Errors in document-type classification
A focus on engineering publications and their publishers
Bibliographic Data
| ID | 21442645 |
|---|---|
| Authors | Domenico A Maisano (0000-0002-8154-4469, Politecnico di Torino), Lucrezia Ferrara (Politecnico di Torino), Fiorenzo Franceschini (0000-0001-7131-4419, Politecnico di Torino, corresponding author) |
| Year | 2025 |
| Volume | 130 |
| Issue | 11 |
| Pages | 6613-6641 |
| Publication date | 2025-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-025-05444-6 |
| OpenAlex | W4415270709 |
| Language | EN |
| References cited | 26 |
This study investigates document-type (DT) classification errors—such as misclassifications of research articles , reviews , conference proceedings , editorials , etc.—in the bibliometric databases Scopus and Web of Science, focusing on the field of engineering . Such misclassifications can adversely affect academic research and research quality assessments, with potential repercussions on researchers' careers and the allocation of funding in academic institutions. By analysing a corpus of approximately 10,000 publications, a semi-automated approach is employed to identify misclassified documents and attribute errors to the responsible database. Additionally, the role of publishers (e.g., “Elsevier”, “Springer Nature”, “Taylor & Francis”, etc.) is investigated, based on the hypothesis that certain publishers may contribute more significantly than others to DT-classification errors, due to specific editorial practices or inconsistencies in metadata. The results reveal that classification errors are non-negligible (i.e., they occur at rates of a few percentage points) and that the extent of publishers' contributions varies significantly in both Scopus and WoS. However, the most problematic publishers for each database appear to be uncorrelated. Integrating various statistical tests, this study provides insights that may be valuable to researchers, research evaluators, database operators, and publishers, raising awareness of the issue and offering preliminary indications for identifying possible remedies to mitigate such errors and enhance DT-classification accuracy. Future research will further investigate the reasons behind the concentration of errors among certain publishers
Bibliometrics · Field (mathematics) · Focus (optics) · Quality (philosophy) · Scopus · Web of science · Academic integrity and plagiarism · Optics and Image Analysis · scientometrics and bibliometrics research
The Oligopoly of Academic Publishers in the Digital Era
A large-scale semi-automated approach for assessing document-type classification errors in bibliometric databases
Assigning different document types by Scopus for similar contents
Understanding the increasing market share of the academic publisher “Multidisciplinary Digital Publishing Institute” in the publication output of Central and Eastern European countries
Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies
| Highly cited | No |
|---|