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Information spreading on multirelational networks

Author

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  • Wang, Jun
  • Zhou, Bin
  • Wang, Wei

Abstract

The spreading dynamics of information has attracted much attention in recent years, yet the effects of multirelational networks have not been systematically studied. In this paper, we propose an information spreading model on multirelational networks, in which assumes that the information transmitted through friend relationships induces the susceptible nodes to become infected, while the information transmitted through hostile relationships proves vaccination to susceptible nodes. Through extensive numerical simulations, we find that the information spreading is suppressed on multirelational networks especially when the average degree of hostile network is large. However the information outbreak threshold is only dependent on the topology of friend network. The above phenomena are quantificationally predicted by a generalized edge-based compartmental theory.

Suggested Citation

  • Wang, Jun & Zhou, Bin & Wang, Wei, 2019. "Information spreading on multirelational networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 21-28.
    • Handle: RePEc:eee:phsmap:v:517:y:2019:i:c:p:21-28
    DOI: 10.1016/j.physa.2018.10.059
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    References listed on IDEAS

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    1. Cai, Meng & Wang, Wei & Cui, Ying & Stanley, H. Eugene, 2018. "Multiplex network analysis of employee performance and employee social relationships," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1-12.
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    Cited by:

    1. Yue Dong & Jiepeng Wang & Tingqiang Chen, 2019. "Price Linkage Rumors in the Stock Market and Investor Risk Contagion on Bilayer-Coupled Networks," Complexity, Hindawi, vol. 2019, pages 1-21, April.

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