An extended distributed learning automata based algorithm for solving the community detection problem in social networks

Due to unstoppable growth of social networks and the large number of users, the detection of communities have become one of the most popular and successful domain of research areas. Detecting communities is a significant aspect in analyzing networks because of its various applications such as sampling, link prediction and communications among members of social networks. There have been proposed many different algorithms for solving community detection problem containing optimization methods. In this paper we propose a novel algorithm based on extended distributed learning automata for solving this problem. Our proposed algorithm benefits from cooperation between learning automata to detect communities efficiently. Based on the presented experimental results, it can be concluded that our proposed algorithm outperforms to different state-of-art algorithms. To show the superiority of our proposed algorithm we compare it based on different criteria such as Modularity, Performance and Normalized Mutual Information.