{"title":"Research on Information Propagation Method Based on Individual User Characteristics","authors":"Lejun Zhang, Weijie Zhao, Chunhui Zhao","doi":"10.1109/CIS.2017.00103","DOIUrl":null,"url":null,"abstract":"At present, the research of information dissemination model based on social platform mainly focuses on the influence of social network structure and information content on information dissemination, but it is not comprehensive enough for user characteristics. And all users use the same prediction model, which will lead to the prediction results of different users will appear homogeneity. This paper focuses on the microblogging forwarding will be affected by what the individual characteristics, and then uses each user's history data to generate an independent prediction model for each user. For users with insufficient historical information data, this paper proposes a scheme to predict microblogging forwarding behavior by neighboring friends.","PeriodicalId":304958,"journal":{"name":"2017 13th International Conference on Computational Intelligence and Security (CIS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2017.00103","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
At present, the research of information dissemination model based on social platform mainly focuses on the influence of social network structure and information content on information dissemination, but it is not comprehensive enough for user characteristics. And all users use the same prediction model, which will lead to the prediction results of different users will appear homogeneity. This paper focuses on the microblogging forwarding will be affected by what the individual characteristics, and then uses each user's history data to generate an independent prediction model for each user. For users with insufficient historical information data, this paper proposes a scheme to predict microblogging forwarding behavior by neighboring friends.