{"title":"A Differential Epidemic Model for Information, Misinformation and Disinformation in Online Social Networks","authors":"N. Narayan, R. Jha, A. Singh","doi":"10.4018/ijswis.300827","DOIUrl":null,"url":null,"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 network has become an important part of our life, so 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 our theoretical results. Again, with the help of data available on twitter related to COVID-19 vaccination is used to perform the experiment. Finally, discuss about the control strategy to minimize the misinformation and disinformation related to vaccination.","PeriodicalId":54934,"journal":{"name":"International Journal on Semantic Web and Information Systems","volume":"24 1","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal on Semantic Web and Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/ijswis.300827","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 4
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 network has become an important part of our life, so 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 our theoretical results. Again, with the help of data available on twitter related to COVID-19 vaccination is used to perform the experiment. Finally, discuss about the control strategy to minimize the misinformation and disinformation related to vaccination.
期刊介绍：
The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.
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