Spreading dynamics on networks: The role of burstiness, topology and non-stationarity

Dávid X. Horváth, János Kertész

    Research output: Contribution to journalArticleScientificpeer-review

    29 Citations (Scopus)
    43 Downloads (Pure)

    Abstract

    Spreading on networks is influenced by a number of factors, including different parts of the inter-event time distribution (IETD), the topology of the network and non-stationarity. In order to understand the role of these factors we study the SI model on temporal networks with different aggregated topologies and different IETDs. Based on analytic calculations and numerical simulations, we show that if the stationary bursty process is governed by power-law IETD, the spreading can be slowed down or accelerated as compared to a Poisson process; the speed is determined by the short time behaviour, which in our model is controlled by the exponent. We demonstrate that finite, so called 'locally tree-like' networks, like the Barabási-Albert networks behave very differently from real tree graphs if the IETD is strongly fat-tailed, as the lack or presence of rare alternative paths modifies the spreading. A further important result is that the non-stationarity of the dynamics has a significant effect on the spreading speed for strongly fat-tailed power-law IETDs, thus bursty processes characterized by small power-law exponents can cause slow spreading in the stationary state but also very rapid spreading, with this heavily dependent on the age of the processes.

    Original languageEnglish
    Article number073037
    Pages (from-to)1-19
    JournalNew Journal of Physics
    Volume16
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA1 Journal article-refereed

    Keywords

    • bursty time series
    • complex networks
    • nonstationary processes
    • spreading phenomena
    • topological bottlenecks

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