This research set out to identify and structure from online reviews the words and expressions related to customers' likes and dislikes to guide product development. Previous methods were mainly focused on product features. However, reviewers express their preference not only on product features. In this paper, based on an extensive literature review in design science, the authors propose a summarization model containing multiples aspects of user preference, such as product affordances, emotions, usage conditions. Meanwhile, the linguistic patterns describing these aspects of preference are discovered and drafted as annotation guidelines. A case study demonstrates that with the proposed model and the annotation guidelines, human annotators can structure the online reviews with high inter-agreement. As high inter-agreement human annotation results are essential for automatizing the online review summarization process with the natural language processing, this study provides materials for the future study of automatization.

中文翻译：

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为产品开发挖掘客户产品评论：总结过程

本研究旨在从在线评论中识别和构建与客户好恶相关的词语和表达，以指导产品开发。以前的方法主要集中在产品特征上。然而，评论者不仅表达了他们对产品功能的偏好。在本文中，基于广泛的设计科学文献综述，作者提出了一个包含用户偏好多个方面的总结模型，例如产品可供性、情感、使用条件。同时，描述这些偏好方面的语言模式被发现并起草为注释指南。一个案例研究表明，使用所提出的模型和注释指南，人工注释者可以构建具有高度一致性的在线评论。