Research on Community Center-metric and Community Detection Algorithm for Complex Networks

Abstract

To resolved the present-existing problem that local community detection is great sensitive to the initial node position in large-scale network, a new community detection algorithm CCMA (Community Central Metric Algorithm) by using the community central node-set as the initial node is proposed. Firstly, community centrality node-set (LC ≥ 0) is determined by using Leverage Centrality (LC). Then, starting from the node with the largest central index, we expand the community according to the community fitness function until completing the acquisition of the entire local community. And community’s numbers does not need to be given. Experiments on existing real networks and artificial networks show that our community central metric algorithm can detect local community structures more efficiently and accurately by comparing the method of expanding community’s central node with the existing best local community detection method.