The h'-index, effectively improving the h-index based on the citation distribution

PLoS One. 2013;8(4):e59912. doi: 10.1371/journal.pone.0059912. Epub 2013 Apr 2.

Abstract

Background: Although being a simple and effective index that has been widely used to evaluate academic output of scientists, the h-index suffers from drawbacks. One critical disadvantage is that only h-squared citations can be inferred from the h-index, which completely ignores excess and h-tail citations, leading to unfair and inaccurate evaluations in many cases.

Methodology principal findings: To solve this problem, I propose the h'-index, in which h-squared, excess and h-tail citations are all considered. Based on the citation data of the 100 most prolific economists, comparing to h-index, the h'-index shows better correlation with indices of total-citation number and citations per publication, which, although relatively reliable and widely used, do not carry the information of the citation distribution. In contrast, the h'-index possesses the ability to discriminate the shapes of citation distributions, thus leading to more accurate evaluation.

Conclusions significance: The h'-index improves the h-index, as well as indices of total-citation number and citations per publication, by possessing the ability to discriminate shapes of citation distribution, thus making the h'-index a better single-number index for evaluating scientific output in a way that is fairer and more reasonable.

MeSH terms

  • Efficiency
  • Humans
  • Models, Statistical*
  • Publications* / statistics & numerical data
  • Research Personnel

Grant support

No current external funding sources for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.