A semantic discontinuity detection (SDD) method for comparing designers' product expressions with users' product impressions

Khalaj J., Pedgley O.

DESIGN STUDIES, vol.62, pp.36-67, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 62
  • Publication Date: 2019
  • Doi Number: 10.1016/j.destud.2019.02.002
  • Journal Name: DESIGN STUDIES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.36-67
  • Keywords: semantics, perception, communication, research methods, design practice, APPEARANCE, RESPONSES, INTENT, FORM
  • Middle East Technical University Affiliated: Yes

Abstract

Designers exert substantial effort to define an intended user experience (UX) for a product, service or system. However, discontinuities can arise when the actual UX of users differs from the design intent. This paper presents a `Semantic Discontinuity Detection' (SDD) method capable of locating discontinuities between (i) realized product semantics, based on users' initial visual impression of a product, and (ii) intended product semantics, based on the originating designer's visual product expression. The experimental design includes a new technique termed 'Semantic Network Clustering' (SNC) to organize diverse product appraisal lexicon. Data generated by the method provides evidence to assist re-designing for reduced semantic discontinuity. The method is suggested to be suitably agile for a wide range of UX intent-realization research. (C) 2019 Elsevier Ltd. All rights reserved.