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Discovering Next Generation Product Innovations by Identifying Lead User Preferences Expressed Through Large Scale Social Media Data

[+] Author Affiliations
Suppawong Tuarob, Conrad S. Tucker

The Pennsylvania State University, University Park, PA

Paper No. DETC2014-34767, pp. V01BT02A008; 12 pages
doi:10.1115/DETC2014-34767
From:
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1B: 34th Computers and Information in Engineering Conference
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4629-2
  • Copyright © 2014 by ASME

abstract

An innovative consumer (a.k.a. a lead user) is a consumer of a product that faces needs unknown to the public. Innovative consumers play important roles in the product development process as their ideas tend to be innovatively unique and can be potentially useful for development of next generation, innovative products that better satisfy the market needs. Oftentimes, consumers portray their usage experience and opinions about products and product features through social networks such as Twitter and Facebook, making social media a viable, rich in information, and large-scale source for mining product related information. The authors of this work propose a data mining methodology to automatically identify innovative consumers from a heterogeneous pool of social media users. Specifically, a mathematical model is proposed to identify latent features (product features unknown to the public) from social media data. These latent features then serve as the key to discover innovative users from the ever increasing pool of social media users. A real-world case study, which identifies smartphone lead users in the pool of Twitter users, illustrates promising success of the proposed models.

Copyright © 2014 by ASME

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