Although there is mounting empirical evidence for the increase in affective polarization, few mechanistic models can explain its emergence at the population level. The question of how such a phenomenon can emerge from divergent opinions of a population on an ideological issue is still an open issue. In this paper, we establish that human normativity, that is, individual expression of normative opinions based on beliefs about the population, can lead to population-level polarization when ideological institutions distort beliefs in accordance with their objective of moving expressed opinion to one extreme. Using a game-theoretic model, we establish that individuals with more extreme opinions will have more extreme rhetoric and higher misperceptions about their outgroup members. Our model also shows that when social recommendation systems mediate institutional signals, we can observe the formation of different institutional communities, each with its unique community structure and characteristics. Using the model, we identify practical strategies platforms can implement, such as reducing exposure to signals from ideological institutions and a tailored approach to content moderation, both of which can rectify the affective polarization problem within its purview.

翻译：尽管越来越多的实证证据表明情感极化现象加剧，但能够解释其在群体层面产生的机制模型仍然稀少。这种基于群体对意识形态议题的异见而涌现的现象，其形成机制仍是未解之谜。本文证明：当意识形态机构为达成将表达意见推向极端的目的而扭曲信念时，人类规范性（即个体基于群体认知表达规范性意见的倾向）会导致群体层面的极化。通过博弈论模型，我们证实持有更极端意见的个体将采用更极端的修辞，并对群体外成员产生更严重的认知偏差。模型同时显示，当社交推荐系统中介制度信号时，可观察到具有独特社区结构与特征的制度群体形成。基于该模型，我们识别出平台可实施的实用策略，包括降低意识形态机构信号的曝光度以及采取差异化的内容审核方法——这两种措施均能在其职责范围内有效纠正情感极化问题。