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Many social and biological networks consist of communities - groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties. © 2005 IOP Publishing Ltd.

Original publication

DOI

10.1088/0305-4470/38/45/002

Type

Journal article

Journal

Journal of Physics A: Mathematical and General

Publication Date

11/11/2005

Volume

38

Pages

9741 - 9749