Research of Signed Networks Community Detection Based on the Tightness of Common Neighbors

According to the characteristics of positive and negative edge of signed networks, a new signed networks community detection algorithm BTCN_SNCD (Signed networks Community Detection Based on the Tightness of Common Neighbors) is proposed based on the tightness of common neighbors. Firstly, in view of the shortcomings of the traditional local similarity metrics only considering the number of common neighbors, the contribution degree and the tightness of common neighbors are defined, which can discover the initial communities with tighter structure. Secondly, for the overlapping nodes exist in initial communities, we propose overlap coefficient and community density to remerge the initial communities, thus improving community detection accuracy. Finally, the correctness and efficiency of the BTCN_SNCD algorithm are verified through a comparison with classic signed networks community detection algorithms.