Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus
By Qi Wang, Ludo Waltman. J. Informetrics, 2015
388 citations recorded by the source corpus.
Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically investigated the accuracy of these classification systems. To examine and compare the accuracy of journal classification systems, we define two criteria on the basis of direct citation relations between journals and categories. We use Criterion I to select journals that have weak connections with their assigned categories, and we use Criterion II to identify journals that are not assigned to categories with which they have strong connections. If a journal satisfies either of the two criteria, we conclude that its assignment to categories may be questionable. Accordingly, we identify all journals with questionable classifications in Web of Science and Scopus. Furthermore, we perform a more in-depth analysis for the field of Library and Information Science to assess whether our proposed criteria are appropriate and whether they yield meaningful results. It turns out that according to our citation-based criteria Web of Science performs significantly better than Scopus in terms of the accuracy of its journal classification system.
Subfields: Artificial Intelligence, Information Systems, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/236e7b07d46edcec6f1ae30e4d163fe8040177d6
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Citations in the corpus
- Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today's Academic World (2021, methodology): “Moreover, an explanation of Scopus metrics, ASJC code classification, and/or information regarding the inclusion of Medline content are also provided in the separate sheet in both lists.”
- Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge? (2015, neutral): “6%), which correlates well with a recent analysis of the two classification systems by Wang and Waltman (2016). However, neither vendor-provided classification system performs as well as some of those created by outside researchers.”