Characterizing the Structure of Affiliation Networks

Our society contains all types of organizations, such as companies, research groups and hobby clubs. Affiliation networks, as a large and important portion of social networks, consist of individuals and their affiliation relations: Two individuals are connected by a link if they belong to the same organization(s). Affiliation networks naturally contain many fully connected cliques, since the nodes of the same organization are all connected with each other by defini-tion. In this paper, we present methods which facilitate the computation for characterizing the real-world affiliation networks of ArXiv coauthorship, IMDB actors collaboration and SourceForge collaboration. We propose a growing hypergraph model with preferential attachment for affiliation networks which reproduces the clique structure of af-filiation networks. By comparing computational results of our model with measurements of the real-world affiliation networks of ArXiv coauthorship, IMDB actors collaboration and SourceForge collaboration, we show that our model captures the fundamental properties including the power-law distributions of group size, group degree, overlapping depth, individual degree and interest-sharing number of real-world affiliation networks, and reproduces the properties of high clustering, assortative mixing and short average path length of real-world affiliation networks