{"title":"年龄预测分析——基于微博","authors":"Prasad Koti, Sujatha Pothula, P. Dhavachelvan","doi":"10.1109/ICRTCCM.2017.38","DOIUrl":null,"url":null,"abstract":"Age predictive analysis is to predict the age of the users who posted the message in any microblog. By using some keywords, we extract the messages as dataset and processed for predicting the age of the user. Here, the design and techniques to foreseen the age of the user by microblog dataset are presented. In recent years, microblogging services like Twitter and SinaWeibo become an essential part in everyone's life. Due to enormous growth in microblogging services, various challenges arise in research fields like detection, sentiment analysis, user classification, etc. due to the data produced by the huge number of microbloggers. In this paper, we used dataset from Twitter and showed promising results for predicting age ranges.","PeriodicalId":134897,"journal":{"name":"2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Age Forecasting Analysis - Over Microblogs\",\"authors\":\"Prasad Koti, Sujatha Pothula, P. Dhavachelvan\",\"doi\":\"10.1109/ICRTCCM.2017.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Age predictive analysis is to predict the age of the users who posted the message in any microblog. By using some keywords, we extract the messages as dataset and processed for predicting the age of the user. Here, the design and techniques to foreseen the age of the user by microblog dataset are presented. In recent years, microblogging services like Twitter and SinaWeibo become an essential part in everyone's life. Due to enormous growth in microblogging services, various challenges arise in research fields like detection, sentiment analysis, user classification, etc. due to the data produced by the huge number of microbloggers. In this paper, we used dataset from Twitter and showed promising results for predicting age ranges.\",\"PeriodicalId\":134897,\"journal\":{\"name\":\"2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM)\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRTCCM.2017.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRTCCM.2017.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Age predictive analysis is to predict the age of the users who posted the message in any microblog. By using some keywords, we extract the messages as dataset and processed for predicting the age of the user. Here, the design and techniques to foreseen the age of the user by microblog dataset are presented. In recent years, microblogging services like Twitter and SinaWeibo become an essential part in everyone's life. Due to enormous growth in microblogging services, various challenges arise in research fields like detection, sentiment analysis, user classification, etc. due to the data produced by the huge number of microbloggers. In this paper, we used dataset from Twitter and showed promising results for predicting age ranges.
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