The dynamics analysis of a rumor propagation model in online social networks

2019 ◽  
Vol 520 ◽  
pp. 118-137 ◽  
Author(s):  
Linhe Zhu ◽  
Mengxue Liu ◽  
Yimin Li
2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.


IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 6105-6120 ◽  
Author(s):  
Zhenhua Tan ◽  
Jingyu Ning ◽  
Yuan Liu ◽  
Xingwei Wang ◽  
Guangming Yang ◽  
...  

2018 ◽  
Vol 29 (08) ◽  
pp. 1850068 ◽  
Author(s):  
Yaming Zhang ◽  
Yanyuan Su ◽  
Weigang Li ◽  
Haiou Liu

Rumor propagation and refutation form an important issue for spreading dynamics in online social networks (OSNs). In this paper, we introduce a novel two-stage rumor propagation and refutation model with time effect for OSNs. The dynamical mechanism of rumor propagation and refutation with time effect is investigated deeply. Then a two-stage model and the corresponding mean-field equations in both homogeneous and heterogeneous networks are obtained. Monte Carlo simulations are conducted to characterize the dynamics of rumor propagation and refutation in both Watts–Strogatz network and Barabási–Albert network. The results show that heterogeneous networks yield the most effective rumor and anti-rumor spreading. Besides, the sooner authority releases anti-rumor and the more attractive anti-rumor is, the less rumor influence is. What’s more, these findings suggest that individuals’ ability to control themselves and identify rumor accurately should be improved to reduce negative impact of rumor effectively. The results are helpful to understand better the mechanism of rumor propagation and refutation in OSNs.


2016 ◽  
Vol 43 (3) ◽  
pp. 342-355 ◽  
Author(s):  
Liyuan Sun ◽  
Yadong Zhou ◽  
Xiaohong Guan

Understanding information propagation in online social networks is important in many practical applications and is of great interest to many researchers. The challenge with the existing propagation models lies in the requirement of complete network structure, topic-dependent model parameters and topic isolated spread assumption, etc. In this paper, we study the characteristics of multi-topic information propagation based on the data collected from Sina Weibo, one of the most popular microblogging services in China. We find that the daily total amount of user resources is finite and users’ attention transfers from one topic to another. This shows evidence on the competitions between multiple dynamical topics. According to these empirical observations, we develop a competition-based multi-topic information propagation model without social network structure. This model is built based on general mechanisms of resource competitions, i.e. attracting and distracting users’ attention, and considers the interactions of multiple topics. Simulation results show that the model can effectively produce topics with temporal popularity similar to the real data. The impact of model parameters is also analysed. It is found that topic arrival rate reflects the strength of competitions, and topic fitness is significant in modelling the small scale topic propagation.


2020 ◽  
Vol 30 (12) ◽  
pp. 2050175
Author(s):  
Linhe Zhu ◽  
Xuewei Wang ◽  
Zhengdi Zhang ◽  
Shuling Shen

In this paper, we improve an Ignorant-Lurker-Spreader-Removal (ILSR) rumor propagation model as in [Yang et al., 2019] in social networks with consideration to Logistic growth and two discrete delays. First, we prove the existence of equilibrium points by calculating the basic reproduction number according to the next generation matrix. Regarding the two discrete delays as bifurcating parameters, the local asymptotical stability and Hopf bifurcation of the positive equilibrium point are discussed for six different scenarios by analyzing the characteristic equations of linearized systems. Applying the normal form theory and the center manifold theorem, some important conclusions about the stability and direction of bifurcating periodic solution are given when the two time delays are equal. Subsequently we study the global stability of the equilibrium points by constructing Lyapunov functions when the two delays disappear. Finally, we verify the conclusions through numerical simulations and perform sensitivity analysis on the basic reproduction numbers.


Author(s):  
Yuhuai Zhang ◽  
Jianjun Zhu

Abstract The rapid development of information society highlights the important role of rumors in social communication, and its propagation has a significant impact on human production and life. The investigation of the influence of uncertainty on rumor propagation is an important issue in the current communication study. Due to incomprehension about others and the stochastic properties of the users' behavior, the transmission rate between individuals on social network platforms is usually not a constant value. In this paper, we propose a new rumor propagation model on homogeneous social networks from the deterministic structure to the stochastic structure. Firstly, a unique global positive solution of rumor propagation model is obtained. Then, we verify that the extinction and persistence of stochastic rumor propagation model are restricted by some conditions. IfR *0< 1 and the noise intensity s i (i = 1,2,3) satisfies some certain conditions, rumors will extinct with a probability one. If R *0 > 1, rumor-spreading individuals will continue to exist in the system, which means the rumor will prevail for a long time. Finally, through some numerical simulations, the validity and rationality of the theoretical analysis are effectively verified.


2016 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Junjie Chen ◽  
Weili Wu ◽  
Ailian Wang

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 62612-62621 ◽  
Author(s):  
Youke Wu ◽  
Haiyang Huang ◽  
Junjie Zhao ◽  
Cheng Wang ◽  
Tian Wang

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yun Li ◽  
Jiakun Wang

PurposeIn modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).Design/methodology/approachFirst, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.FindingsThe results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.Practical implicationsThis study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.Originality/valueThis research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.


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