Automatic identification of product usage contexts from online customer reviews

Dedy Suryadi, Harrison Kim

Research output: Contribution to journalConference articlepeer-review


There are three product design contexts that may significantly affect the design of a product and customer preferences towards product attributes, i.e. customer context, market context, and usage context factors. The conventional methods to gather product usage contexts may be costly and time consuming to conduct. As an alternative, this paper aims to automatically identify product usage contexts from publicly available online customer reviews. The proposed methodology consists of Preprocessing, Word Embedding, and Usage Context Clustering stages. The methodology is applied to identify usage contexts from laptop customer reviews, which results in 16 clusters of usage contexts. Furthermore, analyzing the review sentences explains the separation of "playing games" -which is more related to casual gaming, and "gaming rig" -which implies high computing power requirements. Finally, comparing customer review with manufacturer's product description may reveal a discrepancy to be investigated further by product designer, e.g. a customer suggests a laptop for basic use, although the manufacturer's description describes it for heavy use.

Original languageEnglish (US)
Pages (from-to)2507-2516
Number of pages10
JournalProceedings of the International Conference on Engineering Design, ICED
StatePublished - 2019
Event22nd International Conference on Engineering Design, ICED 2019 - Delft, Netherlands
Duration: Aug 5 2019Aug 8 2019


  • Crowdsourcing
  • Design informatics
  • User centred design

ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Modeling and Simulation


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