论文标题
随机网络中的信息传播
Information Propagation in Stochastic Networks
论文作者
论文摘要
在本文中，开发了基于网络的随机信息传播模型。信息流是通过概率微分方程系统建模的。这些方程的数值解会导致通知节点的预期数量作为时间的函数，并揭示了节点的程度及其接收时间之间的关系。通过蒙特卡洛网络模拟通过分析无标度和ERDOS-RENYI网络中信息传播的分析，模型的有效性是合理的。已经发现，与广泛使用的基于网络的SI平均模型相比，开发的模型提供了更准确的结果，尤其是在稀疏网络中。
In this paper, a network-based stochastic information propagation model is developed. The information flow is modeled by a probabilistic differential equation system. The numerical solution of these equations leads to the expected number of informed nodes as a function of time and reveals the relationship between the degrees of the nodes and their reception time. The validity of the model is justified by Monte Carlo network simulation through the analysis of information propagation in scale-free and Erdos-Renyi networks. It has been found that the developed model provides more accurate results compared to the widely used network-based SI mean-field model, especially in sparse networks.
