Unraveling Hate Speech Amidst the COVID-19 Pandemic: Temporal Insights from the Extremist Political Board 4chan

• In Event: Racially-Motivated Extremism, Discrimination, and Other Bias Outcomes

Abstract

Amid the COVID-19 pandemic, heightened societal and scholarly concerns have emerged regarding anti-Asian, anti-Black, and anti-Semitic violence. Despite growing scholarly and public interest, it remains unclear how major events such as COVID-19 altered the prevalence and frequency of online hate crimes as well as the targeting of minority groups. The current study aims to bridge these gaps in literature. We analyze a random sample of 100,000 internet posts made between 2019 and 2021 from the popular extremist political board 4chan /pol/. Using natural language processing, these posts were classified into various categories reflecting specific types of hate crimes. Interrupted time series analysis is employed to estimate changes in trends for the frequency, prevalence, and targeting of minority groups in response to COVID-19 and other major national events. The findings demonstrate that COVID-19 resulted in a small but non-significant increase in hate speech against Asians, while anti-Black and anti-Semitic posts had larger prevalence and frequency rates compared to hate posts targeting other groups. These results suggest that COVID-19 altered trends and indicate that the amount of online hate directed towards minority groups increased during this period.

Authors

• Christopher Cassity, Florida State University

• Willis Shaw, Florida State University

• Sylwia Piatkowska, Florida State University

• Joseph Hodes, Florida State University

• Brendan Lantz, Florida State University