Discrete group search optimizer for community detection in social networks

Abstract

Discovering community structure in complex networks has been intensively investigated in recent years. Community detection can be treated as an optimization problem in which an objective fitness function is optimized. Intuitively, the objective fitness function captures the subgraphs in the network that has densely connected nodes with sparse connections between subgraphs. In this paper, we propose Discrete Group Search Optimizer (DGSO) which is an efficient optimization algorithm to solve the community detection problem without any prior knowledge about the number of communities. The proposed DGSO algorithm adopts the locus-based adjacency representation and several discrete operators. Experiments in real life networks show the capability of the proposed algorithm to successfully detect the structure hidden within complex networks compared with other high performance algorithms in the literature.