Leveraging Social Network Analysis with Topic Models and the Semantic Web

Social Network Analysis (SNA) and Web Mining (WM) techniques are being applied to study the structures of social networks in order to manage their dynamics and predict their evolution. This paper describes how we used Semantically-Interlinked Online Communities (SIOC) ontology to represent the (latent) semantic relationships between the members of a large community forum (about 2,500), Plexilandia. We extended SIOC, taking advantage of topic-based text mining and developed data mining algorithms that used our SIOC extensions to provide a better understanding of the social dynamics of the members of the Plexilandia community. This new understanding helped us to detect and discover the key members of Plexilandia successfully.