ArticleAffective science2024
Changes in Online Moral Discourse About Public Figures During #MeToo.
Article in Affective science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 authors.
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Abstract
During the #MeToo movement, the perceived morality of public figures changed in light of sexual assault allegations against them. Here, we asked how these changes were influenced by the perceived severity of alleged actions and by how well-known and well-liked were the public figures. Perceived morality was assessed by measuring (im)moral language usage in 1.4 million tweets about 50 male public figures accused of sexual assault. Using natural language processing to analyze the tweets, we found that liking of public figures mitigated perceived immorality for less severe allegations, but had little effect on perceived immorality for more severe allegations. The persistence of negative perceptions 1 year later was related to liking and familiarity for the public figure, not allegation severity. These results suggest that in real-world contexts, we can forgive less harmful actions for people we like, but may not be able to if their actions are more harmful; over time, however, liking for others predicts lasting negative impressions of their moral misdeeds.
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