AGGLOMERATIVE CLUSTERING BASED ON LABEL PROPAGATION FOR DETECTING OVERLAPPING AND HIERARCHICAL COMMUNITIES IN COMPLEX NETWORKS

Community detection is an important issue to understand the structural and functional properties of complex networks, which still remains a challenging subject. In some complex networks, a node may belong to multiple communities, implying overlapping community structure. Moreover, complex networks often show a hierarchical structure where small communities group together to form larger ones. In this paper, we propose a novel parameter-free algorithm called agglomerative clustering based on label propagation algorithm (ACLPA) to detect both overlapping and hierarchical community structure in complex networks. By combining the advantages of agglomerative clustering and label propagation, our algorithm can build the hierarchical tree of overlapping communities in large-scale networks. The tests on both synthetic and real-world networks give excellent results and demonstrate the effectiveness and efficiency of our algorithm.