Publication: A comparison of the Web of Science and publication-level classification systems of science
Loading...
Identifiers
Publication date
2017-02-01
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Impact
Export
Abstract
In this paper, we propose a new criterion for choosing between a pair of classification systems of science that assign publications (or journals) to a set of clusters. Consider the standard target (cited-side) normalization procedure in which cluster mean citations are used as normalization factors. We recommend system A over system B whenever the standard normalization procedure based on system A performs better than the standard normalization procedure based on system B. Performance is assessed in terms of two double tests- one graphical, and one numerical- that use both classification systems for evaluation purposes. In addition, a pair of classification systems is compared using a third, independent classification system for evaluation purposes. We illustrate this strategy by comparing a Web of Science journal-level classification system, consisting of 236 journal subject categories, with two publication-level algorithmically constructed classification systems consisting of 1363 and 5119 clusters. There are two main findings. Firstly, the second publication-level system is found to dominate the first. Secondly, the publication-level system at the highest granularity level and the Web of Science journal-level system are found to be non-comparable. Nevertheless, we find reasons to recommend the publication-level option. (C) 2016 Elsevier Ltd. All rights reserved.
Description
Keywords
Classification systems of science, Journal-level versus publication-level systems, Field-normalization, Citation impact indicators, Field-normalization, Fair
Bibliographic citation
Perianes-Rodriguez, A.; Ruiz-Castillo, J. (2017). A comparison of the Web of Science and publication-level classification systems of science. Journal of Infonometrics, v. 11, n. 1, pp. 32-45.