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Fine-grained academic rankings: mapping affiliation of the influential researchers with the top ranked HEIs

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  • Muhammad Sajid Qureshi

    (International Islamic University
    Foundation University Islamabad)

  • Ali Daud

    (International Islamic University
    University of Jeddah)

Abstract

The academic ranking process has considerably evolved in the past fifteen years and the evolution has gained the momentum in last few years. Starting with the holistic rankings of world universities in 2003, it has crossed the milestone of subject-specific rankings. Nevertheless, the academic rankings published by even the reputed ranking entities are facing various criticism, in terms of their transparency, validity, and coverage. This research effort focuses on enhancing the credibility of the ranking process through the fine-grained analysis of the academic data. The proposed fine-grained analysis drives the researcher’s profiles from the Google Scholar Citations repository. While the DBpedia repository is employed for the information about HEIs and countries. The influential researchers are identified using the ResRank methodology. While, for consistent comparison of the subject-specific rankings of global HEIs, the Grand Average Rank (GAR) metric is employed. The resultant academic rankings with respect to the Research Faculty, Research Productivity, and Research Impact make the ranking process more transparent and fine-grained. The analysis also helps in understanding the causes of differences among the academic rankings published by the ARWU, THE, and QS rankings systems. The growing interest in the subject-specific and sub-discipline-specific rankings is irreversible. The fine-grained analysis is a response to the need.

Suggested Citation

  • Muhammad Sajid Qureshi & Ali Daud, 2021. "Fine-grained academic rankings: mapping affiliation of the influential researchers with the top ranked HEIs," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8331-8361, October.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:10:d:10.1007_s11192-021-04138-z
    DOI: 10.1007/s11192-021-04138-z
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    References listed on IDEAS

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    1. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Soldatenkova, Anastasiia, 2016. "The ratio of top scientists to the academic staff as an indicator of the competitive strength of universities," Journal of Informetrics, Elsevier, vol. 10(2), pages 596-605.
    2. Lin, Chi-Shiou & Huang, Mu-Hsuan & Chen, Dar-Zen, 2013. "The influences of counting methods on university rankings based on paper count and citation count," Journal of Informetrics, Elsevier, vol. 7(3), pages 611-621.
    3. Emilio Ferrara & Alfonso E. Romero, 2013. "Scientific impact evaluation and the effect of self-citations: Mitigating the bias by discounting the h-index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(11), pages 2332-2339, November.
    4. Isidro F. Aguillo & Judit Bar-Ilan & Mark Levene & José Luis Ortega, 2010. "Comparing university rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 243-256, October.
    5. ., 2017. "Standing on the shoulders of giants," Chapters, in: Endogenous Innovation, chapter 1, pages 3-24, Edward Elgar Publishing.
    6. Amjad, Tehmina & Ding, Ying & Xu, Jian & Zhang, Chenwei & Daud, Ali & Tang, Jie & Song, Min, 2017. "Standing on the shoulders of giants," Journal of Informetrics, Elsevier, vol. 11(1), pages 307-323.
    7. Christian Bizer & Tom Heath & Tim Berners-Lee, 2009. "Linked Data - The Story So Far," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 5(3), pages 1-22, July.
    8. Lutz Bornmann & Hans‐Dieter Daniel, 2007. "What do we know about the h index?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1381-1385, July.
    9. Ortega, José Luis, 2014. "Influence of co-authorship networks in the research impact: Ego network analyses from Microsoft Academic Search," Journal of Informetrics, Elsevier, vol. 8(3), pages 728-737.
    10. Emilio Ferrara & Alfonso E. Romero, 2013. "Scientific impact evaluation and the effect of self‐citations: Mitigating the bias by discounting the h‐index," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(11), pages 2332-2339, November.
    11. John Mingers & Jesse R. O’Hanley & Musbaudeen Okunola, 2017. "Using Google Scholar institutional level data to evaluate the quality of university research," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1627-1643, December.
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