Your browser doesn't support javascript.
A differential epidemic Model for Information, Misinformation, and disinformation in online Social Networks: CoVId-19 Vaccination
International Journal on Semantic Web and Information Systems ; 18(1), 2022.
Article in English | Scopus | ID: covidwho-2273684
ABSTRACT
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. © 2022 Authors. All rights reserved.
Keywords

Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Vaccines Language: English Journal: International Journal on Semantic Web and Information Systems Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Vaccines Language: English Journal: International Journal on Semantic Web and Information Systems Year: 2022 Document Type: Article