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Temporal Networks pp 161–174Cite as

Spreading Dynamics Following Bursty Activity Patterns

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Part of the book series: Understanding Complex Systems ((UCS))

Abstract

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Recent empirical evidence indicates that the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. In this work we analyze how this bursty dynamics impacts the dynamics of spreading processes in computer and social systems. We demonstrate that the non-Poisson nature of the contact dynamics results in prevalence decay times significantly larger than predicted by the standard Poisson process based models. Thanks to this slow dynamics the spreading entity, namely a virus, rumor, etc., can persist in the system for long times.

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Author information

Authors and Affiliations

  1. Department of Radiation Oncology and Center for Systems Biology, The Cancer Institute of New Jersey, UMDNJ-RWJMS, 195 Little Albany St, New Brunswick, NJ, 08903, USA

    Alexei Vazquez

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  1. Alexei Vazquez
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Correspondence to Alexei Vazquez .

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Editors and Affiliations

  1. Ice Lab, Department of Physics, Umeå University, Ice Lab, 3rd floor, NA wing, Naturvetarhuset, Umeå, 901 87, Sweden

    Petter Holme

  2. and Computational Sciences (BECS), Department of Biomedical Engineering, Aalto University, Rakentajanaukio, Otaniemi campus 2, Aalto, 00076, Finland

    Jari Saramäki

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Vazquez, A. (2013). Spreading Dynamics Following Bursty Activity Patterns. In: Holme, P., Saramäki, J. (eds) Temporal Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36461-7_8

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  • DOI: https://doi.org/10.1007/978-3-642-36461-7_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36460-0

  • Online ISBN: 978-3-642-36461-7

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