Measuring the robustness of the journal h-index with respect to publication and citation values: A Bayesian sensitivity analysis

TL;DR

This paper uses Bayesian sensitivity analysis to examine how robust the journal h-index is to variations in publication and citation counts, revealing it is most sensitive to citation changes beyond the 25th percentile.

Contribution

It introduces a Bayesian approach to analyze the robustness of the journal h-index against publication and citation fluctuations, providing new insights into its stability.

Findings

h-index is robust to citation changes up to the 25th percentile

Sensitivity increases with citation counts beyond the 25th percentile

Behavior is consistent across different models and research fields

Abstract

Braun et al. (2006) recommended using the h-index as an alternative to the journal impact factor (IF) to qualify journals. In this paper, a Bayesian-based sensitivity analysis is performed with the aid of mathematical models to examine the behavior of the journal h-index to changes in the publication/citation counts of journals. Sensitivity of the h-index was most apparent for changes in the number of citations, revealing similar patterns of behavior for almost all models and independently to the field of research. In general, the h-index was found to be robust to changes in citations up to approximately the 25th percentile of the citation distribution, inflating its value afterwards.