Detecting incoherent citation data among three bibliometric platforms: OpenAlex, Scopus and Web of Science

Abstract

The number of citations received by a research paper is a vital metric for both researchers and institutions. Various indexing databases share common citations, facilitating cross-database comparison to identify citations missing from multiple databases, which are not contributing to the total citation count of a paper. To tackle this problem, we developed an automated method to detect missing citations by utilising multiple indexing databases. We focus on identifying missing citations in Web of Science and Scopus, using OpenAlex to enhance the process and demonstrate the benefits of cross-referencing databases for more comprehensive citation tracking. We compared the results of a previous experiment where we did not use Scopus. This way, we could measure the impact of adding Scopus to our approach. By using the same data set as before, the papers we were able to analyse increased from 1539 to 1989, and we were able to find a total of 1075 missing citations in Web of Science as opposed to the 696 we found without including Scopus. As for the results in Scopus, we identified 1137 missing citations in the same set of papers, totalling 2212 missing citations found. This outcome proves that these indexing databases cannot accurately detect all citations. Also, for more recent publications, we detected a bigger discrepancy in missing citations found in Web of Science when compared with Scopus. We can also conclude that adding different databases can provide us with better results and a more accurate view of the citation list of a paper.