{"title":"基于ARMA模型的话题热度预测","authors":"Yichen Song, Aiping Li, Yong Quan","doi":"10.1145/3208788.3208799","DOIUrl":null,"url":null,"abstract":"With the rapid development of information technology and the widespread application of information, social networks are becoming more convenient and faster tools for information release and acquisition. Predicting topic popularity is important for online referral systems, marketing services and public opinion controls. In this paper, we predict the popularity of topics with the help of time series analysis methods, verifying the validity of ARMA model in topic popularity prediction.","PeriodicalId":211585,"journal":{"name":"Proceedings of 2018 International Conference on Mathematics and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Topics' popularity prediction based on ARMA model\",\"authors\":\"Yichen Song, Aiping Li, Yong Quan\",\"doi\":\"10.1145/3208788.3208799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of information technology and the widespread application of information, social networks are becoming more convenient and faster tools for information release and acquisition. Predicting topic popularity is important for online referral systems, marketing services and public opinion controls. In this paper, we predict the popularity of topics with the help of time series analysis methods, verifying the validity of ARMA model in topic popularity prediction.\",\"PeriodicalId\":211585,\"journal\":{\"name\":\"Proceedings of 2018 International Conference on Mathematics and Artificial Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2018 International Conference on Mathematics and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3208788.3208799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2018 International Conference on Mathematics and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3208788.3208799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
With the rapid development of information technology and the widespread application of information, social networks are becoming more convenient and faster tools for information release and acquisition. Predicting topic popularity is important for online referral systems, marketing services and public opinion controls. In this paper, we predict the popularity of topics with the help of time series analysis methods, verifying the validity of ARMA model in topic popularity prediction.