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A Bibliometric Analysis of COVID-19 across Science and Social Science Research Landscape

Author

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  • Aleksander Aristovnik

    (Faculty of Public Administration, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Dejan Ravšelj

    (Faculty of Public Administration, University of Ljubljana, 1000 Ljubljana, Slovenia)

  • Lan Umek

    (Faculty of Public Administration, University of Ljubljana, 1000 Ljubljana, Slovenia)

Abstract

The lack of knowledge about the COVID-19 pandemic has encouraged extensive research in the academic sphere, reflected in the exponentially growing scientific literature. While the state of COVID-19 research reveals it is currently in an early stage of developing knowledge, a comprehensive and in-depth overview is still missing. Accordingly, the paper’s main aim is to provide an extensive bibliometric analysis of COVID-19 research across the science and social science research landscape, using innovative bibliometric approaches (e.g., Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on binary logistic regression). The bibliometric analysis considers the Scopus database, including all relevant information on COVID-19 related publications ( n = 16,866) available in the first half of 2020. The empirical results indicate the domination of health sciences in terms of number of relevant publications and total citations, while physical sciences and social sciences and humanities lag behind significantly. Nevertheless, there is an evidence of COVID-19 research collaboration within and between different subject area classifications with a gradual increase in importance of non-health scientific disciplines. The findings emphasize the great need for a comprehensive and in-depth approach that considers various scientific disciplines in COVID-19 research so as to benefit not only the scientific community but evidence-based policymaking as part of efforts to properly respond to the COVID-19 pandemic.

Suggested Citation

  • Aleksander Aristovnik & Dejan Ravšelj & Lan Umek, 2020. "A Bibliometric Analysis of COVID-19 across Science and Social Science Research Landscape," Sustainability, MDPI, vol. 12(21), pages 1-30, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9132-:d:439373
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    Cited by:

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    7. Raghu Raman & Ricardo Vinuesa & Prema Nedungadi, 2021. "Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
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    15. Ryan Thomson & Rebecca Mosier & Michelle Worosz, 2023. "COVID research across the social sciences in 2020: a bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3377-3399, June.
    16. Toshiyuki Hasumi & Mei-Shiu Chiu, 2022. "Online mathematics education as bio-eco-techno process: bibliometric analysis using co-authorship and bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4631-4654, August.
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