论文标题
病毒传播和选民模型在带有多种类型节点的随机图上
Virus spread and voter model on random graphs with multiple type nodes
论文作者
论文摘要
在建模流行病或在线社交网络上的信息传播时，至关重要的是不仅包括可以传播感染的连接密度，还包括易感性的可变性。不同的人有不同的机会被疾病感染（由于年龄或一般的健康状况），或者在意见的情况下，人们更容易被他人说服，或者更强烈地分享他们的意见。这项工作的目的是检查多种类型的节点对各种随机图的影响，例如erdős--rényi随机图，优先附件随机图和几何随机图。我们使用了两种模型进行动态：带有疫苗接种的SEIR模型和一种交换意见的选民模型。在第一种情况下，除其他情况下，将各种疫苗接种策略相互比较，而在第二种情况下，我们研究了七杆初始配置，以找到应放置最有效节点以传播意见的关键位置。
When modelling epidemics or spread of information on online social networks, it is crucial to include not just the density of the connections through which infections can be transmitted, but also the variability of susceptibility. Different people have different chance to be infected by a disease (due to age or general health conditions), or, in case of opinions, ones are easier to be convinced by others, or stronger at sharing their opinions. The goal of this work is to examine the effect of multiple types of nodes on various random graphs such as Erdős--Rényi random graphs, preferential attachment random graphs and geometric random graphs. We used two models for the dynamics: SEIR model with vaccination and a version of voter model for exchanging opinions. In the first case, among others, various vaccination strategies are compared to each other, while in the second case we studied sevaral initial configurations to find the key positions where the most effective nodes should be placed to disseminate opinions.
