TY - CONF T1 - Co-evolution of social and affiliation networks T2 - Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining Y1 - 2009 A1 - Zheleva,Elena A1 - Sharara,Hossam A1 - Getoor, Lise KW - affiliation network KW - Evolution KW - graph generator KW - groups KW - social network AB - 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. JA - Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining T3 - KDD '09 PB - ACM CY - New York, NY, USA SN - 978-1-60558-495-9 UR - http://doi.acm.org/10.1145/1557019.1557128 M3 - 10.1145/1557019.1557128 ER -