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The issue of detecting large communities in online social networks is the subject of a wide range of studies in order to explore the network sub-structure. Most of the existing studies are concerned with network topology with no emphasis on active communities among the large online social networks and social portals, which are not based on network topology like forums. Here, new semantic community detection is proposed by focusing on user attributes instead of network topology. In the proposed approach, a network of user activities is established and weighted through semantic data. Furthermore, consistent extended label propagation algorithm is presented. Doing so, semantic representations of active communities are refined and labelled with user-generated tags that are available in web.2. The results show that the proposed semantic algorithm is able to significantly improve the modularity compared with three previously proposed algorithms.

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