ArticleApplied mathematics and computation2021
Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading.
Article in Applied mathematics and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Examining the impact of emotion-driven resource allocation on information-behavior-disease coupling dynamics.Infectious Disease Modelling · 2026Article
- Social, mobility and contact networks in shaping health behaviours and infectious disease dynamics: a scoping review.Infectious diseases of poverty · 2025Article
- Dynamic analysis and optimal control of competitive information dissemination model.Scientific reports · 2024Article
- Information propagation dynamics on heterogeneous-homogeneous coupling bi-layer networks.Scientific reports · 2024Article
- Effects of official information and rumor on resource-epidemic coevolution dynamics.Journal of King Saud University. Computer and information sciences · 2022Article
- The popularity of contradictory information about COVID-19 vaccine on social media in China.Computers in human behavior · 2022Article
- Novelty in Public Health and Epidemiology Informatics.Yearbook of medical informatics · 2022Article
- Fractional-order rumor propagation model with memory effect.Social network analysis and mining · 2022Article
- A probabilistic approach toward evaluation of Internet rumor on COVID.Soft computing · 2022Article
- COVID-19-Related Rumor Content, Transmission, and Clarification Strategies in China: Descriptive Study.Journal of medical Internet research · 2021Article
- A rumor reversal model of online health information during the Covid-19 epidemic.Information processing & management · 2021Article
- A particle swarm optimization approach for predicting the number of COVID-19 deaths.Scientific reports · 2021Review
- Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model.Applied mathematics and computation · 2021Article
- The Public Servants' Response When Facing Pandemic: The Role of Public Service Motivation, Accountability Pressure, and Emergency Response Capacity.Healthcare (Basel, Switzerland) · 2021Article
- Impact of information diffusion on epidemic spreading in partially mapping two-layered time-varying networks.Nonlinear dynamics · 2021Article
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Authors and funding
3 authors.
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Abstract
The interaction between epidemic spreading and information diffusion is an interdisciplinary research problem. During an epidemic, people tend to take self-protective measures to reduce the infection risk. However, with the diffusion of rumor, people may be difficult to make an appropriate choice. How to reduce the negative impact of rumor and to control epidemic has become a critical issue in the social network. Elaborate mathematical model is instructive to understand such complex dynamics. In this paper, we develop a two-layer network to model the interaction between the spread of epidemic and the competitive diffusions of information. The results show that knowledge diffusion can eradicate both rumor and epidemic, where the penetration intensity of knowledge into rumor plays a vital role. Specifically, the penetration intensity of knowledge significantly increases the thresholds for rumor and epidemic to break out, even when the self-protective measure is not perfectly effective. But eradicating rumor shouldn't be equated with eradicating epidemic. The epidemic can be eradicated with rumor still diffusing, and the epidemic may keep spreading with rumor being eradicated. Moreover, the communication-layer network structure greatly affects the spread of epidemic in the contact-layer network. When people have more connections in the communication-layer network, the knowledge is more likely to diffuse widely, and the rumor and epidemic can be eradicated more efficiently. When the communication-layer network is sparse, a larger penetration intensity of knowledge into rumor is required to promote the diffusion of knowledge.
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