Assigning publications to multiple subject categories for bibliometric analysis: An empirical case study based on percentiles

Abstract

Purpose

This study is concerned with a problem in measuring citation impact with the aid of percentile data, which arises from the assignment of publications (or the journals in which the publications have appeared) by Thomson Reuters for the Web of Science to more than one subject category. If there is more than one subject category for a publication, it is initially unclear which category is to be used to create the reference set for the calculation of the percentile. This paper seeks to address these issues.

Design/methodology/approach

In this study the author would like to look at whether the calculation of differences between the citation impact of research institutions is affected by whether the minimum (the maximum percentile), the maximum (the minimum percentile), the mean or the median impact (percentile) for the different subject categories is used. The study is based on a sample of percentile data for three research institutions (n=4,232).

Findings

The result of the comparison of citation impact of the three institutions remains very similar for all the calculation methods, but on a different level.

Originality/value

It is the first study, which investigates how far it makes a difference in the comparison of the citation impact of three different research institutes whether – with multiple assignments of subject categories to one publication – the minimum, the maximum, the mean or the median inverted percentile is used. An answer to the question is very relevant since different methods are used in practical application. For example, the web-based research evaluation tool InCites uses the minimum percentile.

Citation

Bornmann, L. (2014), "Assigning publications to multiple subject categories for bibliometric analysis: An empirical case study based on percentiles", Journal of Documentation, Vol. 70 No. 1, pp. 52-61. https://doi.org/10.1108/JD-10-2012-0136