The clustering coefficient and community structure of bipartite networks
arXiv:0710.0117 · doi:10.1016/j.physa.2008.09.006
Abstract
Many real-world networks display a natural bipartite structure. It is necessary and important to study the bipartite networks by using the bipartite structure of the data. Here we propose a modification of the clustering coefficient given by the fraction of cycles with size four in bipartite networks. Then we compare the two definitions in a special graph, and the results show that the modification one is better to character the network. Next we define a edge-clustering coefficient of bipartite networks to detect the community structure in original bipartite networks.
9 pages, 4 figures
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