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PANACEA dataset - Heterogeneous COVID-19 Claims
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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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Official URL: https://doi.org/10.5281/zenodo.6493847
| Item Type: | Dataset | |||||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RA Public aspects of medicine |
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| 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 | |||||||||||||||
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| Status: | Not Peer Reviewed | |||||||||||||||
| Publication Status: | Published | |||||||||||||||
| Media of Output (format): | .csv | |||||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
| 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. |
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