Effects of self-disclosure and empathy in human-computer dialogue

To build trust or cultivate long-term relationships with users, conversational systems need to perform social dialogue. To date, research has primarily focused on the overall effect of social dialogue in human-computer interaction, leading to little work on the effects of individual linguistic phenomena within social dialogue. This paper investigates such individual effects through dialogue experiments. Focusing on self-disclosure and empathic utterances (agreement and disagreement), we empirically calculate their contributions to the dialogue quality. Our analysis shows that (1) empathic utterances by users are strong indicators of increasing closeness and user satisfaction, (2) the system's empathic utterances are effective for inducing empathy from users, and (3) self-disclosure by users increases when users have positive preferences on topics being discussed.