Dynamic Analysis and Optimal Control of Rumor Propagation Model with Reporting Effect

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

doi:10.1155/2022/5503137

Cited by 2 publications

(1 citation statement)

References 44 publications

(57 reference statements)

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“…Del Vicario et al [24] explored the mechanism and influencing factors of rumor propagation on the internet by analyzing data on Twitter social networks. Pan et al [25] proposed a rumor spreading model based on an infectious disease model, taking into account the impact of media coverage on the speed and scope of rumor spreading, and analyzed the dynamic evolution process of rumor propagation through mathematical modeling and simulation experiments. These studies provide important reference and guidance for us to better understand rumor propagation, and also help to develop effective response measures.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Analysis and Optimal Control of Rumor Victims Affected by Positive Information on the Internet

Li,

Hu,

Meng

2023

Preprint

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The spread of rumors can have a profound impact on people’s physical and mental health, as well as social stability and development. From the perspective of rumor victims, this article proposes a Susceptible-Infected-Victims-Removed (SQVR) model which combines positive information dissemination on the internet. The model considers the impact of positive information on both rumor victims and spreaders on the internet, and proves the existence and stability of the model’s equilibrium point. Based on the selection of optimized control variables, a control strategy was designed to effectively suppress the spread of rumors and reduce the number of victims. Numerical simulations confirmed the theoretical analysis results and the influence of the system on the changes in control parameters. Furthermore, the SQV R model was compared with the SIR model, and the research indicated that the SQV R model reached equilibrium faster than the SIR model. Expanding the scope of positive information dissemination can effectively suppress the spread of rumors, rapidly free the victims of rumors from their predicament, and reduce the harm caused by rumors.

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Section: Introductionmentioning

confidence: 99%

Dynamic Analysis and Optimal Control of Rumor Victims Affected by Positive Information on the Internet

Li,

Hu,

Meng

2023

Preprint

Self Cite

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Dynamic analysis and optimal control of rumor propagation models considering different education levels and hesitation mechanisms

Wang,

Kang,

2024

MATH

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<abstract><p>The spread of rumors has an important impact on the production and life of human society. Moreover, in the process of rumor propagation, individuals with different educational levels show different degrees of trust and ability to spread rumors. Therefore, a new rumor propagation model was established, which considers the influence of education level on rumor propagation. Initially, the basic reproduction number of the model was calculated. Then, we analyzed the existence and stability of the rumor equilibrium point. Next, based on the principle of Pontryagin's maximum value, we obtained a control strategy, which effectively reduced the spread of rumors. Numerical simulations verified the results of theoretical analysis. The results showed that the higher the education level of the population, the slower the spread of rumors to a certain extent, but it could not prevent the spread of rumors. In addition, through the support of the government and the propaganda of the official media, strengthening education can improve people's education level to a certain extent, and then minimize the speed of rumor propagation.</p></abstract>

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Dynamic Analysis and Optimal Control of Rumor Propagation Model with Reporting Effect

Cited by 2 publications

References 44 publications

Dynamic Analysis and Optimal Control of Rumor Victims Affected by Positive Information on the Internet

Dynamic Analysis and Optimal Control of Rumor Victims Affected by Positive Information on the Internet

Dynamic analysis and optimal control of rumor propagation models considering different education levels and hesitation mechanisms

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