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The H-index paradox: your coauthors have a higher H-index than you do

Author

Listed:
  • Fabrício Benevenuto

    (Federal University of Minas Gerais)

  • Alberto H. F. Laender

    (Federal University of Minas Gerais)

  • Bruno L. Alves

    (Federal University of Minas Gerais)

Abstract

One interesting phenomenon that emerges from the typical structure of social networks is the friendship paradox. It states that your friends have on average more friends than you do. Recent efforts have explored variations of it, with numerous implications for the dynamics of social networks. However, the friendship paradox and its variations consider only the topological structure of the networks and neglect many other characteristics that are correlated with node degree. In this article, we take the case of scientific collaborations to investigate whether a similar paradox also arises in terms of a researcher’s scientific productivity as measured by her H-index. The H-index is a widely used metric in academia to capture both the quality and the quantity of a researcher’s scientific output. It is likely that a researcher may use her coauthors’ H-indexes as a way to infer whether her own H-index is adequate in her research area. Nevertheless, in this article, we show that the average H-index of a researcher’s coauthors is usually higher than her own H-index. We present empirical evidence of this paradox and discuss some of its potential consequences.

Suggested Citation

  • Fabrício Benevenuto & Alberto H. F. Laender & Bruno L. Alves, 2016. "The H-index paradox: your coauthors have a higher H-index than you do," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 469-474, January.
    • Handle: RePEc:spr:scient:v:106:y:2016:i:1:d:10.1007_s11192-015-1776-2
    DOI: 10.1007/s11192-015-1776-2
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    References listed on IDEAS

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    1. Lutz Bornmann & Hans-Dieter Daniel, 2005. "Does the h-index for ranking of scientists really work?," Scientometrics, Springer;Akadémiai Kiadó, vol. 65(3), pages 391-392, December.
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    Cited by:

    1. Kong, Xiangjie & Mao, Mengyi & Jiang, Huizhen & Yu, Shuo & Wan, Liangtian, 2019. "How does collaboration affect researchers’ positions in co-authorship networks?," Journal of Informetrics, Elsevier, vol. 13(3), pages 887-900.
    2. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
    3. Brandão, Luana Carneiro & Soares de Mello, João Carlos Correia Baptista, 2019. "A multi-criteria approach to the h-index," European Journal of Operational Research, Elsevier, vol. 276(1), pages 357-363.
    4. Shen, Hongquan & Cheng, Ying & Ju, Xiufang & Xie, Juan, 2022. "Rethinking the effect of inter-gender collaboration on research performance for scholars," Journal of Informetrics, Elsevier, vol. 16(4).
    5. João Mateus Freitas Veneroso & Marlon Dias & Alberto Ueda & Sabir Ribas & Berthier Ribeiro-Neto & Nivio Ziviani & Edmundo Souza e Silva, 2019. "P-score: a reputation bibliographic index that complements citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1269-1291, December.

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