Affective polarization—growing animosity and hostility between political rivals—has become increasingly characteristic of Western politics. While this phenomenon is well-documented through surveys, few studies investigate whether and how it manifests in the digital context, and what mechanisms underpin it. Drawing on social identity and intergroup theories, this study employs computational methods to explore to what extent political discussions on Reddit’s r/politics are affectively polarized, and what communicative factors shape these affective biases. Results show that interactions between ideologically opposed users were significantly more negative than like-minded ones. These interactions were also more likely to be cut short than sustained if one user referred negatively to the other’s political in-group. Conversely, crosscutting interactions in which one of the users expressed positive sentiment toward the out-group were more likely to attract a positive than a negative response, thus mitigating intergroup affective bias. Implications for the study of online political communication dynamics are discussed.

情感两极分化——政治对手之间日益增长的敌意和敌意——已经越来越成为西方政治的特征。虽然这种现象通过调查得到了充分的记录，但很少有研究调查它是否以及如何在数字环境中表现出来，以及支撑它的机制是什么。本研究借鉴社会认同和群体间理论，采用计算方法探索关于 Reddit 的r/politics 的政治讨论程度情感两极分化，以及哪些沟通因素塑造了这些情感偏见。结果表明，意识形态对立的用户之间的互动比志同道合的用户更消极。如果一个用户负面地提及另一个人的政治团体，这些互动也更有可能被缩短而不是持续。相反，其中一个用户对外群体表达积极情绪的横切互动更有可能吸引积极而非消极的反应，从而减轻群体间的情感偏见。讨论了对在线政治传播动态研究的影响。