Methods for Collecting and Analyzing User Experience Information in Online Product Reviews
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摘要: 面向产品设计改进, 提出一种在线产品评论中用户体验信息采集与分析方法。首先构建用户体验要素模型; 然后, 依据要素模型采用分步提取的方法提取单个评论句中的用户情感、产品特征和使用情境三类要素; 最后, 对提取出的用户体验要素信息进行分类整合, 通过定量分析评论数据识别出对用户体验影响较大的产品特征和使用情境。以京东商城上某款智能手机的在线评论为例进行实例验证。实验结果表明, 方法能有效提取在线产品评论中的用户体验要素, 识别对用户体验产生较大影响的产品特征和使用情境, 辅助设计师有针对性地改进产品设计。Abstract: Aiming at the product design improvement, a collection and analysis method of user experience information in online product reviews was proposed. Firstly, an user experience element model was constructed. Then, according to the element model, the user emotion, product feature and usage context in a single review sentence were extracted step by step. Finally, the user experience elements extracted from a single review sentence were classified and integrated, and through quantitative analysis of the review data, the product features and use contexts that have a greater impact on user experience were identified. The method was verified by taking the online reviews of a smart phone on Jingdong Mall as the example. The experimental results show that the method can effectively extract the user experience elements from online product reviews, identify the product features and use contexts that have a great impact on the user experience, and assist designers to improve the product design.
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Key words:
- user experience /
- online product reviews /
- element model /
- design improvement
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表 3 评论挖掘实验结果
评论要素 Precision Recall F-measure 产品特征 89.11% 83.56% 86.24% 使用情境 71.43% 60.50% 65.51% 用户情感 94.85% 91.02% 92.90% 
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