Hate in the Machine: Anti-Black and Anti-Muslim Social Media Posts as Predictors of Offline Racially and Religiously Aggravated Crime
| Autor: | Matthew Leighton Williams, Sefa Ozalp, Han Liu, Amir Javed, Peter Burnap |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Online and offline
Social Psychology 05 social sciences Human factors and ergonomics Poison control 050801 communication & media studies Criminology Social issues Suicide prevention Pathology and Forensic Medicine Politics 0508 media and communications Arts and Humanities (miscellaneous) 050501 criminology Computational criminology Social media Sociology Law 0505 law |
| Zdroj: | The British Journal of Criminology. |
| ISSN: | 1464-3529 0007-0955 |
| DOI: | 10.1093/bjc/azz049 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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