A semantic discontinuity detection (SDD) method for comparing designers' product expressions with users' product impressions. (May 2019) - Khalaj, Javad; Pedgley, Owain
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. Highlights: Method comparing designers' intended product expressions against users' product impressions. 'Semantic Network Clustering' technique to organize diverse impression statements. Uncovers links between semantic appraisals and physical product features. Generates evidence to assist re-designing for reduced semantic discontinuity.