Analyzing journal category assignment using a paper-level classification system: multidisciplinary sciences journals

Jiandong Zhang () and Zhesi Shen ()
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Jiandong Zhang: Chinese Academy of Sciences
Zhesi Shen: Chinese Academy of Sciences

Scientometrics, 2024, vol. 129, issue 10, No 8, 5963-5978

Abstract: Abstract Accurate identification and classification of “multidisciplinary” journals is crucial in scientometrics for revealing scientific structure and evaluating journals. Using Web of Science data from 2016 to 2020, we calculated disciplinary diversity of 12,225 journals based on paper-level subject classifications. We conducted a systematic analysis comparing Journal Citation Reports (JCR) multidisciplinary journals versus non-multidisciplinary journals. Results showed most JCR multidisciplinary journals have high disciplinary diversity, while non-multidisciplinary journals tend to have lower diversity. Some multidisciplinary journals with low diversity may be misclassified. We also found inconsistencies in journal disciplinary diversity at three granularity levels of the classification system. Visual analysis identified four distribution types of multidisciplinary journal diversity. Furthermore, ten potential multidisciplinary journals were identified in non-multidisciplinary JCR categories. Analysis of these journals showed two distinct publishing behaviors—some continuously publish across multiple fields, while others constantly change focus between fields.

Keywords: Journal classification system; Multidisciplinary sciences journals; Disciplinary diversity; Science mapping (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-023-04913-0

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