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Sleeping beauties in meme diffusion


  • Leihan Zhang

    (Beihang University)

  • Ke Xu

    (Beihang University)

  • Jichang Zhao

    () (Beihang University)


A sleeping beauty in diffusion indicates that certain information, whether an idea or innovation, will experience a hibernation period before it undergoes a sudden spike of popularity, and this pattern is found widely in the citation history of scientific publications. However, in this study, we demonstrate that the sleeping beauty is an interesting and unexceptional phenomenon in information diffusion; more inspiring is that there exists two consecutive sleeping beauties in the entire lifetime of a meme’s propagation, which suggests that the information, including scientific topics, search queries or Wikipedia entries, which we call memes, will go unnoticed for a period and suddenly attract some attention, and then it falls asleep again and later wakes up with another unexpected popularity peak. Further exploration of this phenomenon shows that the intervals between two wake-ups follow an exponential distributions, both the rising and falling stage lengths, follow power law distributions, and the second wake-up tends to reach its peak in a shorter period of time. In addition, the total volumes of the two wake-ups have positive correlations. Taking these findings into consideration, an upgraded Bass model is presented to well describe the diffusion dynamics of memes on different media. Our results can help understand the common mechanism behind the propagation of different memes and are instructive towards locating the tipping point in marketing or in finding innovative publications in science.

Suggested Citation

  • Leihan Zhang & Ke Xu & Jichang Zhao, 2017. "Sleeping beauties in meme diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 383-402, July.
  • Handle: RePEc:spr:scient:v:112:y:2017:i:1:d:10.1007_s11192-017-2390-2
    DOI: 10.1007/s11192-017-2390-2

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    References listed on IDEAS

    1. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    2. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    3. Lachance, Christian & Larivière, Vincent, 2014. "On the citation lifecycle of papers with delayed recognition," Journal of Informetrics, Elsevier, vol. 8(4), pages 863-872.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Tibor Braun & Wolfgang Glänzel & András Schubert, 2010. "On Sleeping Beauties, Princes and other tales of citation distributions …," Research Evaluation, Oxford University Press, vol. 19(3), pages 195-202, September.
    6. Robert P. Light & David E. Polley & Katy Börner, 2014. "Open data and open code for big science of science studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1535-1551, November.
    7. Li, Jiang & Shi, Dongbo & Zhao, Star X. & Ye, Fred Y., 2014. "A study of the “heartbeat spectra” for “sleeping beauties”," Journal of Informetrics, Elsevier, vol. 8(3), pages 493-502.
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    Cited by:

    1. Hou, Jianhua & Yang, Xiucai, 2020. "Social media-based sleeping beauties: Defining, identifying and features," Journal of Informetrics, Elsevier, vol. 14(2).
    2. Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha & Ajith Abraham, 2020. "Nature or Science: what Google Trends says," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1367-1385, August.
    3. Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha & Ajith Abraham, 0. "Nature or Science: what Google Trends says," Scientometrics, Springer;Akadémiai Kiadó, vol. 0, pages 1-19.
    4. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.


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