小世界超网络传播模型及实证分析

Propagation Model and Empirical Analysis of Small-World Hypernetworks

  • 摘要: 借鉴WS小世界网络的构造算法,在超网络(也称为超图)中加入超边随机重连,构建小世界超网络模型。以该模型为信息传播的底层网络,提出小世界超网络SIR信息传播模型,仿真模拟超边随机重连概率、超网络中的邻居节点数量以及传播率、恢复率等参数对超网络的信息传播过程影响,并与普通网络中的传播过程进行了对比分析,发现超网络中的信息传播速度更快,波及范围更广。进一步,在3类实证超网络上验证了超网络的小世界特性及信息传播规律。在万物互联时代,世界变得更小的背景下,对现实世界中更为复杂的信息与疾病传播机制的深入研究具有一定的借鉴意义。

     

    Abstract: The construction algorithm of small-world (WS) network was adopted to add randomly rewired hyperedges to the hypernetwork (also called hypergraph) to construct a small-world hypernetwork model. This model was used as the underlying network for information propagation, and a small-world SIR information propagation model in hypernetworks was proposed. A simulation was conducted to investigate the influences of hyperedge rewiring probability, number of neighboring nodes in the hypernetwork, and propagation and recovery rates on the hypernetwork's information propagation process. A comparative analysis is performed with the information propagation process in a normal network, and it is found that information spreads faster and reaches a wider range in hypernetworks. Furthermore, the small-world characteristics and information propagation rules of hypernetworks are verified on three types of empirical hypernetworks. In the era of everything interconnected, where the world is becoming smaller, there is certain reference significance for the in-depth study of more complex information and disease propagation mechanisms in the real world.

     

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