Consumer preference estimation from Twitter classification: Validation and uncertainty analysis

DS 75-7: Proceedings of the 19th International Conference on Engineering Design (ICED13), Design for Harmonies, Vol.7: Human Behaviour in Design, Seoul, Korea, 19-22.08.2013

Year: 2013
Editor: Udo Lindemann, Srinivasan V, Yong Se Kim, Sang Won Lee, John Clarkson, Gaetano Cascini
Author: Stone, Thomas Michael; Choi, Seung-Kyum
Series: ICED
Institution: Georgia Institute of Technology, United States of America
Page(s): 457-466
ISBN: 978-1-904670-50-6
ISSN:  2220-4334


In recent years, the membership and activity of Twitter, Facebook, blogs, and other user-generate content sites has experience significant growth. Users express their opinions regarding a wide range of topics, including consumer products and services. Thus, these sites have the potential to facilitate product design via the extraction of consumer opinion and sentiment regarding product features. A key challenge is how to appropriately extract consumer preferences from the messages. This challenge is addressed with respect to Twitter using a smartphone case study. Twitter messages regarding particular smartphone attributes are classified according to sentiment: positive, negative, or neutral. This sentiment information is then used to develop an estimate of consumer preference for particular smartphone attributes, such as battery life or screen size. Uncertainty analysis is conducted in order to assess the effects of sentiment classification accuracy. Validation techniques indicate that a revised framework would be useful for predicting consumer decisions and facilitating product design; however refinement in terms of comprehensiveness and accuracy or needed.

Keywords: Decision making, new product development, design theory, sentiment classification, consumer behavior


Please sign in to your account

This site uses cookies and other tracking technologies to assist with navigation and your ability to provide feedback, analyse your use of our products and services, assist with our promotional and marketing efforts, and provide content from third parties. Privacy Policy.