An Affordance-Based Online Review Analysis Framework
One of the main tasks of today's data-driven design is to learn customers' concerns from the feedback data posted on the internet, to drive smarter and more profitable decisions during product development. Feature-based opinion mining was first performed by the computer and design scientis...
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creator | Hou, Tianjun Yannou, Bernard Leroy, Yann Poirson, Emilie |
description | One of the main tasks of today's data-driven design is to learn customers' concerns from the feedback data posted on the internet, to drive smarter and more profitable decisions during product development. Feature-based opinion mining was first performed by the computer and design scientists to analyse online product reviews. In order to provide more sophisticated customer feedback analyses and to understand in a deeper way customer concerns about products, the authors propose an affordance-based online review analysis framework. This framework allows understanding how and in what condition customers use their products, how user preferences change over years and how customers use the product innovatively. An empirical case study using the proposed approach is conducted with the online reviews of Kindle e-readers downloaded from amazon.com. A set of innovation leads and redesign paths are provided for the design of next-generation e-reader. This study suggests that bridging data analytics with classical models and methods in design engineering can bring success for data-driven design. |
doi_str_mv | 10.1017/dsi.2019.252 |
format | Conference Proceeding |
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source | Cambridge University Press Wholly Gold Open Access Journals; EZB-FREE-00999 freely available EZB journals |
subjects | Artificial Intelligence Computer Aided Engineering Computer Science Customer feedback Customers Data mining Design engineering E-books Electronic commerce Empirical analysis Engineering Sciences Feedback Modeling and Simulation Other Product development Product reviews Redesign |
title | An Affordance-Based Online Review Analysis Framework |
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