A comparison of the Web of Science and publication-level classification systems of science

作者：Perianes Rodriguez Antonio; Ruiz Castillo Javier^*

来源：Journal of Informetrics, 2017, 11(1): 32-45.

DOI：10.1016/j.joi.2016.10.007

• Classification systems of science
• Journal-level versus publication-level systems
• Field-normalization

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.

• 出版日期2017-2