CoAID: COVID-19 Healthcare Misinformation Dataset

May 22, 2020 · Entered Twilight · 🏛 arXiv.org

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Repo contents: 05-01-2020, 07-01-2020, 09-01-2020, 11-01-2020, README.md

Authors Limeng Cui, Dongwon Lee arXiv ID 2006.00885 Category cs.SI: Social & Info Networks Cross-listed cs.CL Citations 268 Venue arXiv.org Repository https://github.com/cuilimeng/CoAID ⭐ 113 Last Checked 1 month ago

Abstract

As the COVID-19 virus quickly spreads around the world, unfortunately, misinformation related to COVID-19 also gets created and spreads like wild fire. Such misinformation has caused confusion among people, disruptions in society, and even deadly consequences in health problems. To be able to understand, detect, and mitigate such COVID-19 misinformation, therefore, has not only deep intellectual values but also huge societal impacts. To help researchers combat COVID-19 health misinformation, therefore, we present CoAID (Covid-19 heAlthcare mIsinformation Dataset), with diverse COVID-19 healthcare misinformation, including fake news on websites and social platforms, along with users' social engagement about such news. CoAID includes 4,251 news, 296,000 related user engagements, 926 social platform posts about COVID-19, and ground truth labels. The dataset is available at: https://github.com/cuilimeng/CoAID.