论文标题
喝漂白剂或现在做什么？ COVID-HERA：在Covid-19错误信息的存在下对风险信息的健康决策的研究
Drink Bleach or Do What Now? Covid-HeRA: A Study of Risk-Informed Health Decision Making in the Presence of COVID-19 Misinformation
论文作者
论文摘要
考虑到与2019年冠状病毒大流行有关的不准确的医学建议（Covid-19）的广泛传播，例如假疗法，治疗和预防建议，因此错误的信息发现已成为对研究社区的重要性和兴趣的开放问题。几项研究研究健康错误发现检测，但对错误信息的严重程度的关注很少。在这项工作中，我们将健康错误的信息构架为风险评估任务。更具体地说，我们研究了每个错误信息故事的严重性，以及读者如何看待这种严重性，即听众相信的信息可能是多么有害，以及可以使用哪种类型的信号来识别潜在的恶意假新闻并检测被驳回的索赔。为了解决我们的研究问题，我们介绍了一个新的基准数据集，并伴随着详细的数据分析。我们评估了几种传统和最先进的模型，并表明在将传统的错误信息分类模型应用于此任务时，性能存在很大差距。我们以公开挑战和未来的方向结束。
Given the widespread dissemination of inaccurate medical advice related to the 2019 coronavirus pandemic (COVID-19), such as fake remedies, treatments and prevention suggestions, misinformation detection has emerged as an open problem of high importance and interest for the research community. Several works study health misinformation detection, yet little attention has been given to the perceived severity of misinformation posts. In this work, we frame health misinformation as a risk assessment task. More specifically, we study the severity of each misinformation story and how readers perceive this severity, i.e., how harmful a message believed by the audience can be and what type of signals can be used to recognize potentially malicious fake news and detect refuted claims. To address our research questions, we introduce a new benchmark dataset, accompanied by detailed data analysis. We evaluate several traditional and state-of-the-art models and show there is a significant gap in performance when applying traditional misinformation classification models to this task. We conclude with open challenges and future directions.
