Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?

被引:97
作者
Bornmann, Lutz [1 ]
Marx, Werner [2 ]
机构
[1] Max Planck Gesell, Adm Headquarters, Div Sci & Innovat Studies, D-80539 Munich, Germany
[2] Max Planck Inst Solid State Res, D-70569 Stuttgart, Germany
关键词
F1000; Bibliometrics; Citing-side indicator; Cited-side indicator; Normalized citation impact; ADJUSTED PREDICTIONS; INDICATOR; P100;
D O I
10.1016/j.joi.2015.01.006
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Evaluative bibliometrics compare the citation impact of researchers, research groups and institutions with each other across time scales and disciplines. Both factors, discipline and period - have an influence on the citation count which is independent of the quality of the publication. Normalizing the citation impact of papers for these two factors started in the mid-1980s. Since then, a range of different methods have been presented for producing normalized citation impact scores. The current study uses a data set of over 50,000 records to test which of the methods so far presented correlate better with the assessment of papers by peers. The peer assessments come from F1000Prime - a post-publication peer review system of the biomedical literature. Of the normalized indicators, the current study involves not only cited-side indicators, such as the mean normalized citation score, but also citing-side indicators. As the results show, the correlations of the indicators with the peer assessments all turn out to be very similar. Since F1000 focuses on biomedicine, it is important that the results of this study are validated by other studies based on datasets from other disciplines or (ideally) based on multi-disciplinary datasets. (c) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:408 / 418
页数:11
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