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

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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.

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Notes

  1. http://dbpedia.org/page/DBpedia/.

  2. https://scholar.google.coms.

  3. http://www.shanghairanking.com/Shanghairanking-Subject-Rankings/Methodology-for-ShanghaiRanking-Global-Ranking-of-Academic-Subjects-2020.html.

  4. https://www.timeshighereducation.com/world-university-rankings-2021-subject-computer-science-methodology.

  5. https://www.topuniversities.com/subject-rankings/methodology.

  6. http://www.shanghairanking.com/Shanghairanking-Subject-Rankings/index.html.

  7. https://www.timeshighereducation.com/world-university-rankings/2021/world-ranking.

  8. https://www.topuniversities.com/subject-rankings/2020.

  9. https://en.wikipedia.org/wiki/google_scholar.

  10. https://wiki.dbpedia.org/services-resources/datasets/data-set-39.

  11. https://github.com/muhammadsajidqureshi82/OpenRank.git.

  12. https://dbpedia.org/sparql.

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Authors and Affiliations

  1. Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan

    Muhammad Sajid Qureshi & Ali Daud

  2. Department of Software Engineering, Foundation University Islamabad, Islamabad, Pakistan

    Muhammad Sajid Qureshi

  3. Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

    Ali Daud

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  1. Muhammad Sajid Qureshi
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  2. Ali Daud
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Correspondence to Ali Daud.

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Qureshi, M.S., Daud, A. Fine-grained academic rankings: mapping affiliation of the influential researchers with the top ranked HEIs. Scientometrics 126, 8331–8361 (2021). https://doi.org/10.1007/s11192-021-04138-z

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