Solidarity as a byproduct of professional collaboration: Social support and trust in a coworking space

This article investigates solidarity arising from economic exchange, by studying a multiplex network of collaboration, trust and social support. After a qualitative pre-study, we performed a full-network survey on a group of independent professionals sharing a coworking space and occasionally collaborating with each other. By running multivariate Exponential Random Graph Models, we showed that successful collaboration might not determine expectations of social support. However, these relationships were related to business-based trust ties, which were predicted by collaboration. Our results suggest that solidarity can emerge as a byproduct of peer economic exchange when trust mediates between professional relationships and expressive ties.     

Duality of departmental specializations and PhD exchange: A Weberian analysis of status in interaction using multilevel exponential random graph models (mERGM)

Weber proposes that lifestyle similarities preserve status by producing interactional closure between status similar actors. I investigate this theory on academic status hierarchies by conceptualizing sub-disciplinary specializations as departmental lifestyles and PhD exchange networks as interdepartmental interactions. Multilevel exponential random graph models (mERGM) reveal that the more specializations departments share, the more likely they are to exchange personnel. On the flip side, departments that do not share specializations are less likely to exchange doctoral candidates. Moreover, shared specializations are key determinants of closure between elite departments. These results support Weber’s theory and suggest that shared specializations preserve existing patterns of inequality between elite and non-elite departments.     

基于ERGM的协同创新网络形成影响因素实证研究

以电信产业申请并授权的合作专利为数据基础,从社会网络视角,构建企业、大学和研究院所间协同创新网络,并识别影响组织间协同创新网络形成的内生网络构型,以及外生节点属性两个维度的影响因素。基于指数随机图模型(ERGM),实证分析了这些因素对协同创新网络形成的影响程度。研究表明:协同创新网络是组织协同关系社会化特征的体现,其形成受内生因素和外生因素的共同作用;协同创新网络中,边结构表现出显著的稀疏效应,网络多涌现易于形成资源共享与交换的星型结构和三角结构;网络中组织的合作开放度和区域同配性,能够增加网络节点间的连接概率,而组织的协同创新能力与组织类型同配对网络中新合作关系的形成,并没有表现出显著的促进作用。     

Motivations for self-assembling into project teams

This study investigates the self-assembly mechanisms of ad hoc project teams using a bipartite network perspective. Individuals and projects are modeled as two types of nodes and team membership as relations between them. This approach enables us to investigate factors that impact voluntary team assembly at the individual, dyadic, and team levels simultaneously. Using Exponential Random Graph Models (ERGM/p*), we study players’ combat teams in a Massively Multiplayer Online Role-Playing Game (MMORPG) as a case of self-assembled project teams. Empirical results show that individuals are motivated to join ad hoc teams to complete difficult projects but not projects with long durations. We also found that individuals tend to collaborate with specific teammates who have complementary skills, those who have similar age or skill level, and those who are affiliated with the same organizational entity.     

Scaling bias in pooled exponential random graph models

Researchers often use pooled exponential random graph models (ERGM) to analyze samples of networks. However, pooled ERGM—here, understood to include both meta-regression and combined estimation on a stacked adjacency matrix—may be biased if there is heterogeneity in the latent error variance (‘scaling’) of each lower-level model. This study explores the implications of scaling for pooled ERGM analysis. We illustrate that scaling can produce bias in pooled ERGM coefficients that is more severe than in single-network ERGM and we introduce two methods for reducing this bias. Simulations suggest that scaling bias can be large enough to alter conclusions about pooled ERGM coefficient size, significance, and direction, but can be substantially reduced by estimating the marginal effect within a block diagonal or random effects meta-regression framework. We illustrate each method in an empirical example using Add Health data on 15 in-school friendship networks. Results from the application illustrate that many substantive conclusions vary depending on choice of pooling method and interpretational quantity.     

Who are the objects of positive and negative gossip at work?: A social network perspective on workplace gossip

Gossip is informal talking about colleagues. Taking a social network perspective, we argue that group boundaries and social status in the informal workplace network determine who the objects of positive and negative gossip are. Gossip networks were collected among 36 employees in a public child care organization, and analyzed using exponential random graph modeling (ERGM). As hypothesized, both positive and negative gossip focuses on colleagues from the own gossiper's work group. Negative gossip is relatively targeted, with the objects being specific individuals, particularly those low in informal status. Positive gossip, in contrast, is spread more evenly throughout the network.     

Bayesian Inference for Contact Networks Given Epidemic Data

Abstract. In this article, we estimate the parameters of a simple random network and a stochastic epidemic on that network using data consisting of recovery times of infected hosts. The SEIR epidemic model we fit has exponentially distributed transmission times with Gamma distributed exposed and infectious periods on a network where every edge exists with the same probability, independent of other edges. We employ a Bayesian framework and Markov chain Monte Carlo (MCMC) integration to make estimates of the joint posterior distribution of the model parameters. We discuss the accuracy of the parameter estimates under various prior assumptions and show that it is possible in many scientifically interesting cases to accurately recover the parameters. We demonstrate our approach by studying a measles outbreak in Hagelloch, Germany, in 1861 consisting of 188 affected individuals. We provide an R package to carry out these analyses, which is available publicly on the Comprehensive R Archive Network.     

Who speaks up to whom? A relational approach to employee voice

We adopt a relational approach to examine the effects of social relations and formal structure on who speaks up to whom about problems at work. Data were collected in a two-wave employee survey in three Dutch preschools. Using exponential random graph modeling, we found significant positive effects of formal structure (recipient's hierarchical level; team co-membership) and good relations between speaker and recipient on the likelihood of voice in a dyad. Speaker's hierarchical level had positive effects, significant in Wave 1. Speaker's degree centrality significantly reduced the likelihood of voice, whereas recipient's degree centrality had no effect.     

Online news diffusion dynamics and public opinion formation: A case study of the controversy over judges’ personal opinion expression on SNS in Korea

On the Internet, the line between news and opinion becomes blurred in terms of content and form. In this sense, the processes of news diffusion on the Internet and online public opinion formation are integrated. This study selects one Korean example about the private tweet of a judge about government social network service (SNS) regulation and analyzes citation networks from one news/opinion to another news/opinion. By relying on social network analysis (SNA) methods, this study examines how news/opinions diffuse and how they interact and influence each other's ideological frame within agencies sharing the same ideology and between agencies whose ideologies contrast. The results show that public discourse on the Internet is clearly polarized and fragmented along political ideological lines. Additionally, the findings show that the winner is the conservative bloc because it succeeds in achieving within-bloc solidarity and ensures the resonance of news frames with the cultural values of Korean society. Implications for these findings in modern democracy are also discussed.