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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 2, 2021
Open Peer Review Period: Mar 2, 2021 - Apr 27, 2021
Date Accepted: Mar 15, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Types of Errors Hiding in Google Scholar Data

Sauvayre R

Types of Errors Hiding in Google Scholar Data

J Med Internet Res 2022;24(5):e28354

DOI: 10.2196/28354

PMID: 35622395

PMCID: 9187964

What types of errors are hiding in Google Scholar data? A case study

  • Romy Sauvayre

ABSTRACT

Google Scholar (GS) is a free tool that may be used by researchers to analyze citations, to find appropriate literature or to evaluate the quality of an author or a contender for tenure, promotion, a faculty position, funding or research grants. GS has become a major bibliographic and citation database. Following the literature, databases such as PubMed, PsycINFO, Scopus or Web of Science can be used in place of GS because they are more reliable. The aim of this study is to examine the accuracy of citation data collected from GS and provide a comprehensive description of the errors and miscounts identified. For this purpose, 281 documents that cited two specific works were retrieved via the Publish or Perish (PoP) software and examined. This work studied the false positive issue inherent in the analysis of neuroimaging data. The results reveal an unprecedented error rate: 279 of 281 the examined references (99.3%) contain at least one error. The nonacademic documents tend to contain more errors than the academic publications (U = 5117.0, P<.001). GS data not only fail to be accurate but also potentially expose those researchers who would use these data without verification to substantial biases in their analyses and results. This viewpoint article, based on a case study, suggests reflecting on the consequences of using GS data extracted by PoP.


 Citation

Please cite as:

Sauvayre R

Types of Errors Hiding in Google Scholar Data

J Med Internet Res 2022;24(5):e28354

DOI: 10.2196/28354

PMID: 35622395

PMCID: 9187964

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