Political polarization remains perhaps the “greatest barrier” to effective COVID-19 pandemic mitigation measures in the United States. Social media has been implicated in fueling this polarization. In this paper, we uncover the network of COVID-19 related news sources shared to 30 politically biased and 2 neutral subcommunities on Reddit. We find, using exponential random graph modeling, that news sources associated with highly toxic – “rude, disrespectful” – content are more likely to be shared across political subreddits. We also find homophily according to toxicity levels in the network of online news sources. Our findings suggest that news sources associated with high toxicity are rewarded with prominent positions in the resultant network. The toxicity in COVID-19 discussions may fuel political polarization by denigrating ideological opponents and politicizing responses to the COVID-19 pandemic, all to the detriment of mitigation measures. Public health practitioners should monitor toxicity in public online discussions to familiarize themselves with emerging political arguments that threaten adherence to public health crises management. We also recommend, based on our findings, that social media platforms algorithmically promote neutral and scientific news sources to reduce toxic discussion in subcommunities and encourage compliance with public health recommendations in the fight against COVID-19.

政治两极分化可能仍然是美国有效缓解 COVID-19 大流行病措施的“最大障碍”。社交媒体助长了这种两极分化。在本文中，我们发现了与 COVID-19 相关的新闻来源网络共享给 Reddit 上的 30 个有政治偏见的子社区和 2 个中立的子社区。我们发现，使用指数随机图建模，与剧毒（“粗鲁、无礼”）内容相关的新闻来源更有可能在政治子版块之间共享。我们还根据在线新闻来源网络中的毒性水平发现了同质性。我们的研究结果表明，与高毒性相关的新闻来源在由此产生的网络中占据突出位置。COVID-19 讨论中的毒性可能会通过诋毁意识形态对手并将对 COVID-19 大流行的反应政治化来加剧政治两极分化，所有这些都会损害缓解措施。公共卫生从业人员应监测公共在线讨论中的毒性，以熟悉威胁遵守公共卫生危机管理的新兴政治论点。根据我们的发现，我们还建议社交媒体平台通过算法推广中立和科学的新闻来源，以减少子社区中的有害讨论，并鼓励在抗击 COVID-19 的过程中遵守公共卫生建议。公共卫生从业人员应监测公共在线讨论中的毒性，以熟悉威胁遵守公共卫生危机管理的新兴政治论点。根据我们的发现，我们还建议社交媒体平台通过算法推广中立和科学的新闻来源，以减少子社区中的有害讨论，并鼓励在抗击 COVID-19 的过程中遵守公共卫生建议。公共卫生从业人员应监测公共在线讨论中的毒性，以熟悉威胁遵守公共卫生危机管理的新兴政治论点。根据我们的发现，我们还建议社交媒体平台通过算法推广中立和科学的新闻来源，以减少子社区中的有害讨论，并鼓励在抗击 COVID-19 的过程中遵守公共卫生建议。