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Science and Facebook: The same popularity law!

Author

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  • Zoltán Néda
  • Levente Varga
  • Tamás S Biró

Abstract

The distribution of scientific citations for publications selected with different rules (author, topic, institution, country, journal, etc…) collapse on a single curve if one plots the citations relative to their mean value. We find that the distribution of “shares” for the Facebook posts rescale in the same manner to the very same curve with scientific citations. This finding suggests that citations are subjected to the same growth mechanism with Facebook popularity measures, being influenced by a statistically similar social environment and selection mechanism. In a simple master-equation approach the exponential growth of the number of publications and a preferential selection mechanism leads to a Tsallis-Pareto distribution offering an excellent description for the observed statistics. Based on our model and on the data derived from PubMed we predict that according to the present trend the average citations per scientific publications exponentially relaxes to about 4.

Suggested Citation

  • Zoltán Néda & Levente Varga & Tamás S Biró, 2017. "Science and Facebook: The same popularity law!," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-11, July.
    • Handle: RePEc:plo:pone00:0179656
    DOI: 10.1371/journal.pone.0179656
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    References listed on IDEAS

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    1. Pierre Azoulay, 2012. "Turn the scientific method on ourselves," Nature, Nature, vol. 484(7392), pages 31-32, April.
    2. Michal Brzezinski, 2015. "Power laws in citation distributions: evidence from Scopus," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 213-228, April.
    3. Arnab Chatterjee & Asim Ghosh & Bikas K Chakrabarti, 2016. "Universality of Citation Distributions for Academic Institutions and Journals," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-11, January.
    4. C. O. S. Sorzano & J. Vargas & G. Caffarena-Fernández & A. Iriarte, 2014. "Comparing scientific performance among equals," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1731-1745, December.
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    Cited by:

    1. Siudem, Grzegorz & Nowak, Przemysław & Gagolewski, Marek, 2022. "Power laws, the Price model, and the Pareto type-2 distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Biró, Tamás S. & Telcs, András & Józsa, Máté & Néda, Zoltán, 2023. "Gintropic scaling of scientometric indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    3. Ilda Inácio & José Velhinho, 2022. "Comments on Mathematical Aspects of the Biró–Néda Model," Mathematics, MDPI, vol. 10(4), pages 1-10, February.
    4. Mrowinski, Maciej J. & Gagolewski, Marek & Siudem, Grzegorz, 2022. "Accidentality in journal citation patterns," Journal of Informetrics, Elsevier, vol. 16(4).
    5. Lukas Schneider & Johannes Scholten & Bulcsú Sándor & Claudius Gros, 2021. "Charting closed-loop collective cultural decisions: from book best sellers and music downloads to Twitter hashtags and Reddit comments," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(8), pages 1-13, August.
    6. Lin Hu & Anqi Li & Xu Tan, 2021. "A Rational Inattention Theory of Echo Chamber," Papers 2104.10657, arXiv.org, revised Jun 2024.
    7. Tóth, István & Lázár, Zsolt I. & Varga, Levente & Járai-Szabó, Ferenc & Papp, István & Florian, Răzvan V. & Ercsey-Ravasz, Mária, 2021. "Mitigating ageing bias in article level metrics using citation network analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    8. Biró, T.S. & Néda, Z., 2018. "Unidirectional random growth with resetting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 335-361.
    9. Cena, Anna & Gagolewski, Marek & Siudem, Grzegorz & Żogała-Siudem, Barbara, 2022. "Validating citation models by proxy indices," Journal of Informetrics, Elsevier, vol. 16(2).

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