id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-246958-in0m5jnk	Dharawat, Arkin	Drink bleach or do what now? Covid-HeRA: A dataset for risk-informed health decision making in the presence of COVID19 misinformation	2020-10-17		.txt	text/plain	4341	240	48	In contrast with previous works that treat misinformation as a binary classification task, we build a novel health risk assessment misinformation benchmark dataset, Covid-HeRA, that contains social media posts annotated on a finer scale, based on whether the message content is: a) real news, b) inaccurate or misinformation or c) refutes/rebuts a specific claim or news article. To this end, we frame the task as a multi-class classification problem, where each social media post is categorized as: a) Real News/Claims, i.e., reliable correct information, b) Refutes/Rebuts, i.e., refutation or rebuttal of an incorrect statement, c) Not severe, i.e., misinformation but unlikely to result in risky behavioral changes or harmful decisions, d) Possibly severe misinformation, with possible severe health-related impact and e) Highly severe misinformation with increased potential risks for any individual following the advice & suggestions expressed in the social media post content.	./cache/cord-246958-in0m5jnk.txt	./txt/cord-246958-in0m5jnk.txt