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Title:Extracting customer concerns from online reviews of series products for competitor analysis
Author(s):Yan, Sixing; Jin, Jian; Ji, Ping; Geng, Zihao
Subject(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.
Issue Date:2017
Publisher:iSchools
Citation Info:Yan, S., Jin, J., Ji, P., & Geng, Z. (2017). Extracting Customer Concerns from Online Reviews of Series Products for Competitor Analysis. In iConference 2017 Proceedings (pp. 142–156). https://doi.org/10.9776/17017
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper/Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/96669
DOI:https://doi.org/10.9776/17017
Rights Information:Copyright 2017 Sixing Yan, Jian Jin, Ping Ji, Zihao
Date Available in IDEALS:2017-07-27


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