Traditional user research methods are challenged for the decision-making in product design and improvement with the updating speed becoming faster, considering limited survey scopes, insufficient samples, and time-consuming processes. This paper proposes a novel approach to acquire useful online reviews from E-commerce platforms, build a product evaluation indicator system, and put forward improvement strategies for the product with opinion mining and sentiment analysis with online reviews. The effectiveness of the method is validated by a large number of user reviews for smartphones wherein, with the evaluation indicator system, we can accurately predict the bad review rate for the product with only 9.9% error. And improvement strategies are proposed after processing the whole approach in the case study. The approach can be applied for product evaluation and improvement, especially for the products with needs for iterative design and sailed online with plenty of user reviews.

中文翻译：

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在线用户评论分析，用于产品评估和改进

考虑到调查范围有限，样本不足和耗时的过程，随着更新速度变得越来越快，传统的用户研究方法面临着产品设计和改进决策方面的挑战。本文提出了一种从电子商务平台上获取有用的在线评论的新颖方法，建立了产品评估指标体系，并提出了通过意见挖掘和在线评论进行情感分析的产品改进策略。该方法的有效性通过对智能手机的大量用户审核来验证，其中，借助评估指标系统，我们可以准确地预测产品的不良审核率，而错误率仅为9.9％。并在案例研究中处理了整个方法之后，提出了改进策略。