Joanne T. Barros

ABSTRACT The rise in extremist violence is a global concern, prompting advancements in threat assessment. This study applies machine learning to dissect publicly available texts from violent attackers with white supremacist, incel, and political extremist ideologies, as well as from those driven by personal grievances. Through natural language processing, the research identifies specific linguistic patterns and themes inherent to each group and explores the intersections among them.

1 INTRODUCTION Over the past few decades, the expectations and scope of police departments worldwide have undergone a profound transformation to effectively respond to the evolving needs of society, with a focus on fair and equitable responses to cases involving behavioural and/or mental health crises (Paterson & Pollock, 2016).