分析1.1亿条推特数据，发现点赞会短期抑制仇恨，长期助长仇恨。
Testing Hypotheses from the Social Approval Theory of Online Hate: An Analysis of 110 Million Messages from Parler
- 通过分析推特平台1.1亿条消息，检验社会认可理论对网络仇恨的影响。
- 点赞使仇恨言论短期减少，但一周后反而增加；评论点赞则提升长期毒性。
- 评论区的点踩能削弱长期负面影响，适合研究网络暴力与社区治理者。
我们基于社会认可理论，考察了社交认可如何驱动网络仇恨。利用2018至2021年来自Parler的1.1亿条消息，发现仇恨言论帖的点赞数在下一条即时帖子中降低仇恨概率，但在接下来的一周内却增加仇恨。对于评论（嵌入对话线程中的消息），点赞在下一评论中负向预测仇恨言论，但在后续一周和一月内正向预测毒性。跨个体效应显示，仇恨言论也呈现短期抑制、长期促进的模式。对于评论，社会否定（点踩）调节了这些关系，在周至季度时间尺度上减弱其正向影响，并在六个月时增强负向效应。社会认可以时间和消息类型依赖的方式预测网络仇恨。
原文摘要 · Abstract (English)
We examined how social approval motivates online hate via the social approval theory, which argues social approval signals on hate messages predict more hate and toxicity. Using 110 million messages from Parler (2018-2021), we observed that upvotes on hate speech posts (e.g., messages broadcast on users' profiles to followers' feeds) predicted a lower probability of hate in the next immediate post but more in the following week's post. In other analyses, upvotes on comments (e.g., messages embedded within conversational threads) negatively predicted hate speech in the next comment but positively predicted toxicity during the next week and month. Between-person effects revealed a similar pattern of 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 six-months. Social approval predicts online hate in time- and message-dependent ways.
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