Central indexes to the citation distribution: A complement to the h-index

TL;DR

This paper introduces new central indexes that complement the h-index by capturing the central shape of citation distributions, aiming to improve researcher evaluation.

Contribution

It proposes two novel sets of indexes, the central area and interval indexes, to better characterize the central citation distribution beyond the h-index.

Findings

Central indexes reduce bias from distribution tails.

Indexes provide better discrimination among researchers.

Complement h-index for more comprehensive evaluation.

Abstract

The citation distribution of a researcher shows the impact of their production and determines the success of their scientific career. However, its application in scientific evaluation is difficult due to the bi-dimensional character of the distribution. Some bibliometric indexes that try to synthesize in a numerical value the principal characteristics of this distribution have been proposed recently. In contrast with other bibliometric measures, the biases that the distribution tails provoke, are reduced by the h-index. However, some limitations in the discrimination among researchers with different publication habits are presented in this index. This index penalizes selective researchers, distinguished by the large number of citations received, as compared to large producers. In this work, two original sets of indexes, the central area indexes and the central interval indexes, that complement the h-index to include the central shape of the citation distribution, are proposed and compared.