{"title":"Modeling and analyzing network dynamics of COVID-19 vaccine information propagation in the Chinese Sina Microblog","authors":"Fulian Yin, Jinxia Wang, Hongyu Pang, Xin Pei, Zhen Jin, Jianhong Wu","doi":"10.1007/s10588-024-09386-x","DOIUrl":null,"url":null,"abstract":"<p>Information about the vaccine is usually spread through heterogeneous networks in reality, where public opinion bursts out faster than in homogeneous networks. Considering the complexity of heterogeneous networks, we develop a network susceptible-forwarding-immune (NET-SFI) model to describe the patterns of information propagation in the actual social network. Classifying the states of nodes according to the number of users can contact in the social network, the NET-SFI model focuses on the network structure and user heterogeneity. We adopt a data-model drive method to conduct the model validation including two types of COVID-19 vaccine information from the Chinese Sina Microblog. Our parameter sensitivity analyses show the important significance of node degree in causing the outbreak of public opinion. Moreover, corresponding conclusions based on our analytic study are conducive to designing valid strategies for vaccine information dissemination.</p>","PeriodicalId":50648,"journal":{"name":"Computational and Mathematical Organization Theory","volume":"4 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and Mathematical Organization Theory","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10588-024-09386-x","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Information about the vaccine is usually spread through heterogeneous networks in reality, where public opinion bursts out faster than in homogeneous networks. Considering the complexity of heterogeneous networks, we develop a network susceptible-forwarding-immune (NET-SFI) model to describe the patterns of information propagation in the actual social network. Classifying the states of nodes according to the number of users can contact in the social network, the NET-SFI model focuses on the network structure and user heterogeneity. We adopt a data-model drive method to conduct the model validation including two types of COVID-19 vaccine information from the Chinese Sina Microblog. Our parameter sensitivity analyses show the important significance of node degree in causing the outbreak of public opinion. Moreover, corresponding conclusions based on our analytic study are conducive to designing valid strategies for vaccine information dissemination.
期刊介绍：
Computational and Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for integrating data, computational models, analysis and visualization techniques.
Various types of papers and underlying research are welcome. Papers presenting, validating, or applying models and/or computational techniques, new algorithms, dynamic metrics for networks and complex systems and papers comparing, contrasting and docking computational models are strongly encouraged. Both applied and theoretical work is strongly encouraged. The editors encourage theoretical research on fundamental principles of social behaviour such as coordination, cooperation, evolution, and destabilization. The editors encourage applied research representing actual organizational or policy problems that can be addressed using computational tools. Work related to fundamental concepts, corporate, military or intelligence issues are welcome.
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