Comparison of the effect of mean-based method and z-score for field normalization of citations at the level of Web of Science subject categories

Zhihui Zhang (), Ying Cheng () and Nian Cai Liu ()
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Zhihui Zhang: Shanghai Jiao Tong University
Ying Cheng: Shanghai Jiao Tong University
Nian Cai Liu: Shanghai Jiao Tong University

Scientometrics, 2014, vol. 101, issue 3, No 6, 1679-1693

Abstract: Abstract Field normalization is a necessary step in a fair cross-field comparison of citation impact. In practice, mean-based method (m-score) is the most popular method for field normalization. However, considering that mean-based method only utilizes the central tendency of citation distribution in the normalization procedure and dispersion is also a significant characteristic, an open and important issue is whether alternative normalization methods which take both central tendency and variability into account perform better than mean-based method. With the aim of collapsing citation distributions of different fields into a universal distribution, this study compares the normalization effect of m-score and z-score based on 236 Web of Science (WoS) subject categories. The results show that both m-score and z-score have remarkable normalization effect as compared with raw citations, but neither of them can realize the ideal goal of “universality of citation distributions”. The results also suggest that m-score is generally preferable to z-score. The essential cause that m-score has an edge over z-score as a whole has a direct relationship with the characteristics of skewed citation distributions in which case m-score is more applicable than z-score.

Keywords: Citation distribution; Field normalization; Mean-based method; z-score; Normalization effect (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11192-014-1294-7

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