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The influence of heterogeneity of adoption thresholds on limited information spreading

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  • Yang, Qiwen
  • Zhu, Xuzhen
  • Tian, Yang
  • Wang, Guanglu
  • Zhang, Yuexia
  • Chen, Lei

Abstract

The spreading process of information on complex networks has been widely explored. In fact, different individuals in a network usually hold different standards for information adoption. Considering the heterogeneity of adoption thresholds, this study constructs a two-layer network model with limited contacts. The adoption threshold of a node is related to its degree and a parameter obeying truncated normal distribution. This study also proposes a partition theory based on edges to analyze the mechanism of information dissemination quantitatively. Experiments find that increasing the mean of parameters can inhibit information from spreading, and the effect of the standard deviation of parameters on information dissemination depends on the mean of parameters. For instance, when the mean of parameters is a low value, as the standard deviation of parameters increases, the information outbreak size will decrease. On the other hand, the information outbreak size will increase continuously with increased propagation probability. If the mean of parameters is high, the information outbreak size will increase first and then decrease with the increment in the standard deviation of parameters. The theoretical predictions of this study are in good agreement with the numerical simulations.

Suggested Citation

  • Yang, Qiwen & Zhu, Xuzhen & Tian, Yang & Wang, Guanglu & Zhang, Yuexia & Chen, Lei, 2021. "The influence of heterogeneity of adoption thresholds on limited information spreading," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    • Handle: RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321005373
    DOI: 10.1016/j.amc.2021.126448
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    References listed on IDEAS

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    1. Peng, Hao & Peng, Wangxin & Zhao, Dandan & Wang, Wei, 2020. "Impact of the heterogeneity of adoption thresholds on behavior spreading in complex networks," Applied Mathematics and Computation, Elsevier, vol. 386(C).
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    Cited by:

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