Leader-aware community detection in complex networks

Community structures are very common in complex networks. Detecting these communities is important for understanding the hidden features of networks. Besides, each community usually has one leader, which presents its significant influence over the whole community. However, most existing methods just focus on the problem of graph clustering, ignoring the role of community leaders. To solve this problem, in this paper, we propose a novel leader-aware community detection algorithm, which can find community structures as well as leaders of each community. This algorithm measures the leadership of each node and lets each one adhere to its local leader, forming dependence trees. Once all dependence trees are definitely settled, the community structures emerge because one tree actually is a cluster. Additionally, each root node of the tree is exactly the leader of corresponding community. This method can quickly determine the belonging of each node. Experimental results on real-world and benchmark networks demonstrate the effectiveness and the efficiency of our algorithm compared with other state-of-the-art approaches.