Algorithm for Detecting Overlapping Community in Complex Networks

Abstract

Detecting communities from complex networks has been the focus of many recent efforts on complex networks. In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. We introduce a new algorithm for overlapping community finding, the algorithm first finds some seeds and expands these seeds into a community. We perform the algorithm on different data to demonstrate that performance of our algorithm is robust across diverse parameters. The algorithm is compared with current representative algorithms in community mining. Experimental results show the feasibility and validity of our algorithm. We show that our algorithm is highly effective at discovering community structure in different types of complex networks.