Mining customer product reviews for product development: A summarization process

Tianjun Hou (1) , Bernard Yannou (1) , Yann Leroy (1) , Emilie Poirson (2, 3)

1 LGI - Laboratoire Génie Industriel - EA 2606
2 LS2N - Laboratoire des Sciences du Numérique de Nantes
3 LS2N - équipe PACCE - Perception, Action, Cognition pour la Conception et l’Ergonomie

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.

Mots clés: knowledge acquisition; online reviews; user requirement; product design; decision support

Domaines: Ingénierie assistée par ordinateur; Autre; Intelligence artificielle [cs.AI]; Modélisation et simulation

Tianjun Hou, Bernard Yannou, Yann Leroy, Emilie Poirson. Mining customer product reviews for product development: A summarization process. Expert Systems with Applications, 2019, 132, pp.141-150. ⟨10.1016/j.eswa.2019.04.069⟩. ⟨hal-02434235⟩