User Needs Mining Based on Topic Analysis of Online Reviews: Taking Taobao Womens Clothing Store as an Example
In order to aggregate the topic information of online reviews text and clarify the user needs, the paper conducted the study on online reviews of Taobao womens clothing store with semantic analysis and text mining.Online reviews were collected by means of web crawler.Using Chinese word segmentation tool and data analysis tool, the word frequency statistics was realized.The statistical software was used for the clustering analysis and multidimensional scaling analysis of high frequency keywords.It shows that the online reviews mainly include basic features of products, additional features of products, user experience and product display.It reveals the potential needs of Taobao womens clothing stores, which can not only help consumers to make rational decisions, but also provide guidance to merchants and manufacturers.
online reviews topic analysis user needs text mining Taobao
Liqiong Liu Liyi Zhang Pinghao Ye Qihua Liu
School of Business Administration Wuhan Business University Wuhan,China School of Information Management Wuhan University Wuhan,China School of Information Engineering Wuhan Business University Wuhan,China School of Information Technology Jiangxi University of Finance and Economics Nanchang,China
国际会议
郑州
英文
193-198
2018-09-21（万方平台首次上网日期，不代表论文的发表时间）