A Multi-agent Homophily-Based Approach for Community Detection in Social Networks

In this paper, we propose an agent-based approach for modeling dynamic connections in social networks. The key contribution of our work is the definition of a similarity measure for computing the strength of relationships between the social network members. For this purpose, we take into consideration the members' properties, the topological structure of the network and information about the interchange between each connected pair. To well choose the properties of social members, we use the concept of homophily. We show that our approach improves the effectiveness of the community detection process.