Dynamic analysis of a SIDRW rumor propagation model considering the effect of media reports and rumor refuters

Pan, Wenqi; Yan, Weijun; Hu, Yuhan; He, Ruimiao; Wu, Li‐Bing

doi:10.1007/s11071-022-07947-w

Cited by 20 publications

(9 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When there is a high number of such users and limited data availability studying this issue, it could impact the predictive accuracy of the model. Lastly, although our study considers individuals capable of recognizing rumors and refusing their spread, we do not explicitly incorporate a distinct group of rumor-dispelling users as observed in some studies; however, these groups can indeed influence trends in rumor propagation [74].…”

Section: Discussionmentioning

confidence: 99%

Rumor Spreading Model Considering the Roles of Online Social Networks and Information Overload

Fu,

Song,

Feng

2023

IEEE Access

View full text Add to dashboard Cite

Online social networks have become important channels for spreading rumors, and the spreading process in online social networks is influenced by many factors. This study focuses on the problem of rumor spreading through indirect contact, such as non-following/non-friend relationships due to the role of social networks, and considers the phenomenon of rumor isolation from users due to information overload on social networks. The SMQIR rumor-spreading model with five user groups was developed by introducing two parameters: the probability of social network influence and the probability of rumor isolation. The laws of influence of the relevant parameters were investigated using numerical simulations. Furthermore, the reproduction number and equilibrium point of the model were calculated, and the stability of the equilibrium point was analyzed based on the Routh-Hurwitz criterion. The proposed model was evaluated through a comparative analysis with the SIR and SIHR models, while two authentic datasets were employed for validation purposes. This study revealed that online social networks not only intuitively increase the rate of rumor propagation and amplify its reach and magnitude, but also prolong the duration of rumor spreading. Moreover, a higher influence coefficient of online social media leads to an extended period for spreading rumors in terms of speed, scale, and longevity. Conversely, information overload hampers the speed and scale of rumor spreading while simultaneously extending its duration. Additionally, it was observed that information overload may result in the limited exposure to rumors for certain individuals.

show abstract

Section: Discussionmentioning

confidence: 99%

Rumor Spreading Model Considering the Roles of Online Social Networks and Information Overload

Fu,

Song,

Feng

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In this case, the text rumors in the text information base are denoted by W , and the video rumors in the video information base are denoted by V . [39] The ignorant can be exposed to rumors and transformed into a spreader with a certain probability through three channels: contact with spreaders, browsing text rumors and browsing video rumors. In order to propagate rumors, the spreader can create text rumors and upload them to the text information base such as Twitter and WeChat, or create video rumors and upload them to the video information base such as YouTube and Tik Tok, or communicate with the ignorant to propagate rumors.…”

Section: Individual Interactionmentioning

confidence: 99%

An improved ISR-WV rumor propagation model based on multichannels with time delay and pulse vaccination

et al. 2023

View full text Add to dashboard Cite

The rapid development of the Internet has broadened the channels of information dissemination, which makes rumors spread faster, more widely and cause more negative impact. In this paper, an improved ISR-WV rumor propagation model integrating multi-channels is proposed by considering the system time delay, and the influence of different propagation channels on the dynamic process is further analyzed. Moreover, the basic reproduction number R 0, rumor-free equilibrium, and rumor-prevailing equilibrium, as well as their stability, are deduced. Then, an optimal control problem with pulse vaccination is designed. Finally, the validity of the model and theoretical results are verified by numerical simulations and a practical application. The results show that the rumor propagation threshold R 0 is more sensitive to the propagation rate of the information base channel. The shorter the thinking time τ 1 required for the ignorant to react after obtaining the information, the larger the final propagation scale, under this condition, the time delay τ 2 generated by the spreader producing the video is negatively related to the final propagation scale; conversely, a longer τ 1 implies that people tend to be calmer, which can suppress the spread of rumors, under this condition, τ 2 has little effect on the final propagation scale. In addition, the results also prove that timely implementation of the pulse vaccination control strategy of popular science education can effectively control the rumor propagation and reduce its negative impact.

show abstract

“…Zhu et al [15] established a reaction-diffusion rumor propagation model by considering a non-smooth control function to reflect government and media refutation of rumor propagation. Pan et al [16] comprehensively considered population-and media-debunking mechanisms and established a class of SIDRW rumor propagation model. Zhong et al [17] similarly considered the population's refutation behavior of rumor and designed a randomized sedation scheme to suppress rumor propagation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Collaborative Rumor-Debunking Strategies on Virtual-Real Network Layer

Zhong,

Zheng,

Xie

et al. 2024

Mathematics

View full text Add to dashboard Cite

In the era of self-media, the spontaneity and anonymity of information dissemination have led to a surge in rumors, posing significant challenges to cybersecurity. This paper introduces a novel dual-layer VR−SHI1I2R rumor control model for studying collaborative rumor-debunking efforts. Utilizing mathematical modeling and simulation methods, we propose key thresholds for rumor propagation from both theoretical and simulation perspectives, and explore optimal methods for rumor control. Our model is validated with real data from actual cases, confirming its accuracy and the effectiveness. The study shows that without intervention, rumors will spread rapidly. Both constant and dynamically optimized control significantly slow down the spread of rumors. However, dynamic optimization control significantly reduces control costs compared to fixed control schemes. Moreover, we find that controlling only the media layer is insufficient. These findings highlight the importance of meticulous approaches to rumor control in the digital age.

show abstract

Dynamic analysis of a SIDRW rumor propagation model considering the effect of media reports and rumor refuters

Cited by 20 publications

References 34 publications

Rumor Spreading Model Considering the Roles of Online Social Networks and Information Overload

Rumor Spreading Model Considering the Roles of Online Social Networks and Information Overload

An improved ISR-WV rumor propagation model based on multichannels with time delay and pulse vaccination

Multi-Agent Collaborative Rumor-Debunking Strategies on Virtual-Real Network Layer

Contact Info

Product

Resources

About