually influence each other and revise their judgments over the course of the discussion. The main component of the model is an influence network—a weighted, directed graph that determines the extent to which individuals influence each other during the discussion. In simulations, we first study the optimal structure of the influence network that yields the best group performances. Then, we implement a social learning process by which individuals adapt to the past performance of their peers, thereby affecting the structure of the influence network in the long run. We explore the mechanisms underlying the emergence of efficient or maladaptive networks and show that the influence network can converge towards the optimal one, but only when individuals exhibit a social discounting bias by downgrading the relative performances of their peers. Finally, we find a late-speaker effect, whereby individuals who speak later in the discussion are perceived more positively in the long run and are thus more influential. The numerous predictions of the model can serve as a basis for future experiments, and this work opens research on small group discussion to computational social sciences. PMID:29338013

Extended mind and after: socially extended mind and actor-network.

PubMed

Kono, Tetsuya

2014-03-01

The concept of extended mind has been impressively developed over the last 10 years by many philosophers and cognitive scientists. The extended mind thesis (EM) affirms that the mind is not simply ensconced inside the head, but extends to the whole system of brain-body-environment. Recently, some philosophers and psychologists try to adapt the idea of EM to the domain of social cognition research. Mind is socially extended (SEM). However, EM/SEM theory has problems to analyze the interactions among a subject and its surroundings with opposition, antagonism, or conflict; it also tends to think that the environment surrounding the subject is passive or static, and to neglect the power of non-human actants to direct and regulate the human subject. In these points, actor-network theory (ANT) proposed by Latour and Callon is more persuasive, while sharing some important ideas with EM/SEM theory. Actor-network is a hybrid community which is composed of a series of heterogeneous elements, animate and inanimate for a certain period of time. I shall conclude that EM/SEM could be best analyzed as a special case of actor-network. EM/SEM is a system which can be controlled by a human agent alone. In order to understand collective behavior, philosophy and psychology have to study the actor-network in which human individuals are situated.

Pro-socially shareable entertainment television programmes: a programming alternative in developing countries?

PubMed

Singhal, A; Svenkerud, P J

1994-12-01

Over the period 1975-82, the Mexican television network created and aired seven entertainment soap operas promoting educational-development themes like adult literacy, smaller family size norms, and an higher social status for women. These emissions earned high ratings in Mexico and in other Latin American countries where they were subsequently broadcast. Evidence suggests that many of the social objectives of the soaps were met. In light of such success, the authors investigated the potential of pro-socially shareable entertainment television programs in developing countries. These programs use entertaining media formats to carry pro-social messages to a wide, yet culturally-proximate audience group. Entertainment television genres such as melodramatic soap operas offer certain advantages for carrying pro-socially shareable messages to audiences. The possibility of using other television genres and media channels, however, also needs to be seriously considered. Pro-socially shareable entertainment programs do have their limitations and problems, with a certain degree of message dilution invariably accompanying the quest for shareability. Targeting specific problems in specific audience groups is difficult and the identity of a relatively small homogeneous group can be threatened in a larger culturally proximate group. The value-laden nature of pro-social content can also be problematic.

How Does Difficulty Communicating Affect the Social Relationships of Older Adults? An Exploration Using Data from a National Survey

PubMed Central

Palmer, Andrew D.; Newsom, Jason T.; Rook, Karen S.

2016-01-01

Healthy social relationships are important for maintaining mental and physical health in later life. Less social support, smaller social networks, and more negative social interactions have been linked to depression, poorer immune functioning, lower self-rated health, increased incidence of disease, and higher mortality. Overwhelming evidence suggests that communication disorders adversely affect social relationships. Much less is known about whether some or all aspects of social relationships are negatively affected by a communication disorder. The relative impact of a communication disorder on social relationships, as compared to other kinds of disability, is also poorly understood. Data were analyzed from a representative national sample of community-dwelling adults aged 65 and older living in the continental United States (n = 742). Results from multiple regressions indicated that difficulty communicating was significantly associated with several parameters of social relationships even after controlling for age, gender, partnership status, health, functional limitations, and visual impairment. Communication difficulty was a significant predictor of smaller social network size, fewer positive social exchanges, less frequent participation in social activities, and higher levels of loneliness, but was not a significant predictor of negative social exchanges. These findings suggest that communication disorders may place older adults at increased risk for mental and physical health problems because of social isolation, reduced social participation, and higher rates of loneliness. In addition, it appears that communication disorders may have a greater impact on positive, rather than negative, aspects of social relationships. PMID:27420152