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Bibliometric laws: Empirical flaws of fit

Author

Listed:
  • R. Bailón-Moreno

    (Departamento de Ingeniería Química. Facultad de Ciencias, Campus de Fuentenueva Universidad de Granada)

  • E. Jurado-Alameda

    (Departamento de Ingeniería Química. Facultad de Ciencias, Campus de Fuentenueva Universidad de Granada)

  • R. Ruiz-Baños

    (Departamento de Biblioteconomía y Documentación, Facultad de Biblioteconomía y Documentación, Universidad de Granada)

  • J. P. Courtial

    (Laboratoire de Psychologie - Education - Cognition Développement (LabECD), Université de Nantes)

Abstract

Summary The bibliometric laws of Zipf, Bradford, and Lotka, in their various mathematical expressions, frequently present difficulties in the fitting of empirical values. The empirical flaws of fit take place in the frequency of the words, in the productivity of the authors and the journals, as well as in econometric and demographic aspects. This indicates that the underlying fractal model should be revised, since, as shown, the inverse power equations (of the Zipf-Mandelbrot type) are not adequate, as they need to include exponential terms. These modifications not only affect Bibliometrics and Scientometrics, but also, for the generality of the fractal model, apply to Economy, Demography, and even Natural Sciences in general.

Suggested Citation

  • R. Bailón-Moreno & E. Jurado-Alameda & R. Ruiz-Baños & J. P. Courtial, 2005. "Bibliometric laws: Empirical flaws of fit," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(2), pages 209-229, April.
    • Handle: RePEc:spr:scient:v:63:y:2005:i:2:d:10.1007_s11192-005-0211-5
    DOI: 10.1007/s11192-005-0211-5
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    Citations

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    Cited by:

    1. Montecchi, Matteo & Plangger, Kirk & West, Douglas C., 2021. "Supply chain transparency: A bibliometric review and research agenda," International Journal of Production Economics, Elsevier, vol. 238(C).
    2. Heinrich Behrens & Peter Luksch, 2011. "Mathematics 1868–2008: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 179-194, January.
    3. Mengyang Wang & Lihe Chai, 2018. "Three new bibliometric indicators/approaches derived from keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 721-750, August.
    4. Ruth Zárate Rueda & Yolima Ivonne Beltrán Villamizar & Luis Eduardo Becerra Ardila, 2023. "A Retrospective Approach to Pro-Environmental Behavior from Environmental Education: An Alternative from Sustainable Development," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    5. Claudia Jazmín Galeano-Barrera & María Eugenia Arango Ospina & Edgar Mauricio Mendoza García & Dewar Rico-Bautista & Efrén Romero-Riaño, 2022. "Exploring the Evolution of the Topics and Research Fields of Territorial Development from a Comprehensive Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-31, May.
    6. Vincenzo Basile & Massimiliano Giacalone & Paolo Carmelo Cozzucoli, 2022. "The Impacts of Bibliometrics Measurement in the Scientific Community A Statistical Analysis of Multiple Case Studies," Review of European Studies, Canadian Center of Science and Education, vol. 14(3), pages 1-10, November.
    7. Omwoyo Bosire Onyancha & Dennis N. Ocholla, 2022. "Dispersion of ICT-related subject terms in information and knowledge management publications: A Bradford analysis," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-8, December.
    8. Zahed Bigdeli & Ali Gazni, 2012. "Authors’ sources of information: a new dimension in information scattering," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 505-521, September.
    9. Alain Molinari & Jean-Francois Molinari, 2008. "Mathematical aspects of a new criterion for ranking scientific institutions based on the h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(2), pages 339-356, May.

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