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Large Scopus Data Sets and Its Analysis for Decision Making

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  • Prem Kumar Singh

    (Gandhi Institute of Technology and Management-Vishakhapatnam)

Abstract

Recently several authors paid attention towards Scopus Data analysis for intellectual measurement of institutes or authors. It is well known that the SCOPUS contains more than 34,346 peer reviewed Journals from different subjects with 3 lakh conferences. It is difficult to measure the performance or expertise of any institute or author in the given domain for admission, job, and ranking or other decision making process. The reason is several manipulations started in document and citation count via strategic authors or institute which can be measured via average author publications, number of funding, collaborations and retracted papers. It is happening due to rogue editor or business strategic of educationalist for profit. However these types of misconduct impacts lot to real researcher which forces brain drain. To resolve this issue, the current paper provides a way to measure the intellectual achievement of an institute or author based on several metrics. The proposed method is illustrated using the SCOPUS data sets and it’s metric for critical understanding.

Suggested Citation

  • Prem Kumar Singh, 2024. "Large Scopus Data Sets and Its Analysis for Decision Making," Annals of Data Science, Springer, vol. 11(2), pages 589-618, April.
    • Handle: RePEc:spr:aodasc:v:11:y:2024:i:2:d:10.1007_s40745-022-00435-3
    DOI: 10.1007/s40745-022-00435-3
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    References listed on IDEAS

    as
    1. Prem Kumar Singh, 2022. "t-index: entropy based random document and citation analysis using average h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 637-660, January.
    2. Henk F. Moed & Gali Halevi, 2014. "A bibliometric approach to tracking international scientific migration," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1987-2001, December.
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    7. Benedetto Torrisi, 2015. "The quality of work in public universities with no-parametric statistical models," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 349-363, January.
    8. J. E. Hirsch, 2019. "hα: An index to quantify an individual’s scientific leadership," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 673-686, February.
    9. Jeremiah Joven Joaquin & Raymond R. Tan, 2021. "The lost art of short communications in academia," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9633-9637, December.
    10. Vít Macháček & Martin Srholec, 2021. "RETRACTED ARTICLE: Predatory publishing in Scopus: evidence on cross-country differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1897-1921, March.
    11. Alexander Subbotin & Samin Aref, 2021. "Brain drain and brain gain in Russia: Analyzing international migration of researchers by discipline using Scopus bibliometric data 1996–2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7875-7900, September.
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