A Fast Overlapping Community Detection Algorithm Based on Label Propagation and Social Network Graph Clustering Coefficient

Abstract

Detecting community structure on social network has been an important and interesting issue on which many researchers have paid much attention and developed applications. Many graph clustering algorithms have been applied to find disjoint communities, i.e each node belongs to a single community. However, for social network in particular, public communication network in general, most of communities are not completely detached but they may be embedding, overlapping or crossing, that means certain nodes can belong to more than one community. Overlapping node plays a role of interface between communities and it is really interesting to study the community establishment of these nodes because it reflects dynamic behaviuor of participants.This article introduces the algorithm to find overlapping communities on huge social network. The proposed COPACN algorithm has been developed on the basis of label propagation, using advanced clustering coefficient to find overlapping communities on social network. Exprermental results on a set of popular, standard social networks and certain real network have shown the high speed and high effiency in finding overlapping structures.