  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 analyzed based on a mean-field method. Theoretical
results and numerical simulations indicate that this network model has
community structure and scale-free properties.
