document: Co-evolution of social and affiliation networks In our work , we address the problem of modeling social network generation which explains both link and group formation . Recent studies on social network evolution propose generative models which capture the statistical properties of real-world networks related only to node-to-node link formation . We propose a novel model which captures the co-evolution of social and affiliation networks . We provide surprising insights into group formation based on observations in several real-world networks , showing that users often join groups for reasons other than their friends . Our experiments show that the model is able to capture both the newly observed and previously studied network properties . This work is the first to propose a generative model which captures the statistical properties of these complex networks . The proposed model facilitates controlled experiments which study the effect of actors ' behavior on the evolution of affiliation networks , and it allows the generation of realistic synthetic datasets .
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