Searching for Communities in Bipartite Networks

Details Searching for Communities in Bipartite Networks Searching for Communities in Bipartite Networks

2008-03-19

arxiv.org/abs/0803.2854v1

Physics

Physics and Society

12 pages, 4 figures, to appear in "Proceedings of the 5th Jagna International Workshop: Stochastic and Quantum Dynamics of Bio

Scientific paper

10.1063/1.2956795

Bipartite networks are a useful tool for representing and investigating interaction networks. We consider methods for identifying communities in bipartite networks. Intuitive notions of network community groups are made explicit using Newman's modularity measure. A specialized version of the modularity, adapted to be appropriate for bipartite networks, is presented; a corresponding algorithm is described for identifying community groups through maximizing this measure. The algorithm is applied to networks derived from the EU Framework Programs on Research and Technological Development. Community groups identified are compared using information-theoretic methods.

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