可变聚类无标度网络上的谣言免疫策略

Immunity of Rumor on Scale-free Network with Tunable Clustering

提出一种聚类免疫策略,使用改进的经典谣言传播模型,在可变聚类无标度网络上研究其免疫效果.研究发现,聚类免疫的效果随着网络聚类系数的增加而变好.在不同聚类系数下,比较目标免疫、介数免疫、紧密度免疫和聚类免疫的免疫效果发现,无论网络的聚类特性如何,介数免疫始终是几种免疫策略中效果最好的,当网络聚类系数较大时,聚类免疫的效果超过紧密度免疫接近目标免疫,进一步增大网络的聚类系数,聚类免疫的效果超过目标免疫而接近介数免疫.

We present a cluster immunization strategy and study its immune effect on scale-free network with tunable clustering in a modified classic rumor propagation model. Study shows that effect of cluster immunization becomes better with increasing of network clustering coefficient. Several immunization strategies including target immunization, betweenness immunization, closeness immunization and cluster immunization are compared. It shows that betweenness immunization is always the best regardless of network clustering. As a network clustering coefficient is relatively great, effect of cluster immunization is better than that of closeness immunization and close to target immunization. With further increasing network clustering coefficient, cluster immunization exceeds target immunization and approaches to betweenness immunization.