Loading...
Factors associating with or predicting more cited or higher quality journal articles: An Annual Review of Information Science and Technology (ARIST) paper
Authors
Editors
Other contributors
Affiliation
Epub Date
Issue Date
2023-06-27
Submitted date
Files
Loading...
2023_Kousha_Factors.pdf
Adobe PDF, 2.86 MB
Alternative
Abstract
Identifying factors that associate with more cited or higher quality research may be useful to improve science or to support research evaluation. This article reviews evidence for the existence of such factors in article text and metadata. It also reviews studies attempting to estimate article quality or predict long term citation counts using statistical regression or machine learning for journal articles or conference papers. Although the primary focus is on document-level evidence, the related task of estimating the average quality scores of entire departments from bibliometric information is also considered. The review lists a huge range of factors that associate with higher quality or more cited research in some contexts (fields, years, journals) but the strength and direction of association often depends on the set of papers examined, with little systematic pattern and rarely any cause-and-effect evidence. The strongest patterns found include the near universal usefulness of journal citation rates, author numbers, reference properties, and international collaboration in predicting (or associating with) higher citation counts, and the greater usefulness of citation-related information for predicting article quality in the medical, health and physical sciences than in engineering, social sciences, arts, and humanities.
Citation
Kousha, K. and Thelwall, M. (2024). Factors associating with or predicting more cited or higher quality journal articles: An Annual Review of Information Science and Technology (ARIST) paper. Journal of the Association for Information Science and Technology, 75(3), pp. 215–244. https://doi.org/10.1002/asi.24810
Publisher
Research Unit
PubMed ID
PubMed Central ID
Embedded videos
Additional Links
Type
Journal article
Language
en
Description
© 2023 The Authors. Published by Wiley. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1002/asi.24810
Series/Report no.
ISSN
2330-1635
EISSN
2330-1643