Overlapping community detection based on node location analysis

As a novel overlapping community detection theory, topology potential has inspired many methods. However, these methods ignore the mass difference between nodes, leading to inaccurate topological potential values of nodes. Moreover, additional strategies are needed to determine the community affiliation of nodes, further complicating the process of community detection. In this paper, we propose a new overlapping community detection method based on node location analysis. In the proposed method, the PageRank algorithm is used to evaluate the node mass, and the community affiliation of nodes is determined based on their positions in the inherent peak-valley structure of the topology potential field. Experimental results show that the proposed method exhibits excellent performance on artificial and real-world networks and outperforms other topology-potential-based and most non-topology-potential-based methods.