A Hierarchical Multi-label Propagation Algorithm for Overlapping Community Discovery in Social Networks

Multi-label propagation algorithms (MLPAs) have nearly linear time complexity, but the accuracy and stability still need to be improved when applied to overlapping community discovery. Inspired from the idea that boundary nodes are more probable to appear in the overlapping regions of different communities, a Hierarchical Multi-label Propagation Algorithm (HMPA) based on node hierarchy and label propagation gain for overlapping community discovery in social networks is proposed in this paper. HMPA consists of three stages. Firstly, HMPA utilizes LPAm to unfold initial non-overlapping communities. Secondly, a PageRank-like method is proposed to mark the hierarchy of each node according to the initial partition of the first stage. Finally, multi-label propagation algorithm considering label propagation gain between nodes, which is calculated based on node hierarchy, is introduced to refine overlapping region. Experimental results on both the synthetic and real world networks show that the proposed algorithm can effectively solve the problems of traditional multi-label propagation algorithms in terms of accuracy and stability.