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Emergence of scaling in complex substitutive systems

Author

Listed:
  • Ching Jin

    (Northwestern University
    Northwestern University
    Northeastern University)

  • Chaoming Song

    (University of Miami)

  • Johannes Bjelland

    (Telenor Research and Development)

  • Geoffrey Canright

    (Telenor Research and Development)

  • Dashun Wang

    (Northwestern University
    Northwestern University
    Northwestern University)

Abstract

Diffusion processes are central to human interactions. One common prediction of the current modelling frameworks is that initial spreading dynamics follow exponential growth. Here we find that, for subjects ranging from mobile handsets to automobiles and from smartphone apps to scientific fields, early growth patterns follow a power law with non-integer exponents. We test the hypothesis that mechanisms specific to substitution dynamics may play a role, by analysing unique data tracing 3.6 million individuals substituting different mobile handsets. We uncover three generic ingredients governing substitutions, allowing us to develop a minimal substitution model, which not only explains the power-law growth, but also collapses diverse growth trajectories of individual constituents into a single curve. These results offer a mechanistic understanding of power-law early growth patterns emerging from various domains and demonstrate that substitution dynamics are governed by robust self-organizing principles that go beyond the particulars of individual systems.

Suggested Citation

  • Ching Jin & Chaoming Song & Johannes Bjelland & Geoffrey Canright & Dashun Wang, 2019. "Emergence of scaling in complex substitutive systems," Nature Human Behaviour, Nature, vol. 3(8), pages 837-846, August.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:8:d:10.1038_s41562-019-0638-y
    DOI: 10.1038/s41562-019-0638-y
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    Cited by:

    1. Servedio, Vito D.P. & Ferreira, Márcia R. & Reisz, Niklas & Costas, Rodrigo & Thurner, Stefan, 2023. "Scale-free growth in regional scientific capacity building explains long-term scientific dominance," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.

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