Discovering Hidden Networks in On-line Social Networks
International Journal of Intelligent Systems and Applications
Rapid develop ments in information technology and Web 2.0 have provided a platform for the evolution of terrorist organizat ions, extremists fro m a tradit ional pyramidal structure to a technology enabled networked structure. Growing presence of these subversive groups on social networking s ites has emerged as one of the pro minent threats to the society, governments and law enforcement agencies across the world. Identifying messages relevant to the domain of security can serve as a stepping
... tone in criminal network analysis. In this paper, we deploy a ru le based approach for classifying messages in Twitter which can also successfully reveal overlapping clusters. The approach incorporates dictionaries of enriched themes where each theme is categorized by semantically related words. The message is vectorized according to the security dictionaries and is termed as ‗Security Vector'. The documents are classified in categories on the basis of security associations. Further, the approach can also be used along the temporal dimension for classifying messages into topics and rank the most pro minent topics of conversation at a particular instance of time. We further employ social network analysis techniques to visualize the hidden network at a particu lar time. So me of the results of our approach obtained through experiment with informat ion network o f Twitter are also discussed.