CoAID: COVID-19 Healthcare Misinformation Dataset

TL;DR

CoAID is a comprehensive dataset comprising COVID-19 healthcare misinformation, social engagement, and platform posts, designed to aid research in detecting and understanding COVID-19 misinformation.

Contribution

The paper introduces CoAID, a large, annotated dataset with diverse COVID-19 misinformation and user engagement data for research purposes.

Findings

Dataset includes 4,251 news articles and 926 social posts.

Contains 296,000 user engagement records.

Provides ground truth labels for misinformation detection.

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.