Abstract：Based on the rumor spreading characteristics of classic infection model (SIR) on real online social networks, this paper divides the OSN users into 6 different kinds of people, including the ignorants, the knowns, the believers, the spreaders, the temporary stiflers and the permanent stiflers. Taking into account the reality that people enhance their believing level when they contact with the same rumor constantly, this paper combines the positive effects of social reinforcement with the theory of complex networks to construct an improved rumor propagation model of online social network in the scale-free network environment considering tunable clustering. Numerical simulation results show that the rumor spreading range and ability will increase in the rumor first-believing probability, the degree of initial spreader nodes, the density of isolated node and the positive effects of social reinforcement; but on the contrary, it will be restrained by the increase of cluster coefficient. The improved rumor propagation model we proposed well fits the rumor spreading characteristics on real online social network and some theory references will be applied to manage and control Internet rumors.
朱张祥, 刘咏梅. 在线社交网络谣言传播的仿真研究——基于聚类系数可变的无标度网络环境[J]. 复杂系统与复杂性科学, 2016, 13(2): 74-82.
ZHU Zhangxiang, LIU Yongmei. Simulation Study of Propagation of Rumor in Online Social Network Based on Scale-Free Network with Tunable Clustering[J]. Complex Systems and Complexity Science, 2016, 13(2): 74-82.
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