Tehnički vjesnik, Vol. 26 No. 1, 2019.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20181218012812
User Needs Mining Based on Topic Analysis of Online Reviews
Liqiong Liu
; School of Business Administration, Wuhan Business University, No. 816 Dongfeng Road, Wuhan City, Hubei Province, China
Liyi Zhang
; School of Information Management, Wuhan University, No. 299 Bayi Road, Wuchang District, Wuhan City, Hubei Province, China
Pinghao Ye
; School of Business Administration, Wuhan Business University, No. 816 Dongfeng Road, Wuhan City, Hubei Province, China
Qihua Liu
; School of Information Management, Jiangxi University of Finance and Economics, Yuping Avenue, Changbei Economic and Technological Development Zone, Nanchang City, Jiangxi Province, China
Sažetak
The purpose of this paper is to aggregate the topic information of online review text and clarify the user needs. We conducted the study on online reviews of women’s clothing store of Taobao.com 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. The results show that the content of online reviews mainly includes four topics: basic features of products, additional features of products, user experience and product display. It reveals the potential user needs of women’s clothing store of Taobao.com, which cannot only help consumers to make rational decisions, but also provide guidance to merchants and manufacturers.
Ključne riječi
online reviews; Taobao.com; text mining; topic analysis; user needs
Hrčak ID:
217148
URI
Datum izdavanja:
16.2.2019.
Posjeta: 2.494 *