  A natural conversational interface that allows longitudinal symptom tracking
would be extremely valuable in health/wellness applications. However, the task
of designing emotionally-aware agents for behavior change is still poorly
understood. In this paper, we present the design and evaluation of an
emotion-aware chatbot that conducts experience sampling in an empathetic
manner. We evaluate it through a human-subject experiment with N=39
participants over the course of a week. Our results show that extraverts
preferred the emotion-aware chatbot significantly more than introverts. Also,
participants reported a higher percentage of positive mood reports when
interacting with the empathetic bot. Finally, we provide guidelines for the
design of emotion-aware chatbots for potential use in mHealth contexts.
