Social Networks最新文献

This study explores variation in composition and strength of close friendship ties across timing and contexts of tie formation. Analyzing South Korean survey data and comparing it with existing U.S. and Korean network data, we find both similarities and differences between friendship and non-kin discussion networks in the two countries. We show that schools are a crucial source of close friendships for Koreans, shaping homophily patterns. Additionally, we uncover substantial variations in tie strength across timings and contexts of tie formation. We discuss the implications of these findings, highlighting the role of social and cultural contexts in shaping personal networks.

This study contributes to the social connectedness literature by exploring the range of social interactions that people experience on a daily basis using time diary data. First, we investigate the different types of people whom individuals encounter in everyday life (i.e., family, friends, co-workers, acquaintances, others). Quantifying the degree of this social exposure provides insight into potential sources of support, information, comparison, and control. It further allows us to capture certain types of social connections that are commonly missed in traditional social network questionnaires. Second, we examine how social context fosters interactions between different types of people. Upon analyzing data from the American Time Use Survey, we find that a majority of respondents (69%) engaged in at least one interaction with a non-household member in a 24-hour period. We also found that interactions with different types of people varied according to social context. Interactions with friends, acquaintances, and “others” were significantly more likely to occur in public contexts rather than private or professional contexts. Collectively, our findings highlight the prevalence of social exposure among the American population as well as the important role of social context in making these interactions possible.

Although negative ties may cause stress and harm well-being, they are also considered fundamental in close and ongoing relationships. This study distinguishes positive, negative, and – when characterized by both valences – ambivalent ties. Analyzing almost 10,000 personal networks from the Swiss CH-X study shows that: (1) ambivalence among family members is more prevalent than among non-family members, (2) ambivalent family dyads or triads are not negatively associated with well-being, and (3) certain balanced family triads are associated with higher well-being and an unbalanced non-family triad is associated with lower well-being. These results suggest that conflicts are not necessarily detrimental to young adults’ well-being.

Calculating the true probability that a signal will be transmitted between any pair of nodes in a network is computationally hard. Diffusion centrality, which counts the expected number of times that a signal will be transmitted, is often used as a heuristic for this probability. But this formula can lead to distorted results when used in this way, because its summation of probabilities does not take account of the inclusion–exclusion principle. This paper provides a simple new formula for the probabilities of node-to-node diffusion in networks, which uses De Morgan’s laws to account for the inclusion–exclusion principle. Like diffusion centrality, this formula is based on the assumption that the probabilities of a signal travelling along each walk in a network are independent. The probabilities it calculates are therefore called Walk-Independence Probabilities (WIP). These probabilities provide two new centrality measures, WIP centrality and blocking centrality. Blocking centrality is a type of induced centrality which is calculated when some nodes block signals.

This study examined the impact of different social networks on the mental health outcomes of older adults during the COVID-19 pandemic. Participants were 25,534 older adults from the Survey of Health, Ageing and Retirement in Europe (SHARE). The study identified five social network profiles (family, friends, spouse, diverse, others) and a “no network” group. Findings showed that, compared to the no network profile, those with spouse and family profiles are more protected against depression and loneliness during the COVID-19. In turn, individuals within friends and diverse profiles had a similar likelihood of feeling depressed, anxious, and lonely. Friends and diverse profiles had higher likelihood of suffering more anxious or lonelier than before the COVID-19 compared to the no network profile. The study further discusses possible explanations about why these profiles, which typically served as mental health protectors, were significantly affected by the unique circumstances of the COVID-19 pandemic.

The stochastic actor oriented model (SAOM) is a method for modelling social interactions and social behaviour over time. It can be used to model drivers of dynamic interactions using both exogenous covariates and endogenous network configurations, but also the co-evolution of behaviour and social interactions. In its standard implementations, it assumes that all individual have the same interaction evaluation function. This lack of heterogeneity is one of its limitations. The aim of this paper is to extend the inference framework for the SAOM to include random effects, so that the heterogeneity of individuals can be modelled more accurately.

We decompose the linear evaluation function that models the probability of forming or removing a tie from the network, in a homogeneous fixed part and a random, individual-specific part. We extend the algorithm so that the variance of the random parameters can be estimated with method of moments. Our method is applicable for the general random effect formulations. We illustrate the method with a random out-degree model and show the parameter estimation of the random components, significance tests and model evaluation. We apply the method to the Kapferer’s Tailor shop study. It is shown that a random out-degree constitutes a serious alternative to including transitivity and higher-order dependency effects.

In classical Social Network Analysis (SNA), what counted as a “social tie” was fixed by available data collection methods. The emergence of large-scale unobtrusive data collection techniques has sparked renewed interest in the very idea of what counts as a “social tie.” Importantly, there has been an acknowledgment that the core issues raised by these developments are primarily conceptual. As a result, there is renewed interest in developing a scientifically grounded characterization of what is arguably the most central concept in social network analysis. This paper contributes to this conceptual effort. I rely on a technique of conceptual representation borrowed from cognitive psychology and cognitive linguistics in which frames for concepts are represented as directed graphs linking attributes to values. I show how the frame representation helps clarify the sort of claims that network theories make (e.g., imposing restrictions on attributes and values), how it helps specify both intra and inter-conceptual relations, how it illuminates seldom noted inter-theoretical commonalities and contrasts, and how it helps avoid common conceptual pitfalls.

Adolescent health-related behaviours and outcomes are shaped by their peers through various social processes. Research using network data on friendship ties has uncovered evidence for processes such as peer influence and imitation. Much less is known about how the structure of small groups within a network, network communities that represents its meso level, affect individuals. The structure and composition of peer groups could play an important role in shaping health behaviour but knowledge of the effects of groups is limited. We used data from The Peers and Levels of Stress study, a cross-sectional social network study conducted in 2006 of 22 secondary schools in Glasgow, Scotland. Students from one year group (15–16 yrs., N = 3148; 50.8% women) provided information on socio-demographics, health behaviour and friendships via a questionnaire. Dependent variables were substance use and general mental wellbeing measured via principal components. We used a series of multilevel models with students (level 1), network communities (peer groups) identified by the Walktrap algorithm (level 2), and schools (level 3). We found substantial and moderate clustering at the peer group level for substance use and mental wellbeing, respectively. Larger and more transitive groups were associated with less substance use, but worse mental wellbeing. Addressing the methodological gap regarding the influence of the choice of group detection method on findings, we repeated our analysis using nine additional methods. The choice of the method somewhat influenced peer group variance and greatly influenced association of peer group properties with health. This study makes two key contributions to school-health improvement research. Beyond describing peer group clustering health outcomes, this is the first demonstration that structural and compositional characteristics of peer groups are associated with individual health, while highlighting the sensitivity of findings to group detection method used.

Research suggests that coming from a lower economic background compromises social integration at school, yet the precise mechanisms underlying this link remain unknown. Therefore, this study examined the effect of household income on friendship network dynamics among classmates in a large sample of Swedish youths (n = 4787 from 235 classes, m age = 14.65, 51% girls, and 33% immigrant background), using multilevel longitudinal social network analysis. Over time, students from poorer households were less often selected as a friend by classmates and they less often initiated or maintained friendship ties than students from higher income households. Furthermore, different conceptualizations of income relative to classmates did not impact friendship formation tendencies. The findings indicate that theories of relative income do not extend understanding of students’ friendship formation beyond processes related to absolute income. In addition, this study suggests that the social integration of students from low-income households could be boosted by both promoting their agency in forming friendships and preventing exclusion by classmates.

Different lines of research have argued that specific groups, such as boys or ethnic minorities, are more prone to develop an anti-school culture than others, leading to group differences in the social acceptance of high performers. Taking an ecological view, we ask to what extent the school context promotes or prevents the emergence of group-specific oppositional cultures. Theoretically, we argue that group-based oppositional cultures become more likely in schools with low socio-economic resources and in schools where socio-economic differences align with demographic attributes. We test our hypotheses based on data from a large-scale, four-wave network panel survey among more than 4000 students in Germany. Applying stochastic actor-oriented models for the coevolution of networks and behavior, we find that group-based oppositional cultures in which students like high performers less are very rare. However, in line with theoretical expectations, the less resourceful a school is, the more boys tend to evaluate high-performing peers less positively than girls do. Moreover, the more ethnic minority boys are socioeconomically disdvantaged in a school, the more they tend to evaluate high performers less positively than majority boys do.