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协同进化网络中的阈值级联动力学

Threshold Cascade Dynamics in Coevolving Networks.

作者信息

Min Byungjoon, San Miguel Maxi

机构信息

Department of Physics, Chungbuk National University, Cheongju 28644, Chungbuk, Republic of Korea.

Research Institute for Nanoscale Science and Technology, Chungbuk National University, Cheongju 28644, Chungbuk, Republic of Korea.

出版信息

Entropy (Basel). 2023 Jun 13;25(6):929. doi: 10.3390/e25060929.

Abstract

We study the coevolutionary dynamics of network topology and social complex contagion using a threshold cascade model. Our coevolving threshold model incorporates two mechanisms: the threshold mechanism for the spreading of a minority state such as a new opinion, idea, or innovation and the network plasticity, implemented as the rewiring of links to cut the connections between nodes in different states. Using numerical simulations and a mean-field theoretical analysis, we demonstrate that the coevolutionary dynamics can significantly affect the cascade dynamics. The domain of parameters, i.e., the threshold and mean degree, for which global cascades occur shrinks with an increasing network plasticity, indicating that the rewiring process suppresses the onset of global cascades. We also found that during evolution, non-adopting nodes form denser connections, resulting in a wider degree distribution and a non-monotonous dependence of cascades sizes on plasticity.

摘要

我们使用阈值级联模型研究网络拓扑结构与社会复杂传播的共同进化动力学。我们的共同进化阈值模型包含两种机制:一种是少数状态(如新观点、想法或创新)传播的阈值机制,另一种是网络可塑性,通过重新连接链路来切断不同状态节点之间的连接来实现。通过数值模拟和平均场理论分析,我们证明了共同进化动力学可以显著影响级联动力学。发生全局级联的参数域,即阈值和平均度,会随着网络可塑性的增加而缩小,这表明重新布线过程会抑制全局级联的发生。我们还发现,在进化过程中,未采用的节点形成更密集的连接,导致度分布更宽,并且级联大小对可塑性的依赖是非单调的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36a1/10297227/4f286c000c5e/entropy-25-00929-g001.jpg

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