Events in social networks : a stochastic actor-oriented framework for dynamic event processes in social networks

Interactions between people are ubiquitous. When people make phone calls, transfer money, connect on social network sites, or visit each other, these actions can be collected as dyadic, directed, relational events. Each of those events can be understood as driven by multiple individual decisions that at least partially involve rational considerations. This book aims at developing models that allow to understand individual event decisions in the context of large social networks

The co-evolution of emotional well-being with weak and strong friendship ties

Social ties are strongly related to well-being. But what characterizes this relationship? This study investigates social mechanisms explaining how social ties affect well-being through social integration and social influence, and how well-being affects social ties through social selection. We hypothesize that highly integrated individuals - those with more extensive and dense friendship networks - report higher emotional well-being than others. Moreover, emotional well-being should be influenced by the well-being of close friends. Finally, well-being should affect friendship selection when individuals prefer others with higher levels of well-being, and others whose well-being is similar to theirs. We test our hypotheses using longitudinal social network and well-being data of 117 individuals living in a graduate housing community. The application of a novel extension of Stochastic Actor-Oriented Models for ordered networks (ordered SAOMs) allows us to detail and test our hypotheses for weak- and strong-tied friendship networks simultaneously. Results do not support our social integration and social influence hypotheses but provide evidence for selection: individuals with higher emotional well-being tend to have more strong-tied friends, and there are homophily processes regarding emotional well-being in strong-tied networks. Our study highlights the two-directional relationship between social ties and well-being, and demonstrates the importance of considering different tie strengths for various social processes

Interactions, Actors, and Time: Dynamic Network Actor Models for Relational Events

Ample theoretical work on social networks is explicitly or implicitly concerned with the role of interpersonal interaction. However, empirical studies to date mostly focus on the analysis of stable relations. This article introduces Dynamic Network Actor Models (DyNAMs) for the study of directed, interpersonal interaction through time. The presented model addresses three important aspects of interpersonal interaction. First, interactions unfold in a larger social context and depend on complex structures in social systems. Second, interactions emanate from individuals and are based on personal preferences, restricted by the available interaction opportunities. Third, sequences of interactions develop dynamically, and the timing of interactions relative to one another contains useful information. We refer to these aspects as the network nature, the actor-oriented nature, and the dynamic nature of social interaction. A case study compares the DyNAM framework to the relational event model, a widely used statistical method for the study of social interaction data

Partnership Ties Shape Friendship Networks: A Dynamic Social Network Study

Partnership ties shape friendship networks through different social forces. First, partnership ties drive clustering in friendship networks: individuals who are in a partnership tend to have common friends and befriend other couples. Second, partnership ties influence the level of homophily in these emerging friendship clusters. Partners tend to be similar in a number of attributes (homogamy). If one partner selects friends based on preferences for homophily, then the other partner may befriend the same person regardless of whether they also have homophilic preferences. Thus, two homophilic ties emerge based on a single partner's preferences. This amplification of homophily can be observed in many attributes (e.g., ethnicity, religion, age). Gender homophily, however, may be de-amplified, as the gender of partners differs in heterosexual partnerships. In our study, we follow dynamic friendship formation among 126 individuals and their cohabiting partners in a university-related graduate housing community over a period of nine months (N = 2,250 self-reported friendship relations). We find that partnership ties strongly shape the dynamic process of friendship formation. They are a main driver of local network clustering and explain a striking amount of homophil

How to analyze dynamic network patterns of high performing teams

AbstractThe dynamic communication network within teams affects the performance of teams. But how can we analyze these emerging networks? We identified three research areas that have to be included for this purpose. First we summarize empirical studies concerning team networks and performance to point out the need of longitudinal investigations. Second we present the multi-level multi-theoretical model by Monge and Contractor (2003) which provides a theoretical framework to explain the evolution of communication networks within teams. Third a stochastic model is introduced that allows analyzing event based data, like e-mail streams, using exponential random graph models. We propose to include these three research areas that enable researchers and practitioners to analyze dynamic network patterns of virtual teams

Status perception matter: Understanding disliking among adolescents

"The emergence of disliking relations depends on how adolescents perceive the relative informal status of their peers. This notion is examined on a longitudinal sample using dynamic network analysis (585 students across 16 classes in 5 schools). As hypothesized individuals dislike those who they look down on (disdain) and conform to others by disliking those who they perceive as being looked down on by their peers (conformity). The inconsistency between status perceptions also leads to disliking, when individuals do not look up to those who they perceive to be admired by peers (frustration). No evidence is found that adolescents do not dislike those who they look up to (admiration). Results demonstrate the role of status perceptions on disliking tie formation. Keywords: disliking ties, social networks, status perception, adolescents, RSiena models

Assimilation and differentiation: A multilevel perspective on organizational and network change

This paper builds on recently derived stochastic actor-oriented models (SAOMs) for the coevolution of one-mode and two-mode networks, and extends them to the analysis of how concurrent multilevel processes of (internal) organizational and (external) network change affect one another over time. New effects are presented that afford specification and identification of two apparently conflicting micro-relational mechanisms that jointly affect decisions to modify the portfolio of internal organizational activities. The first mechanism, assimilation, makes network partners more similar by facilitating the replication and diffusion of experience. The second mechanism, functional differentiation, operates to maintain and amplify differences between network partners by preventing or limiting internal organizational change. We illustrate the empirical value of the model in the context of data that we have collected on a regional community of hospital organizations connected by collaborative patient transfer relations observed over a period of seven years. We find that processes of social influence conveyed by network ties may lead both to similarity and differences among connected organizations. We discuss the implications of the results in the context of current research on interorganizational networks

Forms of Dependence: Comparing SAOMs and ERGMs From Basic Principles

Two approaches for the statistical analysis of social network generation are widely used; the tie-oriented exponential random graph model (ERGM) and the stochastic actor-oriented model (SAOM) or Siena model. While the choice for either model by empirical researchers often seems arbitrary, there are important differences between these models that current literature tends to miss. First, the ERGM is defined on the graph level, while the SAOM is defined on the transition level. This allows the SAOM to model asymmetric or one-sided tie transition dependence. Second, network statistics in the ERGM are defined globally but are nested in actors in the SAOM. Consequently, dependence assumptions in the SAOM are generally stronger than in the ERGM. Resulting from both, meso- and macro-level properties of networks that can be represented by either model differ substantively and analyzing the same network employing ERGMs and SAOMs can lead to distinct results. Guidelines for theoretically founded model choice are suggested

Social Networks and Social Settings: Developing a Coevolutionary View

One way to think about social context is as a sample of alters. To understand individual action, therefore, it matters greatly where these alters may be coming from, and how they are connected. According to one vision, connections among alters induce local dependencies—emergent rules of social interaction that generate endogenously the observed network structure of social settings. Social selection is the decision of interest in this perspective. According to a second vision, social settings are collections of social foci—physical or symbolic locales where actors meet. Because alters are more likely to be drawn from focused sets, shared social foci are frequently considered as the main generators of network ties, and hence of setting structure. Affiliation to social foci is the decision of central interest in this second view. In this paper we show how stochastic actor-oriented models (SAOMs) originally derived for studying the dynamics of multiple networks may be adopted to represent and examine these interconnected systems of decisions (selection and affiliation) within a unified analytical framework. We illustrate the empirical value of the model in the context of a longitudinal sample of adolescent participating in the Glasgow Teenage Friends and Lifestyle Study. Social selection decisions are examined in the context of networks of friendship relations. The analysis treats musical genres as the main social foci of interest