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Does the h index have predictive power?
Open accessAbstract
Bibliometric measures of individual scientific achievement are of particular interest if they can be used to predict future achievement. Here we report results of an empirical study of the predictive power of the h index compared with other indicators. Our findings indicate that the h index is better than other indicators considered (total citation count, citations per paper, and total paper count) in predicting future scientific achievement. We discuss reasons for the superiority of the h index.
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Cited by
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., et al. (2018) · Science · doi:10.1126/science.aao0185 · Cited by 1,497
“It has been suggested that the future h-index (83) of a scientist can be accurately predicted (84), although the predictive power is reduced when”
A Review of Theory and Practice in Scientometrics
Mingers, J., & Leydesdorff, L. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.04.002 · Cited by 1,002
Universality of citation distributions: Toward an objective measure of scientific impact
Radicchi, F., Fortunato, S., & Castellano, C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806977105 · Cited by 828
Over-optimization of academic publishing metrics: observing Goodhart's Law in action
Fire, M., & Guestrin, C. (2019) · GigaScience · doi:10.1093/gigascience/giz053 · Cited by 351
Acuna, D. E., Allesina, S., & Kording, K. P. (2012) · Nature · doi:10.1038/489201a · Cited by 249
Metadata
- Authors
- Hirsch, J. E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2007-12-04
- Volume
- 104
- Issue
- 49
- Pages
- 19193-19198
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1982218215
- Cited by
- 973
- References
- 0
- FWCI
- 49.40
- Type
- journal article
- Language
- en
- Open access
- green
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
