RT Generic
T1 A comparison of the Web of Science with publication-level classification systems of Science
A1 Perianes-Rodríguez, Antonio
A1 Ruiz-Castillo, Javier
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB 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 (citedside) 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 1,363 and 5,119 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.
SN 2340-5031
YR 2016
FD 2016-01-01
LK https://hdl.handle.net/10016/22137
UL https://hdl.handle.net/10016/22137
LA eng
NO This research project builds on earlier work started by Antonio Perianes-Rodriguez during a research visit to the Centre for Science and Technology Studies (CWTS) of LeidenUniversity as awardee of José Castillejo grant, CAS15/00178, funded by the Spanish MEC. Ruiz-Castillo is a visiting researcher at CWTS and gratefully acknowledges CWTS for the use of its data.Ruiz-Castillo acknowledges financial support from the Spanish MEC through grant ECO2014-55953-P, as well as grant MDM 2014-0431 to his Departamento de Economía.
DS e-Archivo
RD 15 ago. 2024