{"title":"对Twitter用户动态配置文件的兴趣预测","authors":"Elisafina Siswanto, M. L. Khodra, L. J. E. Dewi","doi":"10.1109/ICAICTA.2014.7005952","DOIUrl":null,"url":null,"abstract":"Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user's tweet. In this study, we investigate the best classification model for determining the user's interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user's tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.","PeriodicalId":173600,"journal":{"name":"2014 International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Prediction of interest for dynamic profile of Twitter user\",\"authors\":\"Elisafina Siswanto, M. L. Khodra, L. J. E. Dewi\",\"doi\":\"10.1109/ICAICTA.2014.7005952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user's tweet. In this study, we investigate the best classification model for determining the user's interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user's tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.\",\"PeriodicalId\":173600,\"journal\":{\"name\":\"2014 International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAICTA.2014.7005952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAICTA.2014.7005952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of interest for dynamic profile of Twitter user
Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user's tweet. In this study, we investigate the best classification model for determining the user's interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user's tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.