A Swarm Intelligence Based Community Detection Algorithm in Social Networks

Abstract

A community consists of a group of dense intra-connected and sparse inter-connected actors. To detect communities in social networks have earned popularity in past few years. We have concentrated on swarm intelligence based community detection in real world networks elaborated in this paper. In computational field, there are several algorithms so far suggested to detect communities in social networks. But most of the existing algorithms take the high running time and less efficient. So, there is a need of an efficient community detection algorithm. Here, a swarm intelligence based proposed method has been elucidated to detect the communities in social networks. We have evaluated algorithm on two measures namely accuracy and Normalized Mutual Information and found that the proposed approach provides efficient results than the Girvan-Newman algorithm. Our proposed method achieves highest accuracy for College Football Network as 84% and performs better in other networks too. Also, 86% NMI score as the highest one is obtained by our proposed method for College Football Network.