Abstract
An important puzzle in social network research is to explain how macro-level structures emerge from micro-level network processes. Explaining the emergence and stability of groups in social networks is particularly difficult for two reasons. First, because groups are characterized both by high connectedness within (group cohesion) and lack of connectedness between them (group boundaries). Second, because a large number of theoretical micro-level network processes contribute to their emergence. We argue that traditional social network theories that are concerned with the evolution of positive relations (forces of attraction) are not sufficient to explain the emergence of groups because they lack mechanisms explaining the emergence of group boundaries. Models that additionally account for the evolution of negative ties (forces of repulsion) may be better to explain the emergence and stability of groups in social networks. We build a theoretical model and illustrate it by fitting stochastic actor-oriented models (SAOMs) to empirical data of co-evolving networks of friendship and dislike among 479 secondary-school students. The SAOMs include a number of newly developed effects expressing the co-evolution between positive and negative ties. We then simulate artificial networks from the estimated models to explore the micro-macro link. We find that a model that considers forces of attraction and repulsion simultaneously is better at explaining groups in social networks. In the long run, however, the empirically informed simulations generate networks that are too stylized to be realistic, raising further questions about model degeneracy and time heterogeneity of group processes.
Highlights
Important parts of human life are organized in social groups
We argue that traditional social network theories that are concerned with the evolution of positive relations are not sufficient to explain the emergence of groups because they lack mechanisms explaining the emergence of group boundaries
We argued that forces of attraction that explain the formation of positive ties within groups of individuals are necessary to express group cohesion, but that they cannot fully explain how stable groups emerge within a larger social context
Summary
Important parts of human life are organized in social groups. In large social contexts, like schools, universities, workplaces, neighborhoods, and digital online communities, people form smaller groups in which they experience a higher level of communication, safety, belonging, interdependence, social norms, and psychological well-being as compared to the rest of the social context (Homans, 1950; Kadushin, 2002; Baumeister and Leary, 1995; Cartwright and Ed Zander, 1960; Turner et al, 1987; Berkman et al, 2000). The model that we propose builds upon social network theory and incorporates a battery of well-known positive social mechanisms, for example, reciprocity, transitivity and degree popularity (Rivera et al, 2010; Kadushin, 2012) These mechanisms can be linked to the creation of positive ties within an existing group (group cohesion) and can operate as forces of attraction. We anticipate that the model which includes forces of repulsion will be better able to explain the emergence and stability of structural groups We test this proposition empirically in a two-step procedure, using a combination of two established analytical strategies. In accordance with our theoretical expectations, we find that the model with only forces of attraction is not able to generate groups with clear boundaries that are stable through time This macro-outcome is better represented when forces of attraction and repulsion are considered simultaneously.
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