QCRI's COVID-19 Disinformation Detector: A System to Fight the COVID-19 Infodemic in Social Media

TL;DR

This paper presents QCRI's COVID-19 Disinformation Detector, a comprehensive system with an API and demo to identify and analyze false information related to COVID-19 on social media, aiding stakeholders in combating the infodemic.

Contribution

It introduces a multifaceted disinformation detection system with publicly available API and demo, addressing multiple aspects of COVID-19 misinformation.

Findings

System facilitates detection of COVID-19 misinformation

API and demo are publicly accessible for research and policy use

Supports multifaceted analysis of social media content

Abstract

Fighting the ongoing COVID-19 infodemic has been declared as one of the most important focus areas by the World Health Organization since the onset of the COVID-19 pandemic. While the information that is consumed and disseminated consists of promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic, at the same time there is information (e.g., containing advice, promoting cure) that can help different stakeholders such as policy-makers. Social media platforms enable the infodemic and there has been an effort to curate the content on such platforms, analyze and debunk them. While a majority of the research efforts consider one or two aspects (e.g., detecting factuality) of such information, in this study we focus on a multifaceted approach, including an API,\url{https://app.swaggerhub.com/apis/yifan2019/Tanbih/0.8.0/} and a demo system,\url{https://covid19.tanbih.org}, which we made freely and publicly available. We believe that this will facilitate researchers and different stakeholders. A screencast of the API services and demo is available.\url{https://youtu.be/zhbcSvxEKMk}