The increasing complexity and emergence of Web 2.0 applications have paved way for threats arising out of the use of social networks by cyber extremists (Radical groups). Radicalization (also called cyber extremism and cyber hate propaganda) is a growing concern to the society and also of great pertinence to governments & law enforcement agencies all across the world. Further, the dynamism of these groups adds another level of complexity in the domain, as with time, one may witness a change in members of the group and hence has motivated many researchers towards this field. This proposal presents an investigative data mining approach for detecting the dynamic behavior of these radical groups in online social networks by textual analysis of the messages posted by the members of these groups along with the application of techniques used in social network analysis. Some of the preliminary results obtained through partial implementation of the approach are also discussed.