Detecting communities in social networks by techniques of clustering and analysis of communications

Analysis of social networks will result in detection of communities and interactions between individuals. A community consists of nodes in which density of links is high. Most of existing methods presented for detecting communities, only consider the network's graph without bringing the topics into account. In this article a new method has been discussed which uses ontology and by applying clustering algorithms regarding the topics, clusters the network. After that, by utilization of link analysis, detects communities in each cluster. Results show that this method has a better precision in detecting communities and keeping relevant communications around one topic inside a community.