2009 CoEvolutionofSocialandAffiliati

Subject Headings:

Notes

Categories and Subject Descriptors: H.2.8 Database Management: Database Applications — Data Mining.
General Terms: Algorithms, Measurement, Experimentation

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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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 CoEvolutionofSocialandAffiliati	Elena Zheleva Hossam Sharara Lise Getoor			Co-evolution of Social and Affiliation Networks		KDD-2009 Proceedings		10.1145/1557019.1557128		2009