Arana-Catania, Miguel, Kochkina, Elena, Zubiaga, Arkaitz, Liakata, Maria, Procter, Rob and He, Yulan (2022) PANACEA dataset - Heterogeneous COVID-19 Claims. [Dataset]

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Item Type:	Dataset
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RA Public aspects of medicine
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH):	COVID-19 Pandemic, 2020- , Natural language processing (Computer science), Neural networks (Computer science), Computational linguistics
Publisher:	University of Warwick, Department of Computer Science
Official Date:	9 May 2022
Dates:	Date Event 9 May 2022 Created
Status:	Not Peer Reviewed
Publication Status:	Published
Media of Output (format):	.csv
Access rights to Published version:	Open Access
Copyright Holders:	University of Warwick
Description:	This dataset contains a heterogeneous set of True and False COVID claims and online sources of information for each claim.
RIOXX Funder/Project Grant:	Project/Grant ID RIOXX Funder Name Funder ID EP/V048597/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266 EP/T017112/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266 EP/V030302/1 UK Research and Innovation http://dx.doi.org/10.13039/100014013 EP/V020579/1 UK Research and Innovation http://dx.doi.org/10.13039/100014013
Related URLs:	Related item in WRAP Other
Contributors:	Contribution Name Contributor ID Depositor Arana-Catania, M. 100726

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