Detection of cyber terrorist communities and topic mining of tweets

Social media, while flourishing, has also become a vital tool exploited by various terrorist forces. To analyze and study information related to terrorism on social networks, we propose a model framework that combines complex networks with natural language processing. This framework aims to explore influential key users, community structures, and communication topics within terrorism-related communities. Using a dataset of ISIS jihadist-related tweets from Twitter between 2014 and 2016, we construct an extremist network and employ centrality measures in the framework to identify important influential members. Additionally, the framework employs the ASOCCA community detection algorithm to reveal community structures and utilizes NMF topic modeling to extract topics from tweets and determine the focus of each important member. This approach enhances the capability for monitoring, identifying, disrupting, and tracking online terrorist activities.