An indicator of the impact of journals based on the percentage of their highly cited publications

Abstract

Purpose

The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category). Furthermore, the impact factor is not robust to the presence of articles with a large number of citations, while the h-index depends on the journal size. These limitations are very important when comparing journals of different sizes and categories. The purpose of this paper is to propose an alternative citation impact indicator, based on the percentage of highly cited articles in the journal.

Design/methodology/approach

This alternative indicator is empirically compared with the impact factor and the h-index, considering different time windows and citation percentiles (levels of citation for considering an article as highly cited compared to others in the same year and category). The authors use four journal categories (Clarivate Analytics Web of Science) which are quite different according to the publication profiles and citation levels (Information Science & Library Science, Operations Research & Management Science, Ophthalmology, and Physics Condensed Matter).

Findings

After analyzing 20 different indicators, depending on the citation percentile and the time window in which citations are counted, the indicator that seems to best homogenize the categories is the one that considers a time window of two years and a citation level of 10 percent.

Originality/value

The percentage of highly cited articles in a journal is field normalized (comparable between scientific categories), independent of the journal size and also robust to the presence of articles with a high number of citations.

Citation

González-Betancor, S.M. and Dorta-González, P. (2017), "An indicator of the impact of journals based on the percentage of their highly cited publications", Online Information Review, Vol. 41 No. 3, pp. 398-411. https://doi.org/10.1108/OIR-01-2016-0008