{"title":"社交网络中的信息流建模:度量与评估","authors":"A. Admin, V. Mangat","doi":"10.54216/jchci.020101","DOIUrl":null,"url":null,"abstract":"Social network analysis is a key concept in analyzing the pattern of communication between various individuals in a social network. Various traditional metrics like centrality measures are used in literature to examine the interactions between various nodes. In this paper main aim of our analysis is to quantify the influential property of a node as well as path followed for information flow from one node to another node. To achieve this purpose statistical analysis and visualization is performed with the help of experimental setup and social network visualization tools.","PeriodicalId":330535,"journal":{"name":"Journal of Cognitive Human-Computer Interaction","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling Information Flow in Social Networks: Metrics and Evaluation\",\"authors\":\"A. Admin, V. Mangat\",\"doi\":\"10.54216/jchci.020101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social network analysis is a key concept in analyzing the pattern of communication between various individuals in a social network. Various traditional metrics like centrality measures are used in literature to examine the interactions between various nodes. In this paper main aim of our analysis is to quantify the influential property of a node as well as path followed for information flow from one node to another node. To achieve this purpose statistical analysis and visualization is performed with the help of experimental setup and social network visualization tools.\",\"PeriodicalId\":330535,\"journal\":{\"name\":\"Journal of Cognitive Human-Computer Interaction\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cognitive Human-Computer Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54216/jchci.020101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jchci.020101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling Information Flow in Social Networks: Metrics and Evaluation
Social network analysis is a key concept in analyzing the pattern of communication between various individuals in a social network. Various traditional metrics like centrality measures are used in literature to examine the interactions between various nodes. In this paper main aim of our analysis is to quantify the influential property of a node as well as path followed for information flow from one node to another node. To achieve this purpose statistical analysis and visualization is performed with the help of experimental setup and social network visualization tools.