关键词: 社区检测, 重叠社区, 引力作用, 适应度函数

Abstract: Community structure is an important feature of complex networks, and it is important to analyze and understand the structure and function of complex networks by community detection. The algorithms based on local community detection are popularly used to solve this problem because of their efficiency and validity. Compared with global community discovery methods, local community discovery methods do not require information about the overall structure of complex networks. However, most of the available algorithms have low utilization of local information, and the fitness function in the expansion process is unable to dynamically measure the connectivity between nodes, which makes the community detection results deficient in terms of quality and stability. Based on this, an overlapping community detection algorithm based on gravitational action is proposed in this paper, which brings the topological information in the network into the universal gravity formula to measure the interaction force between two nodes, and applies the gravitational action formula to improve the fitness function in the local expansion process to obtain high-quality overlapping communities. Finally, the experiments in real and synthetic networks showed that the proposed algorithm has good performance.

Key words: community detection, overlapping community, gravitational interaction, fitness function