[Objective] This paper proposes a method to extract product characteristics from user comments, aiming to address the issues facing hedonic price research. [Methods] First, we extracted keywords from user comments. Then, we retrieved the product characteristics favored by consumers through keywords clustering, and established the hedonic price model. Finally, we examined the proposed model with the sales of new properties in Guangzhou. [Results] We found seven real estate characteristics of significant consumer preferences from the user comments. The degree of fitting of the model reached 0.760, the DW statistic was 2.013, and the correlation coefficient between user preferences and price of the real estates was 0.989. [Limitations] The experimental data was collected from real estate website only. [Conclusions] The new model based on users comments could accurately evaluate the price of products. It also helps us effectively avoid multiple collinearity problems between independent variables and further explore business and consumer behaviors.
文秀贤,徐健. 基于用户评论的商品特征提取及特征价格研究 *[J]. 数据分析与知识发现, 2019, 3(7): 42-51.
Xiuxian Wen,Jian Xu. Research on Product Characteristics Extraction and Hedonic Price Based on User Comments. Data Analysis and Knowledge Discovery, 2019, 3(7): 42-51.
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