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Evaluation of the Dynamics of Large Scale COVID-19 Related Literature through Bibliometric Analysis from a Mathematical Standpoint

1,2★, 3, 4, 3, 5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 6, 2,3, 7, 1, 1, 1, 1, 1, 2, 8★ Corresponding author

  1. 1Apollo Multispeciality Hospitals, Kolkata, West Bengal, INDIA.
  2. 2GLA University, Mathura, Uttar Pradesh, INDIA.
  3. 3Manipal Hospitals, Dwarka, New Delhi, INDIA.
  4. 4International Institute of Information Technology, Hyderabad, Telangana, INDIA.
  5. 5Apollo Proton Cancer Center, Chennai, Tamilnadu, INDIA.
  6. 6Patient Information Centre, Kolkata, West Bengal, INDIA.
  7. 7Fortis Memorial Research Institute, Gurgaon Haryana, INDIA.
  8. 8Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, INDIA.

CORRESPONDENCE

Biplab Sarkar

Apollo Multispeciality Hospitals, Kolkata, West Bengal, INDIA.

biplabphy@gmail.com

Received: 30-05-2021; Revised: 19-12-2021; Accepted: 20-06-2022.

Volume 11, Issue 1 · pp. 47-54 · 2022 · DOI: 10.5530/jscires.11.1.5

ABSTRACT

This study aims to analyze the dynamics of the published articles and preprints of Covid-19 related literature from different scientific databases and sharing platforms. The PubMed, ScienceDirect, and ResearchGate (RG) databases were under consideration in this study over a specific time. Analyses were carried out on the number of publications as (a) function of time (day), (b) journals and (c) authors. Doubling time of the number of publications was analyzed for PubMed “all articles” and ScienceDirect published articles. Analyzed databases were (1A) PubMed (01/12/2019-12/06/2020) “all_articles” (1B) PubMed Review articles) and (1C) PubMed Clinical Trials (2) ScienceDirect all publications (01/12/2019- 25/05/2020) (3) RG (Article, Pre Print, Technical Report) (15/04/2020 – 30/4/2020). Total publications in the observation period for PubMed, ScienceDirect, and RG were 23000, 5898 and 5393 respectively. The average number of publications/day for PubMed, ScienceDirect and RG were 70.0 ±128.6, 77.6±125.3 and 255.6±205.8 respectively. PubMed shows an avalanche in the number of publications around May 10, the number of publications jumped from 6.0±8.4/day to 282.5±110.3/ day. The average doubling time for PubMed, ScienceDirect, and RG was 10.3±4 days, 20.6 days, and 2.3±2.0 days respectively. The average number of publications per author for PubMed, ScienceDirect, and RG was 1.2±1.4, 1.3±0.9, and 1.1±0.4 respectively. Subgroup analysis, PubMed review articles mean review days; and reducing at a rate of -0.21 days (count)/day. The number of publications related to the COVID-19 until now is huge and growing very fast with time. It is essential to rationalize and limit the publications.

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    Sarkar, B., Munshi, A., Ghosh, B., Ganesh, T., Manikandan, A., Biswal, S. S., Shahid, T., Bhaskar, R., Sengupta, S., Chowdhury, S. R., Bhattacharya, J., Gazi, M., De, A., George, K., Ghosh, T., Akhtar, J., Mandal, S., Mukherjee, M., Gupta, R., ... Mohanti, B. K. (2022). Evaluation of the Dynamics of Large Scale COVID-19 Related Literature through Bibliometric Analysis from a Mathematical Standpoint. Journal of Scientometric Research, 11(1), 47-54. https://doi.org/10.5530/jscires.11.1.5

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    © 2022 Author(s)

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. CC BY-NC-SA 4.0