产品评论的情感分析:一项调查

M. Ezhilarasan, V. Govindasamy, V. Akila, K. Vadivelan
{"title":"产品评论的情感分析:一项调查","authors":"M. Ezhilarasan, V. Govindasamy, V. Akila, K. Vadivelan","doi":"10.1109/ICCPEIC45300.2019.9082346","DOIUrl":null,"url":null,"abstract":"Online reviews are considered as one of the most essential sources of client opinion. In current scenario, consumers can learn about the products and services using online review resources to make decisions. The customer reviews for numerous products plays a very vital role not only for purchasers, But also for the firms. Consumer reviews are used by companies as feedback in their product development strategies and in the management of consumer relations. Due to their disorganized nature, consumer reviews with valuable information still face difficulties in navigating information. Driven by a need for profit, some organizations may generate spam reviews regarding different products or their own product which may mislead customers to buying unworthy product. Because of its promising commercial benefits, Sentiment Analysis has become one of the most interesting subjects in text analysis. One of its main problem is the detection of false negate reviews. In addition, the user reviews can be classified as positive or negative reviews so that a consumer can use the false review to select a product. In this paper, we examine various levels of Sentiment Analysis and compare different existing techniques.","PeriodicalId":120930,"journal":{"name":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Sentiment Analysis On Product Review: A Survey\",\"authors\":\"M. Ezhilarasan, V. Govindasamy, V. Akila, K. Vadivelan\",\"doi\":\"10.1109/ICCPEIC45300.2019.9082346\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online reviews are considered as one of the most essential sources of client opinion. In current scenario, consumers can learn about the products and services using online review resources to make decisions. The customer reviews for numerous products plays a very vital role not only for purchasers, But also for the firms. Consumer reviews are used by companies as feedback in their product development strategies and in the management of consumer relations. Due to their disorganized nature, consumer reviews with valuable information still face difficulties in navigating information. Driven by a need for profit, some organizations may generate spam reviews regarding different products or their own product which may mislead customers to buying unworthy product. Because of its promising commercial benefits, Sentiment Analysis has become one of the most interesting subjects in text analysis. One of its main problem is the detection of false negate reviews. In addition, the user reviews can be classified as positive or negative reviews so that a consumer can use the false review to select a product. In this paper, we examine various levels of Sentiment Analysis and compare different existing techniques.\",\"PeriodicalId\":120930,\"journal\":{\"name\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"volume\":\"218 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPEIC45300.2019.9082346\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPEIC45300.2019.9082346","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

在线评论被认为是客户意见最重要的来源之一。在当前的场景中,消费者可以使用在线评论资源来了解产品和服务,从而做出决策。消费者对众多产品的评价不仅对购买者,而且对企业都起着至关重要的作用。消费者评论被公司用作产品开发策略和管理消费者关系的反馈。由于有价值信息的消费者评论的无序性,它们在导航信息时仍然面临困难。在利润需求的驱使下,一些组织可能会对不同的产品或自己的产品产生垃圾评论,这可能会误导客户购买不值得的产品。情感分析由于具有良好的商业效益,已成为文本分析领域的研究热点之一。它的一个主要问题是检测假阴性评论。此外,用户评论可以分为正面或负面评论,以便消费者可以使用错误的评论来选择产品。在本文中,我们研究了不同层次的情感分析,并比较了不同的现有技术。
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 On Product Review: A Survey
Online reviews are considered as one of the most essential sources of client opinion. In current scenario, consumers can learn about the products and services using online review resources to make decisions. The customer reviews for numerous products plays a very vital role not only for purchasers, But also for the firms. Consumer reviews are used by companies as feedback in their product development strategies and in the management of consumer relations. Due to their disorganized nature, consumer reviews with valuable information still face difficulties in navigating information. Driven by a need for profit, some organizations may generate spam reviews regarding different products or their own product which may mislead customers to buying unworthy product. Because of its promising commercial benefits, Sentiment Analysis has become one of the most interesting subjects in text analysis. One of its main problem is the detection of false negate reviews. In addition, the user reviews can be classified as positive or negative reviews so that a consumer can use the false review to select a product. In this paper, we examine various levels of Sentiment Analysis and compare different existing techniques.
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:481959085
Book学术官方微信