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arXiv · 2204.03506

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

Preslav Nakov·Firoj Alam·Yifan Zhang·Animesh Prakash·Fahim Dalvi
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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}

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Preslav Nakov, Firoj Alam, Yifan Zhang, Animesh Prakash, Fahim Dalvi. 2022-03-08. QCRI's COVID-19 Disinformation Detector: A System to Fight the COVID-19 Infodemic in Social Media. https://arxiv.org/abs/2204.03506

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