GA-NET: a Genetic Algorithm for Community Detection in Social Networks

The problem of community structure detection in complex networks has been intensively investigated in recent years. In this paper we propose a genetic based approach to discover communities in social networks. The algorithm optimizes a simple but efficacious fitness function able to identify densely connected groups of nodes with sparse connections between groups. The method is efficient because the variation operators are modified to take into consideration only the actual correlations among the nodes, thus sensibly reducing the research space of possible solutions. Experiments on synthetic and real life networks show the capability of the method to successfully detect the network structure.