The COVID-19 pandemic brought about an extraordinary rate of scientific papers on the topic that were discussed among the general public, although often in biased or misinformed ways. In this paper, we present a mixed-methods analysis aimed at examining whether public discussions were commensurate with the scientific consensus on several COVID-19 issues. We estimate scientific consensus based on samples of abstracts from preprint servers and compare against the volume of public discussions on Twitter mentioning these papers. We find that anti-consensus posts and users, though overall less numerous than pro-consensus ones, are vastly over-represented on Twitter, thus producing a false consensus effect. This transpires with favorable papers being disproportionately amplified, along with an influx of new anti-consensus user sign-ups. Finally, our content analysis highlights that anti-consensus users misrepresent scientific findings or question scientists' integrity in their efforts to substantiate their claims.

翻译：COVID-19疫情引发了关于该主题的科学论文的空前发表，公众对这些论文进行了讨论，但往往带有偏见或误导性。本文采用混合方法分析，旨在检验公众讨论是否与关于若干COVID-19问题的科学共识相符。我们基于预印本服务器上的摘要样本估计科学共识，并与推特上提及这些论文的公众讨论量进行比较。研究发现，反共识帖子和用户虽然总体数量少于支持共识的帖子和用户，但在推特上代表性过高，从而产生虚假共识效应。这一现象表现为有利论文被不成比例地放大，同时大量新的反共识用户注册加入。最后，我们的内容分析强调，反共识用户为了支持自身主张，会歪曲科学发现或质疑科学家的诚信。