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Towards Extracting Affordances From Online Consumer Product Reviews

[+] Author Affiliations
Amanda Chou, L. H. Shu

University of Toronto, Toronto, ON, Canada

Paper No. DETC2014-35288, pp. V007T07A030; 10 pages
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 7: 2nd Biennial International Conference on Dynamics for Design; 26th International Conference on Design Theory and Methodology
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4640-7
  • Copyright © 2014 by ASME


We examined online product reviews as a source of novel affordances. Certain affordances may only be discovered through extended use across various environments. User-generated reviews may thus contain unique insights. We analyzed online consumer product reviews from Canadian Tire, one of Canada’s largest retailers. We determined properties of this collection of reviews and commonalities between valuable reviews. In addition to typical challenges associated with natural-language processing, e.g. word-sense disambiguation, we identify characteristics of online consumer reviews that create additional challenges. These challenges include the use of ‘wild English’ and sarcasm in online reviews.

We first present criteria to define and more objectively identify novel affordances from review content. Next, k-means clustering reveals that a combination of syntactical features and high frequency word percentages can separate descriptive from non-descriptive review content. Finally, we identified cue phrases that may indicate higher likelihood of affordance content in a review. Despite existing obstacles, the substantial volume of available online product reviews has potential to become a valuable source of affordances and feedback for designers and retailers alike.

Copyright © 2014 by ASME



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