Automatic Emotional Reactions Identification: A Software Tool for Offline User Experience Research
Current affective response studies lack dedicated data analysis procedures and tools for automatically annotating and triangulating emotional reactions to game-related events. The development of such a tool would potentially allow for both a deeper and more objective analysis of the emotional impact of digital media stimuli on players, as well as towards the rapid implementation of this type of studies. In this paper we describe the development of such a tool that enables researchers to conduct objective a posteriori analyses, without disturbing the gameplay experience, while also automating the annotation and emotional response identification process. The tool was designed in a data-independent fashion and allows the identified responses to be exported for further analysis in third-party statistical software applications.
KeywordsPlayer modelling digital media emotional reaction identification
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