Testing Hypotheses From the Social Approval Theory of Online Hate: An Analysis of 110 Million Messages From Parler

We examined how social approval motivates online hate via the social approval theory, which argues social approval signals on hate messages predict (1) more hate speech, and (2) more toxicity. Using 110 million messages from Parler (2018–2021), we observed that upvotes on hate speech posts (messages broadcast on users’ profiles to followers’ feeds) predicted a lower probability of hate speech in the next immediate post but more in the following week’s posts. Additionally, upvotes on comments (messages embedded within conversational threads) negatively predicted hate speech in the next comment but positively predicted the degree of toxicity during the next week and month. Between-person effects revealed negative immediate short-term effects but positive longer-term effects for hate speech. For comments , social disapproval (downvotes) moderated these relationships, making them less positive at weekly through quarterly time-intervals and more strongly negative at 6-months. Social approval predicts online hate in time- and message-dependent ways.