The rise of misinformation and fake news in online political discourse poses significant challenges to democratic processes and public engagement. While debunking efforts aim to counteract misinformation and foster fact-based dialogue, these discussions often involve language toxicity and emotional polarization. We examined over 86 million debunking tweets and more than 4 million Reddit debunking comments to investigate the relationship between language toxicity, pessimism, and social polarization in debunking efforts. Focusing on discussions of the 2016 and 2020 U.S. presidential elections and the QAnon conspiracy theory, our analysis reveals three key findings: (1) peripheral participants (1-degree users) play a disproportionate role in shaping toxic discourse, driven by lower community accountability and emotional expression; (2) platform mechanisms significantly influence polarization, with Twitter amplifying partisan differences and Reddit fostering higher overall toxicity due to its structured, community-driven interactions; and (3) a negative correlation exists between language toxicity and pessimism, with increased interaction reducing toxicity, especially on Reddit. We show that platform architecture affects informational complexity of user interactions, with Twitter promoting concentrated, uniform discourse and Reddit encouraging diverse, complex communication. Our findings highlight the importance of user engagement patterns, platform dynamics, and emotional expressions in shaping polarization in debunking discourse. This study offers insights for policymakers and platform designers to mitigate harmful effects and promote healthier online discussions, with implications for understanding misinformation, hate speech, and political polarization in digital environments.

翻译：在线政治讨论中错误信息和虚假新闻的兴起对民主进程和公众参与构成了重大挑战。尽管辟谣努力旨在对抗错误信息并促进基于事实的对话，但这些讨论常常涉及语言毒性和情感极化。我们分析了超过8600万条辟谣推文和400多万条Reddit辟谣评论，以研究辟谣工作中语言毒性、悲观情绪和社会极化之间的关系。聚焦2016年和2020年美国总统选举以及QAnon阴谋论的讨论，我们的分析揭示了三个关键发现：(1) 边缘参与者（一度用户）在塑造毒性话语中发挥着不成比例的作用，这源于较低的社区责任感和情感表达；(2) 平台机制显著影响极化，Twitter放大了党派差异，而Reddit由于其结构化、社区驱动的互动导致了更高的整体毒性；(3) 语言毒性与悲观情绪之间存在负相关，增加的互动减少了毒性，尤其是在Reddit上。我们表明平台架构影响用户互动的信息复杂性，Twitter促进集中、统一的话语，而Reddit鼓励多样、复杂的交流。我们的研究结果突显了用户参与模式、平台动态和情感表达在塑造辟谣话语极化中的重要性。这项研究为政策制定者和平台设计者提供了见解，以减轻有害影响并促进更健康的在线讨论，对于理解数字环境中的错误信息、仇恨言论和政治极化具有重要意义。