Detecting Overlapping Communities of Weighted Networks by Central Figure Algorithm

In recent years, the community structures in complex networks has become a research hotspot. In this paper, we focus on weighted networks and propose a unique algorithm on detecting overlapping communities of weighted networks based on central figure with considerable accuracy. In the algorithm, all the central figures are first extracted. Then to each central figure, nodes are absorbed by closures and weak ties. The experiments are based on LFR Benchmark. Through the experiment, we can know that the performance of our algorithm is better than that of COPRA (Community Overlap Propagation Algorithm) algorithm.