An Overlapping Community Discovery Algorithm Based on Label Propagation Constructing a K-Clique Network

Since the initial label scattering can easily lead to large randomness of label propagation, this paper proposes an overlapping community discovery algorithm based on label propagation constructing a k-clique network. First, according to the fact that the nodes in the community are closely related and easy to generate maximal cliques, k-cliques are introduced in the initial stage, k-cliques in the network are searched, and they are regarded as new nodes; Then, by formulating a strategy for building a k-clique network, a clique-scatter network is made up. While optimizing the original network structure, a large number of nodes in the network are initially divided to reduce the unnecessary label propagation process and improve the stability of label propagation algorithm; finally, label propagation is performed in the optimized new network to obtain the final division result. In this paper, we use real network and artificial network to conduct experiments. the results show that the algorithm has good performance in overlapping modularity and Normalized Mutual Information, and is feasible and effective.