{"title":"TWITTER SENTIMENT ANALYSIS","authors":"Vedurumudi Priyanka, June","doi":"10.26634/jcom.8.4.18269","DOIUrl":null,"url":null,"abstract":"In this report, address the problem of sentiment classi�cation on twitter dataset. used a number of machine learning and deep learning methods to perform sentiment analysis. In the end, used a majority vote ensemble method with 5 of our best models to achieve the classi�cation accuracy of 83.58% on kaggle public leaderboard.","PeriodicalId":130578,"journal":{"name":"i-manager's Journal on Computer Science","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"i-manager's Journal on Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26634/jcom.8.4.18269","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
In this report, address the problem of sentiment classi�cation on twitter dataset. used a number of machine learning and deep learning methods to perform sentiment analysis. In the end, used a majority vote ensemble method with 5 of our best models to achieve the classi�cation accuracy of 83.58% on kaggle public leaderboard.
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