Optimal community detection approach based on Ant Lion Optimization

Abstract

One of the important issue in Online Social Networks (OSNs) in recent years is communities detection in such networks. Social Networks depict the interactions between individuals or entities and are represented by a graph of interconnected nodes. The vast amount of data leads to the need of analyzing such social network. Community detection problem can be represented as an optimization problem as the objective is how to divide the network to groups of nodes while the connectivity between nodes in the same group is better than connectivity with other nodes. In this research Ant Lion Optimization (ALO) has been used as effective optimization method to detect the number of communities in the networks automatically. The results show that ALO succeed to find an optimization community structure based on the quality function used.