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Using Google Scholar institutional level data to evaluate the quality of university research
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691114/ https://www.ncbi.nlm.nih.gov/pubmed/29200538 http://dx.doi.org/10.1007/s11192-017-2532-6 |
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author | Mingers, John O’Hanley, Jesse R. Okunola, Musbaudeen |
author_facet | Mingers, John O’Hanley, Jesse R. Okunola, Musbaudeen |
author_sort | Mingers, John |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5691114 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-56911142017-11-30 Using Google Scholar institutional level data to evaluate the quality of university research Mingers, John O’Hanley, Jesse R. Okunola, Musbaudeen Scientometrics Article 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. Springer Netherlands 2017-10-03 2017 /pmc/articles/PMC5691114/ /pubmed/29200538 http://dx.doi.org/10.1007/s11192-017-2532-6 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Mingers, John O’Hanley, Jesse R. Okunola, Musbaudeen Using Google Scholar institutional level data to evaluate the quality of university research |
title | Using Google Scholar institutional level data to evaluate the quality of university research |
title_full | Using Google Scholar institutional level data to evaluate the quality of university research |
title_fullStr | Using Google Scholar institutional level data to evaluate the quality of university research |
title_full_unstemmed | Using Google Scholar institutional level data to evaluate the quality of university research |
title_short | Using Google Scholar institutional level data to evaluate the quality of university research |
title_sort | using google scholar institutional level data to evaluate the quality of university research |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691114/ https://www.ncbi.nlm.nih.gov/pubmed/29200538 http://dx.doi.org/10.1007/s11192-017-2532-6 |
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