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Double rank analysis for research assessment

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  • Rodríguez-Navarro, Alonso
  • Brito, Ricardo

Abstract

Reliable methods for the assessment of research success are still in discussion. One method, which uses the likelihood of publishing very highly cited papers, has been validated in terms of Nobel prizes garnered. However, this method cannot be applied widely because it uses the fraction of publications in the upper tail of citation distribution that follows a power law, which includes a low number of publications in most countries and institutions. To achieve the same purpose without restrictions, we have developed the double rank analysis, in which publications that have a low number of citations are also included. By ranking publications by their number of citations from highest to lowest, publications from institutions or countries have two ranking numbers: one for their internal and another one for world positions; the internal ranking number can be expressed as a function of the world ranking number. In log–log double rank plots, a large number of publications fit a straight line; extrapolation allows estimating the likelihood of publishing the highest cited publication. The straight line derives from a power law behavior of the double rank that occurs because citations follow lognormal distributions with values of μ and σ that vary within narrow limits.

Suggested Citation

  • Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Double rank analysis for research assessment," Journal of Informetrics, Elsevier, vol. 12(1), pages 31-41.
    • Handle: RePEc:eee:infome:v:12:y:2018:i:1:p:31-41
    DOI: 10.1016/j.joi.2017.11.004
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    Cited by:

    1. Alonso Rodríguez-Navarro & Ricardo Brito, 2019. "Probability and expected frequency of breakthroughs: basis and use of a robust method of research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 213-235, April.
    2. Brito, Ricardo & Navarro, Alonso Rodríguez, 2021. "The inconsistency of h-index: A mathematical analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    3. Melika Mosleh & Saeed Roshani & Mario Coccia, 2022. "Scientific laws of research funding to support citations and diffusion of knowledge in life science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1931-1951, April.
    4. Gerson Pech & Catarina Delgado, 2020. "Assessing the publication impact using citation data from both Scopus and WoS databases: an approach validated in 15 research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 909-924, November.
    5. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Technological research in the EU is less efficient than the world average. EU research policy risks Europeans’ future," Journal of Informetrics, Elsevier, vol. 12(3), pages 718-731.
    6. Pech, Gerson & Delgado, Catarina, 2021. "Screening the most highly cited papers in longitudinal bibliometric studies and systematic literature reviews of a research field or journal: Widespread used metrics vs a percentile citation-based app," Journal of Informetrics, Elsevier, vol. 15(3).
    7. Gerson Pech & Catarina Delgado, 2020. "Percentile and stochastic-based approach to the comparison of the number of citations of articles indexed in different bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 223-252, April.
    8. Alonso Rodríguez-Navarro & Ricardo Brito, 2022. "The link between countries’ economic and scientific wealth has a complex dependence on technological activity and research policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2871-2896, May.
    9. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2018. "Research assessment by percentile-based double rank analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 315-329.
    10. Gabriel-Alexandru Vȋiu & Mihai Păunescu, 2021. "The lack of meaningful boundary differences between journal impact factor quartiles undermines their independent use in research evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1495-1525, February.
    11. Brito, Ricardo & Rodríguez-Navarro, Alonso, 2019. "Evaluating research and researchers by the journal impact factor: Is it better than coin flipping?," Journal of Informetrics, Elsevier, vol. 13(1), pages 314-324.

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