{"title":"SentiT:一个半实时的Twitter情感解释系统","authors":"D. Kishore, K. Dheeraj","doi":"10.9790/0661-1904010913","DOIUrl":null,"url":null,"abstract":"SentiT is an opinion analysis application for Twitter. Based on the keyword searched, SentiT collects tweets having to do with it , separates and labels them into the different polarity classes neutral, negative and positive , simultaneously we also categorize them into emotions which are anger, disgust, fear, joy, sadness, surprise .Our main objective is to prepare a system that takes real time data from the twitter and come to a conclusion about the opinion on particular product/keyword","PeriodicalId":91890,"journal":{"name":"IOSR journal of computer engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SentiT: A Semi Real Time System for Interpreting Sentiment in Twitter\",\"authors\":\"D. Kishore, K. Dheeraj\",\"doi\":\"10.9790/0661-1904010913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SentiT is an opinion analysis application for Twitter. Based on the keyword searched, SentiT collects tweets having to do with it , separates and labels them into the different polarity classes neutral, negative and positive , simultaneously we also categorize them into emotions which are anger, disgust, fear, joy, sadness, surprise .Our main objective is to prepare a system that takes real time data from the twitter and come to a conclusion about the opinion on particular product/keyword\",\"PeriodicalId\":91890,\"journal\":{\"name\":\"IOSR journal of computer engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IOSR journal of computer engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9790/0661-1904010913\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IOSR journal of computer engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9790/0661-1904010913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SentiT: A Semi Real Time System for Interpreting Sentiment in Twitter
SentiT is an opinion analysis application for Twitter. Based on the keyword searched, SentiT collects tweets having to do with it , separates and labels them into the different polarity classes neutral, negative and positive , simultaneously we also categorize them into emotions which are anger, disgust, fear, joy, sadness, surprise .Our main objective is to prepare a system that takes real time data from the twitter and come to a conclusion about the opinion on particular product/keyword