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Asymmetric inter-layer interactions induce a double transition of information spreading

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  • Yang, Zheng
  • Wu, Jiao
  • He, Jiaxu
  • Xu, Kesheng
  • Zheng, Muhua

Abstract

In recent years, a unique double transition phenomenon was observed under an asymmetric interaction in the epidemic model, where there are two transitions in the phase diagram of the spreading range versus the transmission probability. However, whether the asymmetric interactions exist and induce the double transition of information spreading is not very clear. Based on the global Twitter network communication data analysis, we found that besides the symmetric effects, there are also asymmetric interactions between different continents, indicated by the asymmetric weights of information exchange. To understand how the asymmetry affects the spreading behaviors, we proposed an information spreading model on a synthetic two-layered network and quantified the asymmetric interactions between regions by asymmetric inter-layer transmission probabilities. Interestingly, our results reveal a double transition under a strong inter-layer asymmetry in the phase diagram, which is derived from an asynchronous outbreak within the two layers. In addition, we discovered that depending on the strength of asymmetry, the second transition could alter from continuous to discontinuous. Finally, we developed a theory with asymmetric interactions to explain the numerical results thoroughly. The findings of this work may shed some light on comprehending the information’s secondary outbreaks in the real world.

Suggested Citation

  • Yang, Zheng & Wu, Jiao & He, Jiaxu & Xu, Kesheng & Zheng, Muhua, 2023. "Asymmetric inter-layer interactions induce a double transition of information spreading," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:chsofr:v:171:y:2023:i:c:s0960077923003880
    DOI: 10.1016/j.chaos.2023.113487
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    References listed on IDEAS

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    1. Joel C Miller, 2014. "Epidemics on Networks with Large Initial Conditions or Changing Structure," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-9, July.
    2. Zheng, Muhua & Wang, Wei & Tang, Ming & Zhou, Jie & Boccaletti, S. & Liu, Zonghua, 2018. "Multiple peaks patterns of epidemic spreading in multi-layer networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 135-142.
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