Publication: Quantitative evaluation of alternative field normalization procedures
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2013-07
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Elsevier
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Abstract
Wide differences in publication and citation practices make impossible the direct comparison
of raw citation counts across scientific disciplines. Recent research has studied new and
traditional normalization procedures aimed at suppressing as much as possible these disproportions
in citation numbers among scientific domains. Using the recently introduced
IDCP (Inequality due to Differences in Citation Practices) method, this paper rigorously tests
the performance of six cited-side normalization procedures based on the Thomson Reuters
classification system consisting of 172 sub-fields. We use six yearly datasets from 1980 to
2004, with widely varying citation windows from the publication year to May 2011. The
main findings are the following three. Firstly, as observed in previous research, within each
year the shapes of sub-field citation distributions are strikingly similar. This paves the way
for several normalization procedures to perform reasonably well in reducing the effect on
citation inequality of differences in citation practices. Secondly, independently ofthe year of
publication and the length of the citation window, the effect of such differences represents
about 13% of total citation inequality. Thirdly, a recently introduced two-parameter normalization
scheme outperforms the other normalization procedures over the entire period,
reducing citation disproportions to a level very close to the minimum achievable given the
data and the classification system. However, the traditional procedure of using sub-field
mean citations as normalization factors yields also good results.
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Yunrong Li, Filippo Radicchi, Claudio Castellano and Javier Ruiz-Castillo, “Quantitative Evaluation of Alternative Field Normalization Procedures”, Journal of Informetrics, 2013, v. 7, n. 3, pp. 476-755