How to Improve Group Homogeneity in Online Social Networks

摘要: The formation and evolution of interest groups in Online Social Networks is driven by both the users’ preferences choices groups’ administrators. In this context, notion homogeneity a social group crucial: it accounts for determining mutual similarity among members it’s often regarded as fundamental to determine satisfaction members. paper we propose measure that takes into account behavioral information users, an algorithm optimize such network scenario matching users profiles. We provide advantageous formulation framework means fully-distributed multi-agent system. Experiments on simulated data clearly highlight performance improvement brought our approach.