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计算机技术21年4期

基于电商评论文本的用户情感分析
刘若雨
(河北经贸大学,河北 石家庄 050061)

摘  要:随着电商行业的迅猛发展,网络购物如雨后春笋般迅速崛起,网购评论数据爆炸式增长,准确挖掘并利用这些能反映消费者情感倾向的信息,已成为商家改进产品质量、提升竞争力不可或缺的手段。该文以国产品牌小米手机为研究对象,利用 Python 软件爬取天猫商城中的评论信息,对爬取的天猫商城评论数据进行情感分析,分别对正、负面评论构建 LDA 主题模型,挖掘出大数据背后的隐含信息。


关键词:评论文本;情感分析;LDA 模型



DOI:10.19850/j.cnki.2096-4706.2021.04.021


中图分类号:TP391.1                                  文献标识码:A                                     文章编号:2096-4706(2021)04-0085-04


User Sentiment Analysis Based on E-Commerce Review Text

LIU Ruoyu

(Hebei University of Economics and Business,Shijiazhuang 050061,China)

Abstract:With the rapid development of E-Commerce industry,online shopping is springing up like mushrooms,online shopping review data is increasing dramatically. It has become an indispensable means for merchants to improve their product quality and enhance their competitiveness by accurately mining and utilizing these information that can reflect consumers’emotional tendency. In this paper,taking domestic brand millet mobile phone as the research object,using Python software to crawl comment information in Tmall, and carry out sentiment analysis on comment data crawled in Tmall. To construct LDA topic model for positive and negative comments respectively,and dig out the hidden information behind big data.

Keywords:review text;sentiment analysis;LDA model


参考文献:

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[2] 章蓬伟,贾钰峰,邵小青,等 . 基于文本情感分析的电商 产品评论数据研究 [J]. 微处理机,2020,41(6):58-62.

[3] POOJA B,JASWINDER S. A Study on Classification Techniques based on Opinions [J].IOP Conference Series:Materials Science and Engineering,2021,1022(1):012091.

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[5] 关鹏,王曰芬 . 科技情报分析中 LDA 主题模型最优主题 数确定方法研究 [J]. 现代图书情报技术,2016(9):42-50.


作者简介:刘若雨(1997—),女,汉族,河北石家庄人,硕 士研究生在读,研究方向:大数据挖掘与分析。