{"title":"Online dynamic rumour propagation model considering punishment mechanism and individual personality characteristics","authors":"Chengai Sun;Donghang Qiao;Liqing Qiu","doi":"10.1093/comnet/cnac038","DOIUrl":null,"url":null,"abstract":"In the Internet era, rumours will spread rapidly in the network and hinder the development of all aspects of society. To create a harmonious network environment, it is essential to take punitive measures against malicious rumour mongers on social platforms. Take the measure of forbidden as an example. The forbidden one may stop spreading rumours because of being punished, or he may become a disseminator again because of paranoia. Other people who know rumours may become alert and stop propagating rumours or temporarily forget rumours. And therefore, the forbidden state is added to describe the above phenomenon, and the SIFR (Ignorant–Disseminator–Forbidden–Restorer) model is proposed. Taking the vigilance and paranoia derived from punishment measures into account, the connection edges from the forbidden to the disseminator and from the disseminator to the restorer are increased in this model. And then, the stability of SIFR model is proved by using the basic regeneration number and Routh–Hurwitz stability theorem. The simulation results demonstrate that individual paranoia may do harm to the control of rumour dissemination. While the punishment mechanism, individual forgetting mechanism and vigilance can effectively curb the spread of rumours.","PeriodicalId":15442,"journal":{"name":"Journal of complex networks","volume":"10 4","pages":"22-37"},"PeriodicalIF":2.2000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of complex networks","FirstCategoryId":"100","ListUrlMain":"https://ieeexplore.ieee.org/document/10070461/","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In the Internet era, rumours will spread rapidly in the network and hinder the development of all aspects of society. To create a harmonious network environment, it is essential to take punitive measures against malicious rumour mongers on social platforms. Take the measure of forbidden as an example. The forbidden one may stop spreading rumours because of being punished, or he may become a disseminator again because of paranoia. Other people who know rumours may become alert and stop propagating rumours or temporarily forget rumours. And therefore, the forbidden state is added to describe the above phenomenon, and the SIFR (Ignorant–Disseminator–Forbidden–Restorer) model is proposed. Taking the vigilance and paranoia derived from punishment measures into account, the connection edges from the forbidden to the disseminator and from the disseminator to the restorer are increased in this model. And then, the stability of SIFR model is proved by using the basic regeneration number and Routh–Hurwitz stability theorem. The simulation results demonstrate that individual paranoia may do harm to the control of rumour dissemination. While the punishment mechanism, individual forgetting mechanism and vigilance can effectively curb the spread of rumours.
期刊介绍:
Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network