 How to improve the prediction based on citation impact percentiles for years shortly after the publication date?Lutz Bornmann (), Loet Leydesdorff and Jian Wang Journal of Informetrics, 2014, vol. 8, issue 1, 175-180 Abstract: The findings of Bornmann, Leydesdorff, and Wang (2013b) revealed that the consideration of journal impact improves the prediction of long-term citation impact. This paper further explores the possibility of improving citation impact measurements on the base of a short citation window by the consideration of journal impact and other variables, such as the number of authors, the number of cited references, and the number of pages. The dataset contains 475,391 journal papers published in 1980 and indexed in Web of Science (WoS, Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these papers. As an indicator of citation impact, we used percentiles of citations calculated using the approach of Hazen (1914). Our results show that citation impact measurement can really be improved: If factors generally influencing citation impact are considered in the statistical analysis, the explained variance in the long-term citation impact can be much increased. However, this increase is only visible when using the years shortly after publication but not when using later years. Keywords: Citation impact normalization; Percentile; Short citation window (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:8:y:2014:i:1:p:175-180 DOI: 10.1016/j.joi.2013.11.005 Access Statistics for this article Journal of Informetrics is currently edited by Leo Egghe More articles in Journal of Informetrics from Elsevier |
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