Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Proceedings of the forty-first annual ACM symposium on Theory of computing
Detecting Highly Overlapping Communities with Model-Based Overlapping Seed Expansion
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Graph Spectra for Complex Networks
Graph Spectra for Complex Networks
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Social networks, as well as many other real-world networks, exhibit overlapping community structure. Affiliation networks, as a large portion of social networks, consist of cooperative individuals: two individuals are connected by a link if they belong to the same organisations, such as companies, research groups and hobby clubs. Affiliation networks naturally contain many fully connected communities/groups. In this paper, we characterise the structure of the real-world affiliation networks, and propose a growing hypergraph model with preferential attachment for affiliation networks, which reproduces the clique structure of affiliation networks. By comparing computational results of our model with measurements of the real-world affiliation networks of ArXiv co-authorship, 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.