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Covid-19 publications: Database coverage, citations, readers, tweets, news, facebook walls, reddit posts
Quantitative Science Studies ; 1(3):1068-1091, 2020.
Article in English | Scopus | ID: covidwho-1495769
ABSTRACT
The 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 identify important new studies quickly. In response, this paper assesses the coverage of scholarly databases and impact indicators during March 21, 2020 to April 18, 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 3 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. © 2020 Kayvan Kousha and Mike Thelwall. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Quantitative Science Studies Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Quantitative Science Studies Year: 2020 Document Type: Article