A recursive methodology for radical communities’ detection on social networks

Abstract

Abstract In the recent years, radical communities have become very aware of the enormous impact of social networks around the world. Thus, these latter are being frequently explored by these groups. Therefore, penetrating into these communities by analyzing both their interactions and their shared content is a considerably challenging task that serves to counter the online radicalization. For this purpose, in this paper, we propose a new recursive methodology for radical communities’ detection on social networks based on the analysis and extraction of their violent used vocabulary. Our methodology consists mainly on extracting recursively a set of dangerous profiles from Twitter based on their suspicious interactions. Then, we analyze their textual shared data in order to construct a rich glossary containing their violent used vocabulary. This glossary is exploited and enriched to detect recursively radical communities. Finally, in order to evaluate the performance of our methodology, we resort to an expert who verifies both the list of the dangerous extracted profiles and the violent constructed glossary. The given results show the effectiveness and efficiency of our method.