4.5 Article

ResearchGate and Google Scholar: how much do they differ in publications, citations and different metrics and why?

Journal

SCIENTOMETRICS
Volume 127, Issue 3, Pages 1515-1542

Publisher

SPRINGER
DOI: 10.1007/s11192-022-04264-2

Keywords

Academic social networks; Altmetrics; Bibliographic data sources; Google Scholar; ResearchGate; Scholarly databases; Scientometrics

Funding

  1. Science and Engineering Research Board (SERB), India [MTR/2020/000625]

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ResearchGate and Google Scholar often show different publication and citation data for the same authors, institutions, and journals. This article analyzes a large dataset of highly cited authors and finds significant differences in publications, citations, and metrics between the two platforms. The main probable reasons for these differences include coverage policy, indexing errors, author attribution mechanism, and strategy to deal with predatory publishing.
ResearchGate has emerged as a popular professional network for scientists and researchers in a very short span. Similar to Google Scholar, the ResearchGate indexing uses an automatic crawling algorithm that extracts bibliographic data, citations, and other information about scholarly articles from various sources. However, it has been observed that the two platforms often show different publication and citation data for the same institutions, journals, and authors. While several previous studies analysed different aspects of ResearchGate and Google Scholar, the quantum of differences in publications, citations, and metrics between the two and the probable reasons for the same are not explored much. This article, therefore, attempts to bridge this research gap by analysing and measuring the differences in publications, citations, and different metrics of the two platforms for a large data set of highly cited authors. The results indicate that there are significantly high differences in publications and citations for the same authors captured by the two platforms, with Google Scholar having higher counts for a vast majority of the cases. The different metrics computed by the two platforms also differ in their values, showing different degrees of correlation. The coverage policy, indexing errors, author attribution mechanism, and strategy to deal with predatory publishing are found to be the main probable reasons for the differences in the two platforms.

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