在社交媒体上对抗COVID-19信息流行病：整体视角和武装号召
Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms
摘要：
随着COVID-19大流行的爆发，人们转向社交媒体阅读和分享及时的信息，包括统计数据、警告、建议和鼓舞人心的故事。不幸的是，除了所有这些有用的信息，还有一种新的医疗和政治错误信息和虚假信息的混合，这导致了第一次全球信息流行病。虽然打击这种信息流行病通常被认为是真实的，但问题要广泛得多，因为恶意内容不仅包括假新闻，谣言和阴谋论，还包括宣传假治疗，恐慌，种族主义，仇外心理和对当局的不信任等。这是一个复杂的问题，需要采取综合方法，将记者、事实核查人员、政策制定者、政府实体、社交媒体平台和整个社会的观点结合起来。考虑到这些，我们定义了一个注释模式和详细的注释说明，反映了这些观点。我们使用这个模式执行了初始注释，我们的初始实验证明了与基线相比有相当大的改进。现在，我们向研究界和其他人发出号召，通过支持我们的众包注释工作来加入战斗。
英文摘要：
With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories. Unfortunately, alongside all this useful information, there was also a new blending of medical and political misinformation and disinformation, which gave rise to the first global infodemic. While fighting this infodemic is typically thought of in terms of factuality, the problem is much broader as malicious content includes not only fake news, rumors, and conspiracy theories, but also promotion of fake cures, panic, racism, xenophobia, and mistrust in the authorities, among others. This is a complex problem that needs a holistic approach combining the perspectives of journalists, fact-checkers, policymakers, government entities, social media platforms, and society as a whole. Taking them into account we define an annotation schema and detailed annotation instructions, which reflect these perspectives. We performed initial annotations using this schema, and our initial experiments demonstrated sizable improvements over the baselines. Now, we issue a call to arms to the research community and beyond to join the fight by supporting our crowdsourcing annotation efforts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
