Sub-field normalization of the IEEE scientific journals based on their connection with Technical Societies

被引:13
作者
Franceschini, Fiorenzo [1 ]
Maisano, Domenico [1 ]
机构
[1] Politecn Torino, DIGEP Dept Management & Prod Syst, I-10129 Turin, Italy
关键词
Journal ranking; IEEE journal; Propensity to cite; Sub-field normalization; IEEE Society; IMPACT; CITATIONS; INDICATORS;
D O I
10.1016/j.joi.2014.04.005
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A recent paper (Canavero et al., 2014. Journal of the American Society for Information Science and Technology, doi:10.1109/TPC.2013.2255935) performed a bibliometric analysis of an extensive set of scientific journals within the Engineering field, published by IEEE (Institute of Electrical and Electronics Engineers). The analysis was based on (i) the citation impact of journal articles and (ii) the reputation of journal authors in terms of total scientific production and relevant citation impact. The goal of this paper is to complement the prior analysis, investigating on the different citation cultures of these journals, depending on the sub-field/specialty of interest. To perform this evaluation, it is suggested a novel technique, which takes into account the connections between journals and some highly specialized communities of scientists, known as IEEE Technical Societies and Councils. After showing significant differences in terms of propensity to cite, probably attributable to the large variety of sub-fields and specialties covered by IEEE journals, it is presented a simplified technique for the sub-field normalization of the results of the prior study. The main contribution of this work is (1) providing an empirical confirmation of the complexity of the problem of normalization, even for journals within the same field but different sub-fields/specialties, and (2) showing how the use of highly specialized information on a journal reference sub-field(s) may be helpful for improving the estimation of the journal propensity to cite. Description is supported by a large amount of empirical data. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:508 / 533
页数:26
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Franceschini, Fiorenzo ;
Galetto, Maurizio ;
Maisano, Domenico ;
Mastrogiacomo, Luca .
SCIENTOMETRICS, 2012, 92 (03) :621-641