信息技术管理2019年10期

情感分析在商品评论中的应用
张明辉
(北京邮电大学 经济管理学院,北京 100876)

摘  要:随着互联网和电子商务的高速发展,各种电商平台上的在线商品评论数量急剧增长。在线评论包含了消费者对购买的商品或服务的感受、态度和情感倾向,对潜在的消费者而言具有很大的参考作用。现在有很多研究关注评论数据的情感倾向以及如何对情感进行量化,并且取得了不错的成果。本文通过学习总结情感分析发展现状,对目前情感分析在商品评论中的应用进行介绍和总结。


关键词:自然语言处理;在线评论;情感分析;情感词典



中图分类号:TP391.1         文献标识码:A         文章编号:2096-4706(2019)10-0187-04


Application of Sentiment Analysis in Product Reviews
ZHANG Minghui
(School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing 100876,China)

Abstract:With the rapid development of the internet and e-commerce,the number of online product reviews on various e-commerce platforms has increased dramatically. Online reviews contain consumer perceptions,attitudes,and sentiments about the goods or services they purchase,and are a great reference for potential consumers. There are many studies that focus on the emotional tendencies of the review data and how to quantify the emotions,and have achieved good results. Through the study and summary of the development status of sentiment analysis,the application of current sentiment analysis in commodity reviews is introduced and summarized.

Keywords:natural language processing;online review;emotion analysis;emotional dictionary


参考文献:

[1] 吴应良,黄媛,王选飞. 在线中文用户评论研究综述:基于情感计算的视角 [J]. 情报科学,2017,35(6):159-163+170.

[2] 朱少杰. 基于深度学习的文本情感分类研究 [D]. 哈尔滨:哈尔滨工业大学,2014.

[3] 李青松. 文本情感分析研究 [J]. 现代计算机(专业版),2019(4):21-25.

[4] 冯俐. 中文分词技术综述 [J]. 现代计算机(专业版),2018(34):17-20.

[5] Suleman K,Vechtomova O.Discovering aspects of online consumer reviews [J]. Journal of Information Science,2015,42(4):492-506.

[6] Marneffe M-C D, MacCartney B, Manning C D. Generating typed dependency parsers from phrase structure parses [C].Portoroz:Proceedings of the fifth international conference on language resources and evaluation,2006:449–454.

[7] 姜伶伶,何中市,张航. 基于Good-Turing 平滑SOPMI 算法构建微博情感词典方法的研究 [J]. 现代计算机(专业版),2018(10):15-20.

[8] Bai X,Chen F,Zhan S B. A Study on Sentiment Computing and Classification of Sina Weibo with Word2vec [C]//Big Data( BigData Congress),2014 IEEE International Congress on. S.l.:s.n.,2014:358-363.


作者简介:张明辉(1998.03-),男,汉族,安徽人,本科在读,研究方向:数据挖掘。