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dc.contributor.authorKousha, Kayvan
dc.contributor.authorThelwall, Michael
dc.date.accessioned2020-05-18T11:26:23Z
dc.date.available2020-05-18T11:26:23Z
dc.date.issued2020-09-04
dc.identifier.citationKousha, K. and Thelwall, M. (2020) COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts, Quantitative Science Studies 1 (3), pp. 1068-1091. DOI: 10.1162/qss_a_00066en
dc.identifier.issn2641-3337en
dc.identifier.doi10.1162/qss_a_00066
dc.identifier.urihttp://hdl.handle.net/2436/623217
dc.description© 2020 The Authors. Published by MIT Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1162/qss_a_00066en
dc.description.abstractThe COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indicators during 21 March to 18 April 2020. The rapidly increasing volume of research, is particularly accessible through Dimensions, and less through Scopus, the Web of Science, and PubMed. Google Scholar’s results included many false matches. A few COVID-19 papers from the 21,395 in Dimensions were already highly cited, with substantial news and social media attention. For this topic, in contrast to previous studies, there seems to be a high degree of convergence between articles shared in the social web and citation counts, at least in the short term. In particular, articles that are extensively tweeted on the day first indexed are likely to be highly read and relatively highly cited three weeks later. Researchers needing wide scope literature searches (rather than health focused PubMed or medRxiv searches) should start with Dimensions (or Google Scholar) and can use tweet and Mendeley reader counts as indicators of likely importance.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherMIT Pressen
dc.relation.urlhttps://www.mitpressjournals.org/doi/full/10.1162/qss_a_00066en
dc.subjectCOVID-19en
dc.subjectDimensionsen
dc.subjectGoogle Scholaren
dc.subjectaltmetricsen
dc.subjectMendeleyen
dc.subjectcitation impacten
dc.subjectScopusen
dc.subjectWeb of Scienceen
dc.subjectPubMeden
dc.titleCOVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit postsen
dc.typeJournal articleen
dc.identifier.journalQuantitative Science Studiesen
dc.date.updated2020-05-14T11:24:20Z
dc.date.accepted2020-05-14
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW18052020MTen
rioxxterms.versionVORen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2020-05-18en
dc.source.volume1
dc.source.issue3
dc.source.beginpage1063
dc.source.endpage1091
refterms.dateFCD2020-05-18T11:21:15Z
refterms.versionFCDVOR
refterms.dateFOA2020-05-18T11:26:23Z


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