Comparing User Perspectives in a Virtual Reality Cultural Heritage Environment

Virtual reality enables the creation of personalized user experience that brings together people of different cultures and ethnicity. We consider a novel concept of virtual reality innovation in museums, which is cognitively grounded and supported by data and their semantics, to enable users sharing their experiences, as well as to take the perspective of other users, with the ultimate goal of increasing social cohesion. The implementation of this scenario requires an autonomous artificial system that detects emotions and values from a dialogue involving museum visitors who express their personal point of view, listen to those from other visitors, and possibly take the perspective of others. An important feature of this system is the ability of detecting similarity and dissimilarity between user perspectives expressed in speech, when exposed to artworks. This ability helps defining an effective strategy for sharing diverse user perspectives for increasing social cohesion. Moreover, it enables an unbiased quantification of the success of the interaction in terms of change in the user perspective. Based on results from previous work, we employ the Ekman’s emotion model and Haidt’s moral value model to extract emotional and moral value profiles from user descriptions of artworks. We propose a novel method for measuring the similarity between user perspectives by comparing emotional and moral value profiles. Our results show that the employment of unsupervised text classification models is a promising research direction for this task.