3.8 Article

The prevalence and impact of university affiliation discrepancies between four bibliographic databases-Scopus, Web of Science, Dimensions, and Microsoft Academic

期刊

QUANTITATIVE SCIENCE STUDIES
卷 3, 期 1, 页码 99-121

出版社

MIT PRESS
DOI: 10.1162/qss_a_00175

关键词

affiliation; benchmarking; bibliometric database; disambiguation; unification; university

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Research managers who benchmark universities against international peers often encounter the problem of affiliation disambiguation. This study examined the affiliation discrepancies between four different databases over a 5-year period for 18 Arab universities. The findings revealed that the larger databases had a higher share of discrepancies, while the smaller, more selective databases had a greater degree of agreement with affiliations in the other databases. The discrepancies were caused by missing affiliations, unification differences, and incorrect assignment of records.
Research managers benchmarking universities against international peers face the problem of affiliation disambiguation. Different databases have taken separate approaches to this problem and discrepancies exist between them. Bibliometric data sources typically conduct a disambiguation process that unifies variant institutional names and those of its subunits so that researchers can then search all records from that institution using a single unified name. This study examined affiliation discrepancies between Scopus, Web of Science (WoS), Dimensions, and Microsoft Academic for 18 Arab universities over a 5-year period. We confirmed that digital object identifiers (DOIs) are suitable for extracting comparable scholarly material across databases and quantified the affiliation discrepancies between them. A substantial share of records assigned to the selected universities in any one database were not assigned to the same university in another. The share of discrepancy was higher in the larger databases (Dimensions and Microsoft Academic). The smaller, more selective databases (Scopus and especially WoS) tended to agree to a greater degree with affiliations in the other databases. Manual examination of affiliation discrepancies showed that they were caused by a mixture of missing affiliations, unification differences, and assignation of records to the wrong institution.

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