2005/10/26 by Chunguang Li, Philip K. Maini, Philip K Maini
Computer Science · Physics and Astronomy · Psychology · #Complex Network Analysis Techniques #Mental Health Research Topics #Opportunistic and Delay-Tolerant Networks #cond-mat.dis-nn #physics.soc-ph
paper · pdf · doi:10.1088/0305-4470/38/45/002
published as Journal of Physics A: Mathematical and General 38 (2005) 9741-9749 · 10 pages, 6 figures
arxiv created 2005/10/26 · openalex publication_date 2005/10/26 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/30
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.