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.
翻译:随着COVID-19大流行的爆发,人们转向社交媒体阅读和及时共享信息,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外,还出现了医学和政治错误以及虚假信息的新混合,这导致了第一个全球性的混乱。在与这种模式作斗争时,通常从事实角度来考虑,问题的范围要广得多,因为恶意内容不仅包括假消息、谣言和阴谋理论,而且还包括假药、恐慌、种族主义、仇外心理和当局中的不信任等。这是一个复杂的问题,需要将记者、事实检查者、决策者、政府实体、社交媒体平台和整个社会的观点结合起来,考虑到他们,我们定义了一种记号和详细的注解说明,反映这些观点。我们使用这种图案做了初步说明,我们的初步实验表明在基线上取得了显著的改进。现在,我们呼吁研究界除参与战斗外,还要支持我们的众包注努力。