Bibliometric Indicators of Young Authors in Astrophysics: Can Later Stars be Predicted?

Abstract

We test 16 bibliometric indicators with respect to their validity at the level of the individual researcher by estimating their power to predict later successful researchers. We compare the indicators of a sample of astrophysics researchers who later co-authored highly cited papers before their first landmark paper with the distributions of these indicators over a random control group of young authors in astronomy and astrophysics. We find that field and citation-window normalisation substantially improves the predicting power of citation indicators. The two indicators of total influence based on citation numbers normalised with expected citation numbers are the only indicators which show differences between later stars and random authors significant on a 1% level. Indicators of paper output are not very useful to predict later stars. The famous $h$-index makes no difference at all between later stars and the random control group.

arXiv comment14 pages, 10 figures

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Cited by in corpus (5)

• Predicting citation counts based on deep neural network learning techniques
• Bibliometric Indicators of Young Authors in Astrophysics: Can Later Stars be Predicted?
• Prediction Methods and Applications in the Science of Science: A Survey
• Identification of young talented individuals in the natural and life sciences using bibliometric data
• Utilizing Citation Network Structure to Predict Citation Counts: A Deep Learning Approach