A machine-learning analysis has revealed patterns in online hate speech that suggest complex—and sometimes counterintuitive—links between real-world events and different types of hate speech. Yonatan Lupu of George Washington University in Washington, D.C., and colleagues present these findings in the open-access journal PLOS ONE on January 25.
Tracking online hate speech that follows real-world events
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