【目的】針對特征價格研究缺乏特征選取標準的現狀,基于大規模用戶評論,提出一種商品特征的挖掘與選取方法,對特征價格研究進行改進和延伸。【方法】提取用戶評論的關鍵詞,通過關鍵詞聚類獲取消費者顯著偏好的商品特征,在此基礎上建立特征價格模型反映特征價格。為驗證模型的科學性和有效性,以廣州在售新樓盤為例進行實證研究。【結果】基于用戶評論挖掘出7個消費者顯著偏好的樓盤特征,以此建立的模型擬合優度達0.760, DW統計量為2.013,樓盤有價特征的用戶偏好度和價格影響力的相關系數達0.989。【局限】實驗數據來源僅局限于房地產網站。【結論】相比已有研究,基于用戶評論選取特征構建的模型在擬合優度上有一定提高,能夠較準確地評估商品價格,有效避免特征之間的多重共線性問題,還能延伸探究消費者的偏好理性,給企業和消費者行為提供一定的指導依據。

[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.