A Dashboard for Mitigating the COVID-19 Misinfodemic
A Dashboard for Mitigating the COVID-19 Misinfodemic
复制标题
DOI：
10.18653/v1/2021.eacl-demos.12
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Zhengyuan Zhu;Kevin Meng;Josue Caraballo;Israa Jaradat;Xiao Shi;Zeyu Zhang;F. Akrami;Haojin Liao;Fatma Arslan;Damian Jimenez;Mohanmmed Samiul Saeef;P. Pathak;Chengkai Li
中科院分区：
文献类型：
--
作者：
Zhengyuan Zhu;Kevin Meng;Josue Caraballo;Israa Jaradat;Xiao Shi;Zeyu Zhang;F. Akrami;Haojin Liao;Fatma Arslan;Damian Jimenez;Mohanmmed Samiul Saeef;P. Pathak;Chengkai Li
本文描述了我们正在进行的项目中目前取得的里程碑，该项目旨在了解对Twitter上的COVID-19错误信息传播的监测、影响和干预。具体来说，它引入了一个公共仪表板，除了在交互式地图和导航面板中显示病例数外，还提供了一些其他地方没有的独特功能。特别是，仪表板使用了与COVID-19相关的事实和错误信息的编排目录，并显示了用户选择的美国地理区域的Twitter用户中最流行的目录信息。本文解释了如何使用BERT模型将tweet与事实和错误信息相匹配，并检测他们对这些信息的立场。本文还讨论了错误信息时空传播分析的初步实验结果。
This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter. Specifically, it introduces a public dashboard which, in addition to displaying case counts in an interactive map and a navigational panel, also provides some unique features not found in other places. Particularly, the dashboard uses a curated catalog of COVID-19 related facts and debunks of misinformation, and it displays the most prevalent information from the catalog among Twitter users in user-selected U.S. geographic regions. The paper explains how to use BERT models to match tweets with the facts and misinformation and to detect their stance towards such information. The paper also discusses the results of preliminary experiments on analyzing the spatio-temporal spread of misinformation.