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

Articolo
Data di Pubblicazione:
2019
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. (C) 2018 Elsevier Ltd. All rights reserved.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Research assessment; Citation time window; Regression analysis; Bibliometrics
Elenco autori:
D'Angelo, CIRIACO ANDREA; Abramo, Giovanni; Felici, Giovanni
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/364493
Pubblicato in:
JOURNAL OF INFORMETRICS
Journal
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