基于机器学习的印地语电影评论情感分析

Tarun Jain, Payal Garg, Rimjhim Gupta, Priyanka Goyal, Namita Chalil
{"title":"基于机器学习的印地语电影评论情感分析","authors":"Tarun Jain, Payal Garg, Rimjhim Gupta, Priyanka Goyal, Namita Chalil","doi":"10.1109/ICDSIS55133.2022.9915961","DOIUrl":null,"url":null,"abstract":"Sentiment analysis has become an important field in the last few years. By performing sentiment analysis of user reviews, news, blogs, etc. we gain a deeper understanding of the general opinion towards a movie, product, etc. Sentiment Analysis is a very valuable tool for organizations to understand the opinion of the public towards their product, service movie, etc. Rather than reading an entire post, blog, or review, Sentiment Analysis allows companies to know the general opinion about their product or movie by deducing the emotion present in the piece of text. Sentiment analysis identifies the keywords in a piece of text and determines the emotion contained in it. Several works have been carried out in the subject area of sentiment analysis on English but hardly any work on Hindi. Hindi is a widely spoken language with a growing number of speakers. The social media platforms too see a large number of reviews, blogs in Hindi. Due to the rising amount of web content in Hindi, there was a requirement to perform sentiment analysis on the Hindi language. We propose a system for sentiment analysis on Hindi by using the Bag of Words model and applying four Machine Learning models.","PeriodicalId":178360,"journal":{"name":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","volume":"794 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sentiment Analysis of Movie Reviews in Hindi Language Using Machine Learning\",\"authors\":\"Tarun Jain, Payal Garg, Rimjhim Gupta, Priyanka Goyal, Namita Chalil\",\"doi\":\"10.1109/ICDSIS55133.2022.9915961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentiment analysis has become an important field in the last few years. By performing sentiment analysis of user reviews, news, blogs, etc. we gain a deeper understanding of the general opinion towards a movie, product, etc. Sentiment Analysis is a very valuable tool for organizations to understand the opinion of the public towards their product, service movie, etc. Rather than reading an entire post, blog, or review, Sentiment Analysis allows companies to know the general opinion about their product or movie by deducing the emotion present in the piece of text. Sentiment analysis identifies the keywords in a piece of text and determines the emotion contained in it. Several works have been carried out in the subject area of sentiment analysis on English but hardly any work on Hindi. Hindi is a widely spoken language with a growing number of speakers. The social media platforms too see a large number of reviews, blogs in Hindi. Due to the rising amount of web content in Hindi, there was a requirement to perform sentiment analysis on the Hindi language. We propose a system for sentiment analysis on Hindi by using the Bag of Words model and applying four Machine Learning models.\",\"PeriodicalId\":178360,\"journal\":{\"name\":\"2022 IEEE International Conference on Data Science and Information System (ICDSIS)\",\"volume\":\"794 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Data Science and Information System (ICDSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSIS55133.2022.9915961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Data Science and Information System (ICDSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSIS55133.2022.9915961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在过去的几年里,情感分析已经成为一个重要的领域。通过对用户评论、新闻、博客等进行情感分析,我们可以更深入地了解人们对电影、产品等的普遍看法。情感分析是组织了解公众对其产品、服务、电影等的意见的一个非常有价值的工具。与阅读整篇文章、博客或评论不同,情感分析允许公司通过推断文本中存在的情感来了解对其产品或电影的总体看法。情感分析识别文本中的关键字,并确定其中包含的情感。在英语情感分析这一学科领域已经开展了一些工作,但对印地语的研究却很少。印地语是一种广泛使用的语言,使用人数不断增加。社交媒体平台上也有大量的印度语评论和博客。由于印地语的网络内容数量不断增加,因此需要对印地语进行情感分析。我们提出了一个使用词袋模型和四个机器学习模型的印地语情感分析系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis of Movie Reviews in Hindi Language Using Machine Learning
Sentiment analysis has become an important field in the last few years. By performing sentiment analysis of user reviews, news, blogs, etc. we gain a deeper understanding of the general opinion towards a movie, product, etc. Sentiment Analysis is a very valuable tool for organizations to understand the opinion of the public towards their product, service movie, etc. Rather than reading an entire post, blog, or review, Sentiment Analysis allows companies to know the general opinion about their product or movie by deducing the emotion present in the piece of text. Sentiment analysis identifies the keywords in a piece of text and determines the emotion contained in it. Several works have been carried out in the subject area of sentiment analysis on English but hardly any work on Hindi. Hindi is a widely spoken language with a growing number of speakers. The social media platforms too see a large number of reviews, blogs in Hindi. Due to the rising amount of web content in Hindi, there was a requirement to perform sentiment analysis on the Hindi language. We propose a system for sentiment analysis on Hindi by using the Bag of Words model and applying four Machine Learning models.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信