A Cultural Algorithm Based on Artificial Bee Colony Optimization for Community Detection in Signed Social Networks

In this paper, we propose a cultural algorithm for detecting communities in signed networks based on artificial bee colony optimization, which is a process of dual inheritance from both a micro-evolutionary level and a macro-evolutionary level. We define the population space and belief space of the algorithm which are fit for community detection problem in signed social networks. To validate the performance of the algorithm we make experiments on two real-world networks and comparative experiments with three existing detecting algorithms on synthetic networks. The experimental results show that our algorithm gets a good performance on real-world networks and outperforms other algorithms on most of synthetic networks.