{"title":"推特情绪分析","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":"{\"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}","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}
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
