基于文本挖掘的B2C购物网站在线评论内容特征分析  

Analysis on the Content Characteristics of the Online Review about B2C Shopping Websites Based on Text Mining

作　　者：董爽[1] 王晓红[1] 葛争红[2] 

机构地区：[1]北京联合大学管理学院 [2]北京联合大学生物化学工程学院

出　　处：《图书馆理论与实践》2017年第6期54-58,共5页Library Theory and Practice

基　　金：国家自然科学基金项目"面向商务智能的思维主题发现"(项目编号:71272161)研究成果之一

摘　　要：基于文本挖掘和定量分析研究三个B2C购物网站在线评论的内容特征。通过高频词进行在线评论内容特征分析得出,购物网站的用户群体更多关注手机的商品特征和情感表达,而对服务特征的关注相对较少。通过分析网站间高频词的相关性与差异性发现,虽然不同购物网站在线评论内容的相关性较强,但也存在着显著差异,反映出不同网站消费者关注点或感受的相似性和差异。研究结果为消费者购买决策、企业战略调整、购物平台提升管理能力提供了有价值的参考。This article uses text mining and quantitative analysis tools to analyze the content characteristics of the online review captured from three B2C shopping websites. Based on the high frequency words, the content characteristics of online review are analyzed. It is concluded that the user groups of shopping websites pay more attention to the product features and emotional expression of mobile phones, while the attention of service features is relatively small. The correlation and difference analysis of the high frequency words between websites are carried out to find that although the content correlation of online shopping reviews of difference shopping websites is strong, there are significant differences, reflecting the similarity and differences of the different website consumers＇ focus of attention or feelings. The results provide valuable reference for consumer purchasing decision, enterprise strategy adjustment and shopping platform management.

关 键 词：在线评论 内容特征 购物网站 文本挖掘 

分 类 号：F724.6[经济管理—产业经济] G254[文化科学—图书馆学]