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Customer knowledge discovery from online reviews |
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| Authors: | Weijia You Mu Xia Lu Liu Dan Liu |
| Affiliation: | 1. School of Economics and Management, Beijing Forestry University, 35 East Qinghua Road, Haidian District, Beijing, 100083, People??s Republic of China 2. Department of OMIS, Leavey School of Business, Santa Clara University, Santa Clara, CA, 95053, USA 3. School of Economics and Management, Beihang University, Beijing, 100191, China |
| Abstract: | The explosive growth of Chinese electronic market has made it possible for companies to better understand consumers?? opinion towards their products in a timely fashion through their online reviews. This study proposes a framework for extracting knowledge from online reviews through text mining and econometric analysis. Specifically, we extract product features, detect topics, and identify determinants of customer satisfaction. An experiment on the online reviews from a Chinese leading B2C (Business-to-Customer) website demonstrated the feasibility of the proposed method. We also present some findings about the characteristics of Chinese reviewers. |
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| 本文献已被 SpringerLink 等数据库收录！ | |