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Updated: Jun 29, 2025
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Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication
Published on: December 2, 2011
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A multilayer network model of interaction between rumor propagation and media influence
Shidong Zhai1, Haolin Li1, Shuaibing Zhu2
1School of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Chaos (Woodbury, N.Y.)
|April 1, 2024
Summary
This study models media and crowd interactions in rumor spread. Findings show media influence wanes without feedback, reducing rumor dissemination, while feedback loops decrease both media influence and rumor spread.
Area of Science:
- Social network analysis
- Information science
- Computational social science
Background:
- Rumor dissemination is influenced by media, and media influence is affected by public feedback.
- Understanding this dynamic interaction is crucial for managing information flow.
Purpose of the Study:
- To develop and analyze a two-layer network model of rumor-media interaction.
- To investigate the impact of media influence and feedback on rumor spread dynamics.
Main Methods:
- Constructed a two-layer network model combining the susceptibility-apathy-propagation-recovery (SI) model for crowd behavior and a flow model for media influence.
- Performed sensitivity analysis on key parameters, focusing on the basic reproduction number.
- Validated the model using a real-world rumor dataset.
Main Results:
- Unilateral media influence without feedback leads to a decrease in media influence and rumor spread.
- Media accepting feedback without direct influence initially reduces both media influence and rumor spread.
- The model accurately simulates real-world rumor propagation with an R-squared value of 0.9606.
Conclusions:
- The interplay between media influence and public feedback significantly shapes rumor dynamics.
- The developed model provides a robust framework for understanding and predicting rumor propagation in social networks.
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