RT Article
T1 Hate in the Machine: Anti-Black and Anti-Muslim Social Media Posts as Predictors of Offline Racially and Religiously Aggravated Crime
JF The British journal of criminology
VO 60
IS 1
SP 93
OP 117
A1 Williams, Matthew L. 1976-
A2 Burnap, Pete
A2 Javed, Amir
LA English
YR 2020
UL https://krimdok.uni-tuebingen.de/Record/1687561400
AB National governments now recognize online hate speech as a pernicious social problem. In the wake of political votes and terror attacks, hate incidents online and offline are known to peak in tandem. This article examines whether an association exists between both forms of hate, independent of ‘trigger' events. Using Computational Criminology that draws on data science methods, we link police crime, census and Twitter data to establish a temporal and spatial association between online hate speech that targets race and religion, and offline racially and religiously aggravated crimes in London over an eight-month period. The findings renew our understanding of hate crime as a process, rather than as a discrete event, for the digital age.
K1 Hate speech
K1 Hate crime
K1 Social media
K1 Predictive policing
K1 Big data
K1 Far right
DO 10.1093/bjc/azz049