Entropy-based eye-tracking analysis when a user watches a PRVA's recommendations

We conducted three experiments to discover the effect of a virtual agent's state transition on a user's eye gaze. Many previous studies showed that an agent's state transition affects a user's state. We focused on two kinds of transitions, the internal state transition and appearance state transition. In this research, we used a product recommendation virtual agent (PRVA) and aimed to discover the effect of its state transitions on users' eye gaze as it made recommendations. We used entropy-based analysis to visualise the deviation of a user's fixations. In experiment 1, the PRVA made recommendations without state transitions. In experiment 2, the amount of the PRVA's knowledge transitioned from low to high during the recommendations. This is an internal state transition. In experiment 3, the PRVA's facial expressions and gestures transitioned from a neutral to positive emotion during the recommendations. This is an appearance state transition. As a result, both the entropy-based analysis and fixation duration based analysis showed significant differences in experiment 3. These results show that an agent's appearance state transitions cause a user's eye gaze to transition.