CoAID: COVID-19 Healthcare Misinformation Dataset

• URL: http://arxiv.org/abs/2006.00885v3
• Date: Tue, 3 Nov 2020 20:37:11 GMT
• Title: CoAID: COVID-19 Healthcare Misinformation Dataset
• Authors: Limeng Cui, Dongwon Lee
• Abstract summary: CoAID includes 4,251 news, 296,000 related user engagements, 926 social platform posts about COVID-19, and ground truth labels. CoAID includes 4,251 news, 296,000 related user engagements, 926 social platform posts about COVID-19, and ground truth labels.
• Score: 12.768221316730674
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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