Abstract: The recognition of community in complex social networks by mining big data can favor the quantitative research for economic,political and demographic problems.Community recognition algorithms have become a hot topic of current research.This paper focused on the research of overlapping community discovery,and proposed the overlapping community detection algorithm GWCR,which is based on gravity factor of weighted networks.Firstly,the GWCR algorithm selects the node with the largest gravitation factor as the center node,and uses the gravitation factor between one node and the central node as a measure.The node whose gravitation factor is larger than the threshold will be included in the community.Finally,overlapping communities are discovered by identifying overlapping nodes.Experimental results on three real network datasets show that,compared with conventional overlapping community detection algorithm,GWCR has higher modularity value.

Key words: Gravity factor,Community recognition,Weighted network,Overlapping community