Discovering next generation product innovations by identifying lead user preferences expressed through large scale social media data

Suppawong Tuarob, Conrad S. Tucker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

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.

Original languageEnglish (US)
Title of host publication34th Computers and Information in Engineering Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791846292
DOIs
StatePublished - Jan 1 2014
EventASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014 - Buffalo, United States
Duration: Aug 17 2014Aug 20 2014

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume1B

Other

OtherASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2014
CountryUnited States
CityBuffalo
Period8/17/148/20/14

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All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Tuarob, S., & Tucker, C. S. (2014). Discovering next generation product innovations by identifying lead user preferences expressed through large scale social media data. In 34th Computers and Information in Engineering Conference (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1B). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC201434767