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Online review analysis : How to get useful information for innovating and improving products?

Abstract : With the development of e-commerce,consumers have posted large number of onlinereviews on the internet. These user-generated dataare valuable for product designers, as informationconcerning user requirements and preference can beidentified.The objective of this study is to develop an approachto guide product design by analyzing automaticallyonline reviews. The proposed approach consists oftwo steps: data structuration and data analytics.In data structuration, the author firstly proposes anontological model to organize the words andexpressions concerning user requirements in reviewtext. Then, a rule-based natural language processingmethod is proposed to automatically structure reviewtext into the propose ontology.In data analytics, two methods are proposed based onthe structured review data to provide designers ideason innovation and to draw insights on the changes ofuser preference over time. In these two methods,traditional affordance-based design, conjointanalysis, the Kano model are studied andinnovatively applied in the context of big data.To evaluate the practicability of the proposedapproach, the online reviews of Kindle e-readers aredownloaded and analyzed, based on which theinnovation path and the strategies for productimprovement are identified and constructed.
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Submitted on : Monday, February 11, 2019 - 4:06:06 PM
Last modification on : Monday, October 19, 2020 - 10:52:43 AM
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  • HAL Id : tel-02014508, version 1


Tianjun Hou. Online review analysis : How to get useful information for innovating and improving products?. Other. Université Paris Saclay (COmUE), 2018. English. ⟨NNT : 2018SACLC095⟩. ⟨tel-02014508⟩



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