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Modeling the competitive diffusions of rumor and knowledge and the impacts on epidemic spreading.
Huang, He; Chen, Yahong; Ma, Yefeng.
  • Huang H; School of Economics and Management, China University of Geosciences (Beijing), Beijing 100083, China.
  • Chen Y; School of Economics and Management, Tsinghua University, Beijing 100084, China.
  • Ma Y; School of Information, Beijing Wuzi University, Beijing 101149, China.
Appl Math Comput ; 388: 125536, 2021 Jan 01.
Article in English | MEDLINE | ID: covidwho-670600
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Appl Math Comput Year: 2021 Document Type: Article Affiliation country: J.amc.2020.125536

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study Language: English Journal: Appl Math Comput Year: 2021 Document Type: Article Affiliation country: J.amc.2020.125536