The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits

Abstract

Percentiles have been established in bibliometrics as an important alternative to mean-based indicators for obtaining a normalized citation impact of publications. Percentiles have a number of advantages over standard bibliometric indicators used frequently: for example, their calculation is not based on the arithmetic mean which should not be used for skewed bibliometric data. This study describes the opportunities and limits and the advantages and disadvantages of using percentiles in bibliometrics. We also address problems in the calculation of percentiles and percentile rank classes for which there is not (yet) a satisfactory solution. It will be hard to compare the results of different percentile-based studies with each other unless it is clear that the studies were done with the same choices for percentile calculation and rank assignment.

A review of theory and practice in scientometrics

“…This approach provides a lot of information about the 16 There are several technical problems to be dealt with in operationalising these classes (Bornmann, Leydesdorff & Mutz, 2013;Bornmann, Leydesdorff, et al, 2013b). 17 Using Dunn's test or the Mann-Whitney U test proportions of papers at different levels, but it is still useful to be able to summarise performance in a single value.…”

Methods for the generation of normalized citation impact scores in bibliometrics: Which method best reflects the judgements of experts?

“…Percentiles may be calculated with various procedures (Bornmann, Leydesdorff, & Mutz, 2013). For the current study, two procedures were used which may be described as the most important.…”

Can comments cause citations? Yes, they can!

“…In recent years there has been a controversy in bibliometrics how to treat tied papers, i.e. papers with the same number of citations in the dataset [2]. For the present purpose it is sufficient to average the ranks of the tied papers and utilize the corresponding percentile [3].…”