Social Networks最新文献

Social relations are embedded in material, cultural, and institutional settings that affect network dynamics and the resulting topologies. For example, romantic entanglements are subject to social and cultural norms, interfirm alliances are constrained by country-specific legislation, and adolescent friendships are conditioned by classroom settings and neighborhood effects. In short, social contexts shape social relations and the networks they give rise to. However, how and when they do so remain to be established. This paper presents network ecology as a general framework for identifying how the proximal environment shapes social networks by focusing interactions and social relations, and how these interactions and relations in turn shape the environment in which social networks form. Tie fitness is introduced as a metric that quantifies how well particular dyadic social relations would align with the setting. Using longitudinal networks collected on two cohorts each in 18 North American schools, i.e., 36 settings, we develop five generalizable observations about the time-varying fitness of adolescent friendship. Across all 252 analyzed networks, tie fitness predicted new tie formation, tie longevity, and tie survival. Dormant fit ties cluster in relational niches, thereby establishing a resource base for social identities competing for increased representation in the relational system.

Homophily – the fact that friendships happen at a higher rate among similar individuals – does not necessarily imply homophilic selection – the tendency to look for similar friends. This is particularly true for socioeconomic homophily: because individuals’ social class impacts most aspects of their lives, there are several ways in which it can favor homogeneity in friendship networks. Applying this view to the relationships of French middle-school students, the present article tries to unravel the contribution of various relational processes to the emergence of socioeconomic homophily. Stochastic Actor-Oriented Models, a class of generative models designed for network panel data, are applied to the friendship networks of 820 students surveyed over a year and a half. Simulations derived from the estimated models are then used to assess the impact of different processes on aggregated levels of homophily. To that aim, a new metric is proposed that help researchers decompose an observed property of a network into a set of contributions from low-order processes, called “contribution scores”. Results suggest that direct homophilic selection can be important in explaining socioeconomic homophily, but not in all cases. Indirect inducers, such as residential propinquity or ethnic selection, also play a significant role. Moreover, endogenous network processes – namely reciprocation and transitive closure – strongly contribute to homophily by reinforcing other homophily-inducing processes.

Advice-seeking typically occurs across organizational boundaries through informal connections. By using Stochastic Actor-Oriented Models (SAOM), previous research has tried to identify the micro-level mechanisms behind these informal connections. Unfortunately, these models assume perfect network information, require agents to perform too cognitively demanding decisions, and do not account for threshold-based critical events, such as simultaneous tie changes. In the context of knowledge-intensive organizations, the shortage of high-skilled professionals could determine complex network effects given that many less-skilled professionals would seek advice from a few easily overloaded, selective high-skilled, who are also sensitive to status demotion. To capture these context-specific organizational features, we have elaborated on SAOM with an agent-based model that assumes local information, status-based tie selection, and simultaneous re-direction of multiple ties. By fitting our simulated networks to Lazega’s advice network used in previous research, we reproduced the same set of macro-level network metrics with a parsimonious model based on more empirically plausible assumptions than previous research. Our findings show the advantage of exploring multiple generative paths of network formation with different models.

Individuals are more likely to interact with people who are similar in terms of socio-demographics and values than dissimilar people, which is often explained by a focus on selection effects. Yet, tie loss of dissimilar ties might also cause network homogeneity. Unfortunately, within the literature, there is a relative dearth of knowledge on the relationship between (dis)similarity and tie loss. Hence, we address this gap by theorizing and testing the relation between (dis)similarity and tie loss in the core discussion network (CDN) of Dutch citizens, also considering how ties are embedded in the CDN.

This paper reports on a network-based investigation of the gendered nature of work in the screen sector. Using nine years of Australian film and television production data, we explore how the networks of project-based collaboration might explain the disparities in the career trajectories of men and women. Our analysis finds that projects with men as directors tend to reproduce familiar teams to the exclusion of women, while projects led by women in key creative roles tend to make more space for women. Moreover, we find that there is a significant number of men who only work with men (regardless of whether they have worked with them before), but no corresponding group of women who only work with women. Our findings bear on proposed equity interventions, especially government policies designed to encourage women to enter the industry. Ultimately, even accounting for the statistical domination of men in the network, we argue that inequities in the organisation of the screen sector appear to be driven much more by the closed network behaviours of men than they are by the positioning or behaviour of women.

Although research has explored social factors influencing memory performance during adolescence, the impact of adolescent social network positions remains largely unknown. This study examines whether adolescent network position is associated with memory performance in adulthood, while also considering potential gender differences. The study used a sibling sample from the National Longitudinal Study of Adolescent to Adult Health (N = 2462) and employed sibling fixed effects models to account for unobserved family background factors, such as genetics, parental characteristics, family environment, and childhood neighborhood. Four dimensions of adolescent network position—i.e., popularity, sociality, degree centrality, and closeness centrality—were sociometrically assessed in schools. Memory performance in adulthood was measured using the Rey Auditory Verbal Learning Test. The sibling fixed effects estimates indicate that sociality, degree centrality, and closeness centrality are significantly associated with increased memory performance in adulthood, even after controlling for unobserved family heterogeneity as well as a set of individual-level covariates. In contrast, controlling for unobserved family heterogeneity attenuated the association for popularity, making it statistically insignificant. This study also provides evidence of gender differences in the association between social network position and memory performance. The associations for popularity, sociality, and degree centrality are more pronounced among men than women. This study’s findings highlight the importance of adolescent network positions as social determinants in shaping cognitive outcomes over the life course. Interventions that encourage positive peer interactions and reduce social isolation during adolescence may help improve cognitive health in the population.

This paper investigates the case of interference, when a unit’s treatment also affects other units’ outcome. When interference is at work, policy evaluation mostly relies on the use of randomized experiments under cluster interference and binary treatment. Instead, we consider a non-experimental setting under continuous treatment and network interference. In particular, we define spillover effects by specifying the exposure to network treatment as a weighted average of the treatment received by units connected through physical, social or economic interactions. Building on Forastiere et al. (2021), we provide a generalized propensity score-based estimator to estimate both direct and spillover effects of a continuous treatment. Our estimator also allows to consider asymmetric network connections characterized by heterogeneous intensities. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of policy interventions in agricultural markets. Our results show that, in this context, neglecting interference may underestimate the degree of policy effectiveness.

Studies often find gender differences in social networks in later life, but are these findings universal, or do they differ in various cultural contexts? To address this research gap, the current study examines the association between gender differences in social relationships and country-level gender-role attitudes. We combined data from the Survey of Health, Ageing and Retirement in Europe (SHARE) of individuals aged 50 years and older with country-level data on gender-role attitudes from the European Values Survey (EVS) for 15 European countries. We estimated a series of multivariate hierarchical regression models that predicted the size of the personal social network, its emotional closeness, and the proportion of the spouse, children, and friends in the network. The results indicated gender differences in social network characteristics. Women reported larger social networks and were more likely to have larger proportions of children and friends but smaller proportions of the spouse in their social networks. The magnitude of gender differences was associated with country-level gender-role attitudes. In countries with more egalitarian gender-role attitudes, women had larger networks with a larger proportion of friends compared to men. In countries with more traditional gender-role attitudes, women had larger proportions of their children and spouse in their social networks and had emotionally closer networks. Our findings suggest that the societal context and opportunity structures for social interactions play an important role in shaping the structure of women’s and men’s social relationships in later life.

Recent studies have found order effects in social network data collection, where later names on a roster receive fewer nominations. Some thus argue for randomizing name orders or sampling peer names for survey rosters. We model order effects as biases in nomination choices and demonstrate observational and experimental methods for assessing these biases and illuminating their mechanisms. Employing these lenses, we find little evidence of order effects on eight sociometric questions in four middle school cohorts over six waves. To inform future work, we investigate aspects of the survey situation that may amplify or attenuate order effects. Analyzing these moderating forces offers guidance for detecting, understanding, and mitigating order effects in future research.

The structure of many complex social networks is determined by nodal and dyadic covariates that are endogenous to the tie variables. While exponential-family random graph models (ERGMs) have been very successful in modeling social networks with exogenous covariates, they are often misspecified for networks where some covariates are stochastic. Exponential-family random network models (ERNMs) are an extension of ERGM that retain the desirable properties of ERGM, but allow the joint modeling of tie variables and covariates. We compare ERGM to ERNM to show how conclusions of ERGM modeling are improved by consideration of the ERNM framework. In particular, ERNM simultaneously represents the effects of social influence and social selection processes, while commonly used models do not.