Abstract
The study of social networks has gained much interest from the research community in recent years. Most of the existing algorithms proposed for communities determination are based on the topological features of social networks. In this paper, we propose a new objective function where we incorporate the value of structure and semantic similarity and a bees colonies algorithm to optimize our objective function. We show that our approach provides more meaningful communities than conventional methods that consider only relationship information.