Discovering product feature and affective associations through collaborative tagging

Affective or kansei design is a field of design engineering that concerns with designing emotionally pleasing products. One of the challenging issues in this area is to successfully understand customers´ affective needs and to interpret it in terms of product design elements. Previous studies have attempted to obtain customer´s affective needs using manual approaches, e.g. survey, which is time-consuming and a costly process. In relation, the study for such a need is usually limited to a number of product features only. In this paper, we proposed a collaborative tagging approach for discovering product features, affective description and their associations from product review analysis. Specifically, we have discussed on the tagging task assignment, tags aggregation and performance analysis of our proposal. A case study on discovering feature-affective associations from car reviews is reported to showcase the feasibility of our approach.