{"title":"Sentiment Analysis using Different Machine Learning Techniques for Product Review","authors":"Ruqaiya Khanam, Abhishek Sharma","doi":"10.1109/ComPE53109.2021.9752004","DOIUrl":null,"url":null,"abstract":"The World Wide Web (WWW) has turned into an immense wellspring of crude information produced by both the customers and the clients. Utilizing online media, web - based business sites, and film surveys, for example, Facebook, Twitter, Amazon, Flip kart and so forth, clients share their perspectives and emotions in an advantageous way. In WWW, where many individuals express their perspectives in their day by day connection, by the same token in the web-based media or in e-commerce which can be their opinions , what’s more, sentiments about a specific thing. Sentiment analysis is characterized as the way toward mining information, reviewing or anticipating the feelings or emotions behind the sentence via natural language processing. This paper includes two approaches, the first one is a lexicon-based approach, and the second one is machine learning technique logistic regression to extract the sentiments from text.","PeriodicalId":211704,"journal":{"name":"2021 International Conference on Computational Performance Evaluation (ComPE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Performance Evaluation (ComPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComPE53109.2021.9752004","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
The World Wide Web (WWW) has turned into an immense wellspring of crude information produced by both the customers and the clients. Utilizing online media, web - based business sites, and film surveys, for example, Facebook, Twitter, Amazon, Flip kart and so forth, clients share their perspectives and emotions in an advantageous way. In WWW, where many individuals express their perspectives in their day by day connection, by the same token in the web-based media or in e-commerce which can be their opinions , what’s more, sentiments about a specific thing. Sentiment analysis is characterized as the way toward mining information, reviewing or anticipating the feelings or emotions behind the sentence via natural language processing. This paper includes two approaches, the first one is a lexicon-based approach, and the second one is machine learning technique logistic regression to extract the sentiments from text.