A Genetic Algorithm Based on Modularity Density for Detecting Community Structure in Complex Networks

Abstract

The problem of community structure detection in complex networks has been intensively investigated in recent years. Many algorithms were proposed based on optimization modularity. To overcome the solution limitation drawbacks of modularity function, as a new measure, modularity density for measuring the community structure was introduced. In this paper, we propose a genetic algorithm for detecting community structure in complex networks based on optimization modularity density. Experiments on synthetic and real life networks show the high capability of the method to successfully detect the network structure, particularly for the cases where the community structure is obscure.