HCC: Small: Assessing Radicalization and Deradicalization Online

University Of Maryland, College Park, College Park MD

Investigators

Abstract

This research will develop a foundation for measuring radicalization and, importantly, deradicalization, in online communities by tracking individual behavioral trends over time and at scale, and identifying patterns among members who disengage from the subculture they had earlier joined in a process of radicalization, but had begun to deradicalize. Online extremism and radicalization has been a growing concern and active area of research. There is a broad body of cross-disciplinary work studying online extremist groups but limited computational and data science-based research on the deradicalization process. The primary empirical research will analyze a recently-collected large corpus of over 8 million online forum posts, including comprehensive archives of five popular forums related to one extremist subculture. The practical implications of this work have potential to benefit the well-being of society, both online and offline, and to bolster national security. This work includes five core projects: (1) Detecting Radicalization will build a formal lexicon of subcultural language, a signal of belonging in the group, and build a suite of tools to detect hate speech among members. (2) Detecting Radicalization will analyze trends of language use per user to find patterns and conduct content analysis to identify markers of radicalization. (3) Social Incentives will study social interaction and its relationship with radicalization to understand the applicability of theories that connect social incentives and genuine beliefs. (4) Detecting Deradicalization will identify markers of deradicalization among members who disengage from forums and those who turn to support groups for members who are trying to leave the community. (5) Classifying Deradicalization will build machine-learning models to automatically identify members who may be considering deradicalization. The models and lexicons developed in this research will provide methods for understanding the social and normative dynamics of extremist groups and subcultures more broadly. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.