Cui, YaozuWang, XingyuanEustace, Justine2020-12-102020-12-102014Cui, Y., Wang, X., & Eustace, J. (2014). Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks. Physica A: Statistical Mechanics and its Applications, 416, 198-207.http://hdl.handle.net/20.500.12661/2639Abstract. Full text article available at https://doi.org/10.1016/j.physa.2014.08.050Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.enComplex networksMaximal sub-graphBelonging degreeCommunity structureOverlapping communityComputational complexityCommunityNetworkArticle