A Word Vector Based Review Vector Method for Sentiment Analysis of Movie Reviews Exploring the Applicability of the Movie Reviews

Fulian Yin, Yanyan Wang, Xingyi Pan, Pei Su
{"title":"A Word Vector Based Review Vector Method for Sentiment Analysis of Movie Reviews Exploring the Applicability of the Movie Reviews","authors":"Fulian Yin, Yanyan Wang, Xingyi Pan, Pei Su","doi":"10.1109/ICCIA.2018.00028","DOIUrl":null,"url":null,"abstract":"Based on word embedding method, this paper presents a word vector based review vector method for sentiment analysis of movie reviews. As a result, it is achieved that 86.18% classification accuracy using the method. Meanwhile, the method is applicable to multiple languages such as Chinese and English, and it is extensible for larger scale contents as well. What’s more, the influence of word vector dimensions on the sentiment analysis accuracy and the method’s applicability on sentences of varied lengths are also discussed in this paper. The experimental result proved that the word vector based review method for sentiment analysis is not only an efficient and simple way to analyze emotional expression, but also has extensibility and applicability for comments in varied lengths and multiple languages.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIA.2018.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Based on word embedding method, this paper presents a word vector based review vector method for sentiment analysis of movie reviews. As a result, it is achieved that 86.18% classification accuracy using the method. Meanwhile, the method is applicable to multiple languages such as Chinese and English, and it is extensible for larger scale contents as well. What’s more, the influence of word vector dimensions on the sentiment analysis accuracy and the method’s applicability on sentences of varied lengths are also discussed in this paper. The experimental result proved that the word vector based review method for sentiment analysis is not only an efficient and simple way to analyze emotional expression, but also has extensibility and applicability for comments in varied lengths and multiple languages.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于词向量的影评情感分析方法探讨了影评的适用性
基于词嵌入方法,提出了一种基于词向量的影评情感分析方法。结果表明,该方法的分类准确率达到了86.18%。同时,该方法适用于多种语言,如中文和英文,并可扩展到更大规模的内容。此外,本文还讨论了词向量维数对情感分析精度的影响以及该方法对不同长度句子的适用性。实验结果证明,基于词向量的情感评论分析方法不仅是一种高效、简单的情感表达分析方法,而且对不同长度、多语言的评论具有可扩展性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Text Extraction and Categorization from Watermark Scientific Document in Bulk Locating Heartbeats from Electrocardiograms and Other Correlated Signals Combining Deep Learning and JSEG Cuda Segmentation Algorithm for Electrical Components Recognition An Oppositional Learning Prediction Operator for Simulated Kalman Filter Clustering Method for Financial Time Series with Co-Movement Relationship
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1