Predicting publication long-term impact through a combination of early citations and journal impact factor

Giovanni Abramo, D’Angelo, Ciriaco Andrea and Giovanni Felici

Journal of Informetrics, 2019, vol. 13, issue 1, 32-49

Abstract: The ability to predict the long-term impact of a scientific article soon after its publication is of great value towards accurate assessment of research performance. In this work we test the hypothesis that good predictions of long-term citation counts can be obtained through a combination of a publication's early citations and the impact factor of the hosting journal. The test is performed on a corpus of 123,128 WoS publications authored by Italian scientists, using linear regression models. The average accuracy of the prediction is good for citation time windows above two years, decreases for lowly-cited publications, and varies across disciplines. As expected, the role of the impact factor in the combination becomes negligible after only two years from publication.

Keywords: Research assessment; Citation time window; Regression analysis; Bibliometrics (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (36)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:13:y:2019:i:1:p:32-49

DOI: 10.1016/j.joi.2018.11.003

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