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What Country, University, or Research Institute, Performed the Best on Covid-19 During the First Wave of the Pandemic?

Author

Listed:
  • Petar Radanliev

    (University of Oxford)

  • David Roure

    (University of Oxford)

  • Rob Walton

    (University of Oxford)

  • Max Kleek

    (University of Oxford)

  • Omar Santos

    (Cisco Research Centre)

  • La’Treall Maddox

    (Cisco Research Centre)

Abstract

In this article, we conduct data mining and statistical analysis on the most effective countries, universities, and companies, based on their output (e.g., produced or collaborated) on COVID-19 during the first wave of the pandemic. Hence, the focus of this article is on the first wave of the pandemic. While in later stages of the pandemic, US and UK performed best in terms of vaccine production, the focus in this article is on the initial few months of the pandemic. The article presents findings from our analysing of all available records on COVID-19 from the Web of Science Core Collection. The results are compared with all available data records on pandemics and epidemics from 1900 to 2020. This has created interesting findings that are presented in the article with visualisation tools.

Suggested Citation

  • Petar Radanliev & David Roure & Rob Walton & Max Kleek & Omar Santos & La’Treall Maddox, 2022. "What Country, University, or Research Institute, Performed the Best on Covid-19 During the First Wave of the Pandemic?," Annals of Data Science, Springer, vol. 9(5), pages 1049-1067, October.
  • Handle: RePEc:spr:aodasc:v:9:y:2022:i:5:d:10.1007_s40745-022-00406-8
    DOI: 10.1007/s40745-022-00406-8
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    References listed on IDEAS

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    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Gwo-Jen Hwang & Yun-Fang Tu, 2021. "Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    3. Aman Khakharia & Vruddhi Shah & Sankalp Jain & Jash Shah & Amanshu Tiwari & Prathamesh Daphal & Mahesh Warang & Ninad Mehendale, 2021. "Outbreak Prediction of COVID-19 for Dense and Populated Countries Using Machine Learning," Annals of Data Science, Springer, vol. 8(1), pages 1-19, March.
    4. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
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