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The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution

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  • Chun-Ting Zhang

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.

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  • Chun-Ting Zhang, 2013. "The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-8, April.
    • Handle: RePEc:plo:pone00:0059912
    DOI: 10.1371/journal.pone.0059912
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    References listed on IDEAS

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    1. Zhang, Lin & Thijs, Bart & Glänzel, Wolfgang, 2011. "The diffusion of H-related literature," Journal of Informetrics, Elsevier, vol. 5(4), pages 583-593.
    2. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    3. Schreiber, M. & Malesios, C.C. & Psarakis, S., 2012. "Exploratory factor analysis for the Hirsch index, 17 h-type variants, and some traditional bibliometric indicators," Journal of Informetrics, Elsevier, vol. 6(3), pages 347-358.
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    Cited by:

    1. Wei, Shelia X. & Tong, Tong & Rousseau, Ronald & Wang, Wanru & Ye, Fred Y., 2022. "Relations among the h-, g-, ψ-, and p-index and offset-ability," Journal of Informetrics, Elsevier, vol. 16(4).
    2. Jingda Ding & Chao Liu & Goodluck Asobenie Kandonga, 2020. "Exploring the limitations of the h-index and h-type indexes in measuring the research performance of authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1303-1322, March.
    3. Lina Zhou & Uchechukwuka Amadi & Dongsong Zhang, 2020. "Is Self-Citation Biased? An Investigation via the Lens of Citation Polarity, Density, and Location," Information Systems Frontiers, Springer, vol. 22(1), pages 77-90, February.
    4. Shaibu Mohammed & Anthony Morgan & Emmanuel Nyantakyi, 2020. "On the influence of uncited publications on a researcher’s h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1791-1799, March.

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