HEXACO personality factors and their associations with Facebook use and Facebook network characteristics

2018 ◽  
Author(s):  
Riana Brown ◽  
Sam G. B. Roberts ◽  
Thomas V. Pollet
Keyword(s):  
Social Networks ◽  
Network Size ◽  
Openness To Experience ◽  
Personality Factors ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Online Networks ◽  
Facebook Use ◽  
Objectively Measured ◽  
Size And Structure

Personality factors affect the properties of ‘offline’ social networks, but how they are associated with the structural properties of online networks is still unclear. We investigated how the six HEXACO personality factors (Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness and Openness to Experience) relate to Facebook use and three objectively measured Facebook network characteristics - network size, density, and number of clusters. Participants (n = 107, mean age = 20.6, 66% female) extracted their Facebook networks using the GetNet app, completed the 60-item HEXACO questionnaire and the Facebook Usage Questionnaire. Users high in Openness to Experience spent less time on Facebook. Extraversion was positively associated with network size and the number of network clusters (but not after controlling for size). These findings suggest that personality factors are associated with Facebook use and the size and structure of Facebook networks, and that personality is an important influence on both online and offline sociality.

scholarly journals The Social Networks and Social Support of Siblings of Children with Cancer

Children ◽  
2022 ◽  
Vol 9 (1) ◽  
pp. 113
Author(s):  
Sarah E. Wawrzynski ◽  
Melissa A. Alderfer ◽  
Whitney Kvistad ◽  
Lauri Linder ◽  
Maija Reblin ◽  
...  
Keyword(s):  
Social Networks ◽  
Network Size ◽  
Support Networks ◽  
Support Network ◽  
Structured Interviews ◽  
Children With Cancer ◽  
Network Characteristics ◽  
The Social ◽  
Need Support ◽  
Sources Of Support

Siblings of children with cancer need support to ameliorate the challenges they encounter; however, little is known about what types and sources of support exist for siblings. This study addresses this gap in our understanding of the social networks and sources of support for adolescents with a brother or sister who has cancer. Additionally, we describe how the support siblings receive addresses what they feel are the hardest aspects of being a sibling of a child with cancer. During semi-structured interviews, siblings (ages 12–17) constructed ecomaps describing their support networks. Data were coded for support type (emotional, instrumental, informational, validation, companionship) and support provider (e.g., mother, teacher, friend). Network characteristics and patterns of support were explored. Support network size ranged from 3 to 10 individuals (M = 6 ± 1.9); siblings most frequently reported mothers as sources of support (n = 22, 91.7%), followed by fathers (n = 19, 79.2%), close friends (n = 19, 79.2%) and siblings (with or without cancer) (n = 17, 70.8%). Friends and brothers or sisters most often provided validation and companionship while instrumental and informational supports came from parents. This study provides foundational knowledge about siblings’ support networks, which can be utilized to design interventions that improve support for siblings of children with cancer.

Who Belongs to Me? Social Relationship and Personality Characteristics in the Transition to Young Adulthood

2014 ◽  
Vol 28 (6) ◽  
pp. 586-603 ◽  
Author(s):  
Jenny Wagner ◽  
Oliver Lüdtke ◽  
Brent W. Roberts ◽  
Ulrich Trautwein
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Young Adulthood ◽  
Social Relationship ◽  
Multilevel Models ◽  
Network Size ◽  
Big Five Personality ◽  
Personality Psychology ◽  
Emotional Closeness ◽  
Network Characteristics

Not much is known about how social network characteristics change in the transition out of school and what role Big Five personality plays in this context. The aim of this paper was twofold. First, we explored changes in social network and relationship characteristics across the transition out of secondary school. Second, we examined within–person and between–person effects of personality on these social network changes. Results based on a series of multilevel models to a longitudinal sample of 2287 young adults revealed four main findings. First, social networks increased in size, and this increase was mainly due to a larger number of nonkin. Stable social networks during the transition consisted mainly of family ties but were generally characterized by high closeness. Second, extraversion and openness consistently predicted network size, whereas agreeableness predicted network overlap. Third, increases in emotional closeness were found only for kin; closeness was generally lower for unstable relationships. Fourth, changes in emotional closeness were related to personality, particularly neuroticism, agreeableness, and conscientiousness for stable relationships; for unstable relationships, however, closeness was related to extraversion and openness. The article concludes by discussing the role of personality for social relationship development and the active moulding of social networks in young adulthood. Copyright © 2014 European Association of Personality Psychology

Network characteristics matter in politics on Facebook: evidence from a US national survey

2018 ◽  
Vol 42 (3) ◽  
pp. 372-386 ◽  
Author(s):  
Yanqin Lu ◽  
Jae Kook Lee ◽  
Eunyi Kim
Keyword(s):  
Political Participation ◽  
Positive Association ◽  
Network Size ◽  
Strong Ties ◽  
Content Type ◽  
Network Heterogeneity ◽  
Network Characteristics ◽  
Online Panel ◽  
Facebook Use ◽  
The Relationship

PurposeFacebook has been identified as a primary source of political information by a majority (63 percent) of its users. The purpose of this paper is to examine the relationship between Facebook use and political participation, and investigate the mediating effects of the characteristics of one’s Facebook network (i.e. network size, proportion of strong ties, and discussion network heterogeneity).Design/methodology/approachThis study relies on a representative survey of American adults (n=1,032) conducted during the 2012 primary election campaigns from May 3 to May 10. The sample was randomly selected from a representative online panel maintained by a professional research organization. Given this study’s focus on the influence of Facebook use and network characteristics, an online panel is suitable for testing the hypotheses.FindingsThe results show positive associations between Facebook use and both off- and online political participation. Further, the positive association between Facebook use and political participation is mediated by discussion network heterogeneity and the proportion of strong ties in one’s Facebook network, but not the network size.Originality/valueThis study sheds light on the roles played by network characteristics of Facebook. The composition of a user’s Facebook network is closely related with what kind of information she encounters and how likely she is to participate in politics. Hence, network characteristics (e.g. Facebook discussion network heterogeneity) arise as important for gaining a nuanced understanding of the relationship between general use of the medium and its political outcomes.

Association between social network characteristics and depressive symptoms in South Korean adults: The moderating roles of age diversity and age difference

2020 ◽  
Author(s):  
Ye Jin Jeon ◽  
Sun Wook Jung ◽  
Ji Eun Heo ◽  
Yoosik Youm ◽  
Hyeon Chang Kim ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Depressive Symptoms ◽  
Network Size ◽  
Community Dwelling ◽  
Age Difference ◽  
Inverse Association ◽  
Network Characteristics ◽  
South Korean ◽  
Age Diversity

Abstract Background: This study aimed to examine the association between size and intimacy of social networks and substantial depressive symptoms, and further, to assess the moderating roles of age diversity and age difference in these linkages, in the community-dwelling adult population in South Korea.Methods: A South Korean population of 2,363 in the Cardiovascular and Metabolic Disease Etiology Research Center cohort was utilized. Each participant’s social network characteristics were measured using the egocentric social network analysis tool. Substantial depressive symptoms were assessed using the Beck Depression Inventory-II (BDI-II). Multivariable logistic regression was used to compute odds ratios (ORs) for substantial depressive symptoms by different social network characteristics.Results: Mean perceived intimacy of social networks had an inverse association with substantial depressive symptoms; Overall, the size of social networks had a negative association with depressive symptoms. In women, age diversity and age difference had moderation effects on the association of network size and intimacy with substantial depressive symptoms. The association of network size and intimacy with substantial depressive symptoms was stronger than women’s average (OR=3.23; 95% CI=1.91-5.47) when social networks had a higher age diversity (OR=4.95; 2.32-10.51) and higher age differences (OR=5.38; 2.22-13.05).Limitations: Substantial Depressive symptoms were measured according to self-assessed levels of depressive symptoms during the previous two weeks, which do not necessarily indicate depressive disorder. Categorization of certain variables was made considering the distribution, but not with the actual critical known cut-off.Conclusions: We found that low social network size and intimacy were linearly associated with substantial depressive symptoms in women. Women whose networks are small-sized, less intimate, and with high age diversity and age difference, especially with older persons are more likely to have depressive symptoms in South Korean settings.Trial registration: KCT0001038, Clinical Research Information Service (CRIS)

scholarly journals Social networks in coworking spaces and individual coworker’s creativity

2021 ◽  
Author(s):  
Alexandra Rese ◽  
Lars Görmar ◽  
Alena Herbig
Keyword(s):  
Social Networks ◽  
Network Size ◽  
Vital Role ◽  
Value Orientations ◽  
Central Position ◽  
Network Characteristics ◽  
Managerial Implications ◽  
Coworking Spaces ◽  
The Individual ◽  
Favorable Conditions

AbstractCoworking spaces (CWS) are open creative labs that provide a community-like environment and the necessary surroundings for their users to build and maintain networks with different actors inside and outside the CWS. With a wide variety of knowledge and skills available in trusted surroundings as well as similar value orientations, coworkers enjoy favorable conditions to establish their network-style. However, research has not investigated the benefit of coworkers’ social networks as far as their individual creativity is concerned so far. This paper takes several network characteristics into account: structure in terms of network size and centrality in the CWS, but also trusted and reciprocal relationships, supportiveness, diversity of knowledge exchanged, and the individual openness to core coworking values. Based on the literature on social networks and small group research, we developed a research model. We tested it to get deeper insights into the phenomenon by relying on 113 coworkers in 33 private German coworking spaces. The results show that a central position in the CWS allowing for direct exchange and high individual openness to core coworking values positively affects social involvement and the diversity of knowledge exchanged, and finally, a coworker’s individual creativity. Managerial implications include the vital role of a central position in the CWS for creativity and a somewhat balanced composition of coworkers working alone or in a team.

Fast detection of the fuzzy communities based on leader-driven algorithm

2018 ◽  
Vol 32 (06) ◽  
pp. 1850058
Author(s):  
Changjian Fang ◽  
Dejun Mu ◽  
Zhenghong Deng ◽  
Jun Hu ◽  
Chen-He Yi
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Learning Community ◽  
Network Structure ◽  
Fast Algorithm ◽  
Network Size ◽  
Local Minima ◽  
Large Networks ◽  
Number Of Clusters ◽  
Fast Detection

In this paper, we present the leader-driven algorithm (LDA) for learning community structure in networks. The algorithm allows one to find overlapping clusters in a network, an important aspect of real networks, especially social networks. The algorithm requires no input parameters and learns the number of clusters naturally from the network. It accomplishes this using leadership centrality in a clever manner. It identifies local minima of leadership centrality as followers which belong only to one cluster, and the remaining nodes are leaders which connect clusters. In this way, the number of clusters can be learned using only the network structure. The LDA is also an extremely fast algorithm, having runtime linear in the network size. Thus, this algorithm can be used to efficiently cluster extremely large networks.

scholarly journals Associations of Quality, Quantity, and Structural Characteristics of Individual Social Network on Depressive Symptoms

2020 ◽  
Author(s):  
Ji Eun Heo ◽  
Sun Wook Jung ◽  
Yoosik Youm ◽  
Hyeon Chang Kim ◽  
Sun Jae Jung
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Depressive Symptoms ◽  
Network Size ◽  
Age Difference ◽  
Analysis Tool ◽  
Disease Etiology ◽  
Network Characteristics ◽  
Age Diversity ◽  
High Age

Abstract Background This study explores the association between the size and intimacy of an individual’s social network with depressive symptoms, considering age diversity and age difference in the general adult population in South Korea. Methods We utilized data from a population of 2,363 in the Cardiovascular and Metabolic Disease Etiology Research Center cohort. Each participant’s social network properties and social support status were measured using the egocentric social network analysis tool. Depressive symptoms were assessed using the Beck Depression Inventory-II. Multivariable logistic regression was used to compute odds ratios (ORs) for depression by different social network characteristics. Results Overall, network size and mean intimacy were both associated with depressive symptoms; however, the combination of the two showed different association patterns with depressive symptoms by gender. Compared to those with both a larger network size and higher average intimacy in the network, only women showed significantly increased ORs for depression with decreases in either the size or the intimacy of the network. This tendency was prominent in women whose social networks had high age diversity or members mainly older than themselves. Limitations Depressive symptoms were measured according to self-assessed levels of depressive symptoms during the previous two weeks, which do not necessarily indicate depressive disorder. Conclusion The social network characteristics of size and intimacy associated differently with depressive symptoms by gender. In women whose social networks had high age diversity, smaller-sized and less intimate networks increased the likelihood of depression.

scholarly journals Social Network Characteristics and Smoking Index Among Smoking Cessation Outpatients in Kunming’s Grade-A Tertiary Hospitals in China: A Cross-Sectional Observational Study

2021 ◽  
Author(s):  
Rui Zeng ◽  
Li Ai ◽  
Yang Yuan ◽  
Yu Cao ◽  
Ke-Li Chen ◽  
...  
Keyword(s):  
Social Networks ◽  
Smoking Cessation ◽  
Social Network ◽  
Network Size ◽  
Network Member ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Network Characteristics ◽  
Tertiary Hospitals ◽  
Smoking Index

Abstract IntroductionThe success rate of smoking cessation outpatients remains modest. Previous studies have highlighted the importance of social networks for quitting smoking, yet there is a substantial lack of studies examining participants in outpatient smoking cessation programs, especially regarding their smoking index.AimWe aimed to identify the associations between the social network characteristics of smoking cessation outpatients and their smoking indexes. The association was analyzed with participants in Grade-A Tertiary Hospitals in Kunming, the capital of Yunnan province in China.MethodsA multicenter cross-sectional survey was conducted in Kunming in six randomly sampled Grade-A tertiary hospitals. Participants included 351 smoking cessation outpatients who provided data on cigarette smoking and social networks. Multivariate logistic regression was used to examine the association between social network characteristics and smoking index across outpatients. Strong associations were identified using adjusted odds ratios and a 95% confidence interval.ResultsLarge network size (AOR=1.79, 95%CI=0.99, 3.86), having children (AOR = 6.35, 95%CI = 2.26, 19.86), and at least one highly influential person in the network (AOR = 2.74, 95% CI =1.13, 7.01)were all associated with the risk of a high smoking index. However, having drinking friends (AOR = 0.28, 95% CI = 0.14, 0.56), non-smoking and non-drinking friends in the network (AOR = 0.44, 95% CI = 0.21, 0.88), and a network member who provided health advice (AOR = 0.41, 95% CI = 0.11, 1.35) were associated with a lower risk of a high smoking index.The results were sustained even after adjusting for demographic details.ConclusionsThe study findings suggest the importance of social network characteristics for smoking cessation physicians when formulating a personalized smoking cessation plan for outpatients.

Personal networks and mortality in later life: racial and ethnic differences

2020 ◽  
Author(s):  
Adam R Roth
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Race And Ethnicity ◽  
Social Life ◽  
Later Life ◽  
Network Size ◽  
Racial And Ethnic Differences ◽  
Network Characteristics ◽  
Logistic Regression Models ◽  
All Cause Mortality

ABSTRACT Background Social network characteristics are associated with health outcomes in later life, including mortality. Moreover, there are well-established mortality disparities across race and ethnicity. Although previous studies have documented these associations separately, limited research considers the two in tandem. The present study addressed how the associations between social network characteristics and mortality differ across race and ethnicity in later life. Methods Data were from the National Social Life, Health, and Aging Project. At baseline, 3005 respondents were interviewed with regards to their health and social networks. Five years later, 430 respondents had died. Logistic regression models were used to estimate the odds of all-cause mortality over the study period. Results Network size and kin composition were negatively associated with mortality, whereas density was positively associated with mortality. There was a stronger negative association between the kin composition and mortality for Hispanic respondents compared with white and black respondents. Conclusion The present study contributes to the large literature documenting the link between social networks and health by highlighting the importance of analyzing networks through a sociocultural lens.

Social networks and service use among representative cases of psychosis in South London

1997 ◽  
Vol 171 (1) ◽  
pp. 15-19 ◽  
Author(s):  
Thomas Becker ◽  
Graham Thornicroft ◽  
Morven Leese ◽  
Paul McCrone ◽  
Sonia Johnson ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Service Use ◽  
Network Size ◽  
Controlled Study ◽  
Network Characteristics ◽  
Social Network Size ◽  
The Social ◽  
One Year ◽  
Prospective Controlled Study

BackgroundLarge social networks in patients with severe mental illness have been reported to be associated with a low rate of hospitalisation. We aim to determine whether social network size is related to the likelihood of hospitalisation and the amount of service use.MethodAs part of a prospective controlled study, baseline interview data for a random sample of one-year prevalent cases with non-organic psychosis were analysed with respect to social network characteristics and service use during a six-month period.ResultsThe likelihood of hospitalisation decreased with an increase in network size, while the number of services used by patients grew as the social network size increased.ConclusionsWhile larger social networks may be associated with a lower likelihood of hospitalisation, they may also be related to wider use of non-hospital services.

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