Dynamical study and event-triggered impulsive control of rumor propagation model on heterogeneous social network incorporating delay

2021 ◽  
Vol 145 ◽  
pp. 110806
Author(s):  
Shuzhen Yu ◽  
Zhiyong Yu ◽  
Haijun Jiang ◽  
Jiarong Li
2022 ◽  
Author(s):  
Yuhuai Zhang ◽  
Jianjun Zhu

Abstract In daily lives, when emergencies occur, rumors will spread widely on the Internet. However, it is quite difficult for the netizens to distinguish the truth of the information. The main reasons are the uncertainty of netizens' behavior and attitude, which make the transmission rates of these information among social network groups being not fixed. In this paper, we propose a stochastic rumor propagation model with general incidence function. The model can be described by a stochastic differential equation. Applying the Khasminskii method via a suitable construction of Lyapunov function, we first prove the existence of a unique solution for the stochastic model with probability one. Then we show the existence of a unique ergodic stationary distribution of the rumor model, which exhibits the ergodicity. We also provide some numerical simulations to support our theoretical results. The numerical results give us some possible methods to control rumor propagation that (1)increasing noise intensity can effectively reduce rumor propagation when $\widehat{\mathcal{R}}_{0}>1$. That is, after rumors spread widely on social network platforms, government intervention and authoritative media coverage will interfere with netizens' opinions, thus reducing the degree of rumor propagation; (2) Speed up the rumor refutation, intensify efforts to refute rumors, and improve the scientific quality of netizen(i.e. increase the value of $\beta$ and decrease the value of $\alpha$ and $\gamma$ ) can effectively curb rumor propagation.


2017 ◽  
Vol 5 (6) ◽  
pp. 571-584 ◽  
Author(s):  
Jianhong Chen ◽  
Qinghua Song ◽  
Zhiyong Zhou

AbstractTo simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.


Author(s):  
Yunpeng Xiao ◽  
Wen Li ◽  
Shuai Qiang ◽  
Qian Li ◽  
Hanchun Xiao ◽  
...  

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