Homophily as a process generating social networks: insights from Social Distance Attachment model.
2019
Real-world social networks often exhibit high levels of clustering, positive degree assortativity, short average path lengths (small-world property) and bounded, which means not scale-free, degree distributions. At the same time homophily, defined as the propensity of similar agents to connect to each other, is one of the characteristic features observed in many human and animal societies. In this paper we examine an extent to which homophily may be considered an important force generating and structuring social networks. To do so, we conduct a simulation study based on Social Distance Attachment (SDA) network model in which nodes are embedded in an abstract social space and connection probabilities depend functionally on distances between nodes. We find that homophily, especially when combined with random edge rewiring, can reproduce many of the characteristic features of social networks. Additionally, we devise a hybrid model combining SDA with configuration model that allows to generate homophily-driven networks with arbitrary degree distributions and we use it to study interactions of homophily with processes imposing constraints on degree distributions. We show that the effects of homophily on clustering are robust with respect to distribution constraints, while degree assortativity can be highly dependent on the particular kind of enforced degree sequence. Numerical results are additionally enriched with a review of theoretical and/or analytical arguments supporting both the general geometric approach to social networks and homophily as well as the particular functional form of the connection probability function assumed in SDA model.
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