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

TL;DR

This study analyzes affiliation discrepancies across four major bibliographic databases for Arab universities, revealing significant inconsistencies influenced by database size and disambiguation practices, impacting research benchmarking.

Contribution

It provides a comparative analysis of affiliation discrepancies among four databases, highlighting causes and implications for university benchmarking and bibliometric research.

Findings

Higher discrepancy in larger databases like Dimensions and Microsoft Academic.

Smaller, selective databases like Web of Science show greater agreement.

Discrepancies caused by missing affiliations, unification differences, and misassignments.

Abstract

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 sub-units 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, Dimensions, and Microsoft Academic for 18 Arab universities over a five-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 Web of Science tended to agree to a greater degree with affiliations in the other databases. Manual examination of affiliation discrepancies showed they were caused by a mixture of missing affiliations, unification differences, and assignation of records to the wrong institution.