Moralized language predicts hate speech on social media.

ABSTRACT: Hate speech on social media threatens the mental health of its victims and poses severe safety risks to modern societies. Yet, the mechanisms underlying its proliferation, though critical, have remained largely unresolved. In this work, we hypothesize that moralized language predicts the proliferation of hate speech on social media. To test this hypothesis, we collected three datasets consisting of N = 691,234 social media posts and ∼35.5 million corresponding replies from Twitter that have been authored by societal leaders across three domains (politics, news media, and activism). Subsequently, we used textual analysis and machine learning to analyze whether moralized language carried in source tweets is linked to differences in the prevalence of hate speech in the correspon

SUBMITTER: Solovev K 

PROVIDER: S-EPMC9837664 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature