Extracting customer concerns from online reviews of series products for competitor analysis

Yan, Sixing; Jin, Jian; Ji, Ping; Geng, Zihao

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https://hdl.handle.net/2142/96669 Copy

Description

Title

Extracting customer concerns from online reviews of series products for competitor analysis

Author(s)

• Yan, Sixing
• Jin, Jian
• Ji, Ping
• Geng, Zihao

Issue Date

2017

Keyword(s)

• Review analysis
• Online reviews
• Competitor analysis
• Series product comparison
• Customer concerns

Abstract

Online reviews provide valuable information for product designers, and the integration of online concerns into new product design has been investigated by different researchers. However, few researchers exploit how to apply online concerns in the competitor analysis about the merits and drawbacks of series products. Accordingly, in this research, a framework is presented to sample representative sentences from online reviews, aiming to highlight similar customer concerns of series products. First, opinionated sentences of specific features are identified. Then, opinionated sentences in the same series products are clustered to extract similar customer concerns. Finally, an optimization problem is formulated for sampling a few representative sentences. With real data from Amazon.com, categories of experiments were conducted to evaluate the effectiveness of the proposed approach. This study explores the possibility about integrating big consumer data into competitor analysis in the market driven product design, which is essentially critical in fierce market competition.

Publisher

iSchools

Series/Report Name or Number

iConference 2017 Proceedings

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/96669

Copyright and License Information

Copyright 2017 Sixing Yan, Jian Jin, Ping Ji, Zihao

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