Koryachko Aleksei Vyacheslavovich, Minaev Vladimir Aleksandrovich, Faddeev Aleksandr Olegovich
{"title":"Simulation Modeling of Manipulative Influences in Social Networks","authors":"Koryachko Aleksei Vyacheslavovich, Minaev Vladimir Aleksandrovich, Faddeev Aleksandr Olegovich","doi":"10.1109/ELEKTRO49696.2020.9130364","DOIUrl":null,"url":null,"abstract":"System-dynamic model of manipulative influences in social networks is considered. Used differential equation system is given. Experiments with the model using simulation system AnyLogic are carried out. Experimental results based on the research of information distribution in different regions of Russian Federation are shown. Using cluster analysis, the typology of locations into statistically homogeneous groups is made. An accurate model showing the dependency of dynamic characteristics shown by information distribution in social networks of different clusters from the median that characterizes the number of network user \"followers\" is constructed. The model allows implementing the forecast of information counteractions in social networks and reproducing different scenarios of given processes development.","PeriodicalId":165069,"journal":{"name":"2020 ELEKTRO","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 ELEKTRO","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELEKTRO49696.2020.9130364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
System-dynamic model of manipulative influences in social networks is considered. Used differential equation system is given. Experiments with the model using simulation system AnyLogic are carried out. Experimental results based on the research of information distribution in different regions of Russian Federation are shown. Using cluster analysis, the typology of locations into statistically homogeneous groups is made. An accurate model showing the dependency of dynamic characteristics shown by information distribution in social networks of different clusters from the median that characterizes the number of network user "followers" is constructed. The model allows implementing the forecast of information counteractions in social networks and reproducing different scenarios of given processes development.