Can we use Google Scholar to identify highly-cited documents?

Article


Martin-Martin, A., Orduna-Malea, E., Harzing, A. and Delgado López-Cózar, E. 2017. Can we use Google Scholar to identify highly-cited documents? Journal of Informetrics. 11 (1), pp. 152-163. https://doi.org/10.1016/j.joi.2016.11.008
TypeArticle
TitleCan we use Google Scholar to identify highly-cited documents?
AuthorsMartin-Martin, A., Orduna-Malea, E., Harzing, A. and Delgado López-Cózar, E.
Abstract

The main objective of this paper is to empirically test whether the identification of highly-cited documents through Google Scholar is feasible and reliable. To this end, we carried out a longitudinal analysis (1950 to 2013), running a generic query (filtered only by year of publication) to minimise the effects of academic search engine optimisation. This gave us a final sample of 64,000 documents (1,000 per year). The strong correlation between a document’s citations and its position in the search results (r= -0.67) led us to conclude that Google Scholar is able to identify highly-cited papers effectively.
This, combined with Google Scholar’s unique coverage (no restrictions on document type and source), makes the academic search engine an invaluable tool for bibliometric research relating to the identification of the most influential scientific documents. We find evidence, however, that Google Scholar ranks those documents whose language (or geographical web domain) matches with the user’s interface language higher than could be expected based on citations. Nonetheless, this language effect and other factors related to the Google Scholar’s operation, i.e. the proper identification of versions and the date of publication, only have an incidental impact. They do not compromise the ability of Google Scholar to identify the highly-cited papers.

KeywordsGoogle Scholar; academic search engines; highly-cited documents; academic information retrieval
Research GroupInternational and Cross-cultural Management group
LanguageEnglish
PublisherElsevier
JournalJournal of Informetrics
ISSN1751-1577
Electronic1875-5879
Publication dates
Online23 Dec 2016
Print01 Feb 2017
Publication process dates
Deposited20 Dec 2016
Accepted29 Nov 2016
Submitted26 Oct 2016
Output statusPublished
Accepted author manuscript
License
Copyright Statement

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Digital Object Identifier (DOI)https://doi.org/10.1016/j.joi.2016.11.008
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