arXiv (Cornell University) · 2020 · 184 citations · 16 references
Social SciencesHealth InformaticsEpidemiologyHealth CommunicationSocial Media AnalyticsDisinformationMisinformation DetectionSocial MediaFake News AnalysisGround Truth ConstructionGround Truth LabelingGround-truth ValidationMisinformation MitigationMisinformation PropagationSocial Engagement ModelingSocial Media Platforms
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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Stephen A. Lauer, Kyra H. Grantz, Qifang Bi et al. · Annals of Internal Medicine · 2020 · 6.6K citations · Full text
Veterinary Medicine, Infectious Disease Control, Infectious Diseases +17
Distributed Representations of Sentences and Documents
Quoc V. Le, Tomáš Mikolov · arXiv (Cornell University) · 2014 · 5.1K citations · Full text
Yaqing Wang, Fenglong Ma, Zhiwei Jin et al. · 2018 · 1.1K citations · Full text