A Differential Epidemic Model for Information, Misinformation, and Disinformation in Online Social Networks: COVID-19 Vaccination

被引：13
作者：
Narayan, Nitesh [1 ]
Jha, Rishi Kumar [1 ]
Singh, Anshuman [2 ]
机构：
[1] Natl Inst Technol, Patna, Bihar, India
[2] Natl Inst Technol, Dept Civil Engn, Patna, Bihar, India
来源：
INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS | 2022年 / 18卷 / 01期
关键词：
Control Strategy; COVID-19; Vaccination; Differential Epidemic Model; Numerical Simulation; Online Social Network; Stability of the System;
D O I：
10.4018/IJSWIS.300827
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
These days the online social network has become a huge source of data. People are actively sharing information on these platforms. The data on online social networks can be misinformation, information, and disinformation. Because online social networks have become an important part of our lives, the information on online social networks makes a great impact on us. Here a differential epidemic model for information, misinformation, and disinformation on online social networks is proposed. The expression for basic reproduction number has been developed. Again, the stability condition for the system at both infection-free and endemic equilibriums points has been discussed. The numerical simulation has been performed to validate the theoretical results. Data available on Twitter related to COVID-19 vaccination is used to perform the experiment. Finally, the authors discuss the control strategy to minimize the misinformation and disinformation related to vaccination.
引用
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页数：20
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