The COVID-19 crisis has revealed structural failures in governance and coordination on a global scale. With related policy interventions dependent on verifiable evidence, pandemics require governments to not only consider the input of experts but also ensure that science is translated for public understanding. However, misinformation and fake news, including content shared through social media, compromise the efficacy of evidence-based policy interventions and undermine the credibility of scientific expertise with potentially longer-term consequences. We introduce a formal mathematical model to understand factors influencing the behavior of social media users when encountering fake news. The model illustrates that direct efforts by social media platforms and governments, along with informal pressure from social networks, can reduce the likelihood that users who encounter fake news embrace and further circulate it. This study has implications at a practical level for crisis response in politically fractious settings and at a theoretical level for research about post-truth and the construction of fact.

中文翻译：

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在 COVID-19 时代打击假新闻：来自均衡模型的政策见解

COVID-19 危机揭示了全球范围内治理和协调的结构性失败。由于相关政策干预依赖于可验证的证据，大流行病要求政府不仅要考虑专家的意见，还要确保将科学转化为公众理解。然而，错误信息和假新闻，包括通过社交媒体分享的内容，会损害循证政策干预的有效性，并破坏科学专业知识的可信度，并可能产生长期后果。我们引入了一个正式的数学模型来了解影响社交媒体用户在遇到假新闻时的行为的因素。该模型表明，社交媒体平台和政府的直接努力，以及来自社交网络的非正式压力，可以减少遇到假新闻的用户接受并进一步传播的可能性。这项研究在实践层面对政治动荡环境中的危机应对以及对后真相和事实建构的研究具有理论层面的意义。