论文标题
混合网络中的信息传播模型
Information Propagation Model in Hybrid Networks
论文作者
论文摘要
实际上，不可能使用单个动态模型来描述真实网络或其消息传播过程的拓扑。为了解决这个问题，我们构建了一个基于无标度（SF），小世界（SW）功能的新混合网络模型，该模型与真实网络尽可能紧密地发挥作用。杂种繁殖模型是由易感感染感染的（SIS），易感感染的（SIR）和易感感染感染的可易感（SIRS）模型以任意比例混合的。该模型应用了大片效应和隐式节点边缘的概念，以反映爆炸性传播，作为信息传播的重要特征。模拟混合网络的新模型的理论分析和推导表明，网络分布紧密遵循幂律。使用改进的相似性函数来定义与实际网络案例的亲密程度，所提出的模型被证明是有效的，并且非常接近真实的网络。
It is in practice impossible to describe the topology of a real network or its message propagation process using a single dynamic model. To address this issue, we constructed a new hybrid network model based on scale-free (SF), small-world (SW) features that functions as closely as possible to a real network. And the hybrid propagation model is constructed with susceptible-infected-susceptible (SIS), susceptible-infected-recovered (SIR) and susceptible-infected-recovered-susceptible (SIRS) model mixed in arbitrary proportions. The model applies the concepts of blockbuster effect and implicit node edges to reflect explosive spread as a significant characteristic of information propagation. A theoretical analysis and derivation of the new model in which hybrid networks were simulated revealed that the network degree distribution closely follows a power law. Using an improved similarity function to define the degree of closeness to real network cases, the proposed model was shown to be valid and very close to a real network.
