【摘要】 为了探究实际情形中公共危机伪信息的扩散及免疫规律,构建了ER-ER随机双层网络拓扑结构,并基于SIR模型得出了该网络中伪信息扩散的阈值.依据扩散阈值选取相应的扩散速率,利用Netlogo仿真研究了双层网络间的相互联系对伪信息免疫的影响,结果表明双层网络相互联系对伪信息免疫存在双重影响作用,即在单一免疫情况下,表现为扩散抑制;双重免疫下,表现为扩散促进.进一步基于该相互联系,得出了公共危机双层网络伪信息扩散的综合免疫阈值,发现其相较各子网分别免疫有较大幅度的增加.更多还原

【Abstract】 In order to investigate the diffusion and immunization law of false information in public crisis in reality, a two-layered ER-ER random network topology is developed. Further, based on SIR model, the theoretical threshold of false information diffusion in two-layered networks is derived. Setting appropriate spreading rates in the two-layered network according to the threshold, the influence of the interrelationships between the networks on the immunization of false information is studied using Netlogo simulation. The results show that there is a dual influence on immunization. In the case of single-network immunization, there is a negative effect on diffusion, while in the case of both immunization there is a positive effect. Furthermore,the integrated immunization threshold is calculated in two-layered networks considering the relationships. It is found that there is a large increase in the threshold compared with separate immunization.更多还原