A New Follow based Community Detection Algorithm

Nowadays, social networks have gained a lot of popularity among people. With the growth of these networks and a large number of people using these networks, social network analysis has received special attention, so the need for highly accurate and fast algorithms on various issues is strongly felt. One of the important issues in these networks is community detection problem that many algorithms have been proposed for this purpose. In social networks, communities usually are formed around popular or influential nodes. Most algorithms in this field, that are usually density-based, are unable to detect this structure. In this paper, we propose a new community detection algorithm based on the local popularity structure. In this algorithm, the most popular person in neighborhood of each user is selected as a leader and the user falls into that group. Experimental results on six real networks show that the proposed method not only has comparable results in terms of NMI and ARI, but also has shorter execution time compared to existing algorithms.