Identifying Overlapping Communities in Directed Networks via Triangles - Qingyu Zou; Fu Liu; Tao Hou; Yihan Jiang (Institute of Advanced Engineering and Science, 2013)
A lot of complex systems in nature and society can be represented as the form of network. The small-scale subnets topological features are vital to understand the dynamics and function of the networks. Triangles comprised of three nodes are the simplest subnet in the network. Based on the triangle distribution of the complex network, we present a novel approach to detect overlapping community structure in directed networks. Different from previous studies focused on grouping nodes, our method defines communities as groups of links rather than nodes so that nodes naturally belong to more than one community. It can identify a suitable number of overlapping communities without any prior knowledge about the community. We evaluated our approach on several real-networks. Experimental results prove that the algorithm proposed is efficient for detecting overlapping communities in directed networks. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3401