标题： 从在线仇恨的社会认可理论检验假设：对来自Parler的11000万条帖子的分析 显示英文标题

标题： Testing Hypotheses from the Social Approval Theory of Online Hate: An Analysis of 110 Million Posts from Parler

摘要： 在本文中，我们探讨了在线仇恨行为如何受到来自他人的社会认可的驱动。我们特别检验了Walther（2024）的在线仇恨社会认可理论的两个核心观点：（H1a）对仇恨信息的社会认可信号越多，预测后续的仇恨信息越多，（H1b）随着社会认可的增加，仇恨言论信息会变得更加极端。使用来自Parler（2018-2021）超过1.1亿条帖子的数据，我们观察到，一个人在仇恨言论帖子上获得的点赞数与其下一条帖子以及接下来一周、一个月、三个月和六个月内的仇恨言论数量没有关联。跨个体效应显示，在帖子层面，社会认可与仇恨言论产生的平均关系为负，但在其他时间间隔内该关系是混合的。在线仇恨的社会认可强化机制可能在小众社交媒体平台上以不同的方式运作。 显示英文摘要

摘要： In this paper, we explored how online hate is motivated by receiving social approval from others. We specifically examined two central tenets of Walther's (2024) social approval theory of online hate: (H1a) more signals of social approval on hate messages predicts more subsequent hate messages, and (H1b) as social approval increases, hate speech messages become more extreme. Using over 110 million posts from Parler (2018-2021), we observed that the number of upvotes a person received on a hate speech post was unassociated with the amount of hate speech in their next post and posts during the next week, month, three months, and six months. Between-person effects revealed an average negative relationship between social approval and hate speech production at the post level, but this relationship was mixed at other time intervals. Social approval reinforcement mechanisms of online hate may operate differently on niche social media platforms.