2024/02/13 by Catie Snow Bailard, Rebekah Tromble, Wei Zhong +3 · 1 voice · 2 citations
Social Sciences · Computer Science · #Social Media and Politics #Hate Speech and Cyberbullying Detection #Terrorism, Counterterrorism, and Political Violence
paper · pdf · doi:10.1017/s0003055423001478
openalex publication_date 2024/02/13 · openalex created_date 2024/02/14 · openalex updated_date 2026/06/16
This study examines the relationship between online communication by the Proud Boys and their offline activities. We use a supervised machine learning model to analyze a novel dataset of Proud Boys Telegram messages, merged with US Crisis Monitor data of violent and nonviolent events in which group members participated over a 31-month period. Our analysis finds that intensifying expressions of grievances online predict participation in offline violence, whereas motivational appeals to group pride, morale, or solidarity share a reciprocal relationship with participation in offline events. This suggests a potential online messaging–offline action cycle, in which (a) nonviolent offline protests predict an increasing proportion of motivational messaging and (b) increases in the frequency and proportion of motivational appeals online, in turn, predict subsequent violent offline activities. Our findings offer useful theoretical insights for understanding the relationship between online speech and offline behavior.