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Using Google Scholar institutional level data to evaluate the quality of university research

Author

Listed:
  • John Mingers

    (University of Kent)

  • Jesse R. O’Hanley

    (University of Kent)

  • Musbaudeen Okunola

    (University of Kent)

Abstract

In recent years, the extent of formal research evaluation, at all levels from the individual to the multiversity has increased dramatically. At the institutional level, there are world university rankings based on an ad hoc combination of different indicators. There are also national exercises, such as those in the UK and Australia that evaluate research outputs and environment through peer review panels. These are extremely costly and time consuming. This paper evaluates the possibility of using Google Scholar (GS) institutional level data to evaluate university research in a relatively automatic way. Several citation-based metrics are collected from GS for all 130 UK universities. These are used to evaluate performance and produce university rankings which are then compared with various rankings based on the 2014 UK Research Excellence Framework (REF). The rankings are shown to be credible and to avoid some of the obvious problems of the REF ranking, as well as being highly efficient and cost effective. We also investigate the possibility of normalizing the results for the university subject mix since science subjects generally produce significantly more citations than social science or humanities.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:scient:v:113:y:2017:i:3:d:10.1007_s11192-017-2532-6
    DOI: 10.1007/s11192-017-2532-6
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    References listed on IDEAS

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    4. Margaret K. Merga & Sayidi Mat Roni & Shannon Mason, 2020. "Should Google Scholar be used for benchmarking against the professoriate in education?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2505-2522, December.
    5. Enrique Orduna-Malea & Selenay Aytac & Clara Y. Tran, 2019. "Universities through the eyes of bibliographic databases: a retroactive growth comparison of Google Scholar, Scopus and Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 433-450, October.

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