Site-Effect-Based Semi-Synchronous Label Propagation Algorithm for Community Detection

The label propagation algorithm (LPA) for community detection has become prevalent due to its linear time complexity, and the number of communities does not need to be determined in advance when this algorithm is implemented. However, the results of LPA are unstable due to unavoidable randomness. A site-effect-based semi-synchronous label propagation algorithm (SE-SLPA) for community detection is proposed in this study. To deal with randomness, the algorithm divides nodes into correct communities quickly and accurately according to the three degrees of influence rule (TDIR). TDIR posits that different influence coefficients can be assigned to loops formed by nodes within three degrees, and the edge influence can be calculated to expedite label propagation and make the community structure visible. Results show that SE-SLPA improves modularity performance, normalized mutual information, stability, and iterative efficiency in community detection. This research is vital to the study of social networks.