Automatic, Gestural, Voice, Positional, or Cross-Device Interaction? Comparing Interaction Methods to Indicate Topics of Interest to Public Displays

Abstract

Most public and semi-public displays show content that is not related to people passing by. As a result, most passersby completely ignore the displays. One solution to this problem is to give viewers the means to interact explicitly with such displays to convey their interests and thus receive content relevant to them. However, which method of interaction is most appropriate for gathering information on viewers' interests is still an open question. To identify methods appropriate for indicating topics of interest to public displays, we identified a range of dimensions to be considered when setting up public displays. We report a single-user and a multi-user study that use these dimensions to measure the effects of automatic, gestural, voice, positional, and cross-device interest indication methods. Our results enable us to establish guidelines for practitioners and researchers for selecting the most suitable interest indication method for a given scenario. Our results showed that cross-device and automatic methods strongly retain users' privacy. Gestural and positional methods were reported to be a fun experience. However, the gestural method performed better in the single-user study than in the multi-user study in all dimensions.