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A Meta-Analysis of Scholarly Research on Corona virus through Big Data Approach

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  • Panda, Subhajit

    (Chandigarh University)

Abstract

The purpose of the study is to examine the status of scholarly literature on Corona virus indexed in the big database, the Lens, taking into account, top-cited articles, top contributors, top active country region, most accepted study field and open access status. Relative growth rate (RGR) and Doubling time (Dt) calculation is also a major reflects of the paper. The study analyzes the status of scholarly publications on Corona virus research as indexed by Lens spanning a period from the oldest record until July 15, 2020. “Structured Search” was made under “New Scholar Search” using the term “Corona virus” and restrict the search result only for “Journal Article”. Results obtained were imported through email (.csv file) for further analysis and visualization using spreadsheet software. The results of the study show that out of total 26628 scholarly outputs 2109 are cited in a patent while 15963 in another scholarly literature. “The University of Hong Kong” is the most productive university with 412 scholarly literature, “The United States” as a most contributing country provides 8433 publications, “Journal of Virology” is the most contributing journal with 1012 publications, “Kwok-Yung Yuen” contributed maximum as an individual author and “Elsevier” as a top journal publisher. Among the Lens indexed scholarly publications on Corona virus, 64.04% obtained open accessibility in terms of open access colour while 64.09% under an open-access. No previous study could be identified dealing with such meta-analysis using the Lens database.

Suggested Citation

  • Panda, Subhajit, 2020. "A Meta-Analysis of Scholarly Research on Corona virus through Big Data Approach," SocArXiv tkbc2, Center for Open Science.
    • Handle: RePEc:osf:socarx:tkbc2
    DOI: 10.31219/osf.io/tkbc2
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