Sharing motives shape interface preferences for social sharing of emotion with conversational AI

Social sharing of emotion with conversational AI is a growing phenomenon. While social presence theory suggests richer, more human-like interfaces enhance social connection, how interface design influences users’ willingness to share emotions with conversational AI depending on their motives remains underexplored. Using an experimental vignette methodology, this study examines the influence of interface type (text vs. voice; without vs. with visual presence) and user motives (seeking cognitive support, social-affective support, or capitalization) on the willingness to share emotions with conversational AI, drawing a comparison with human partners. Based on data from 195 Japanese university students, the results revealed distinct user preferences. For the cognitive and social-affective support motives, users preferred a text-based interface, especially without visual presence (i.e., no avatar). Conversely, for the capitalization motive, an interface featuring visual presence was preferred. Moreover, perceived warmth was positively related to the willingness to share for social-affective support and capitalization motives, whereas perceived competence was positively related to it for cognitive and social-affective support motives. These patterns differed from those found in mediated communication with human partners. These findings refine social presence theory by suggesting that richer, more human-like interfaces are not always superior and underscore the importance of designing conversational AI tailored to user motives from a human-centered perspective. • For negative emotions, users prefer simpler, text-based AI without an avatar. • An AI with a visual avatar is preferred for sharing positive emotional events. • Optimal AI interface design depends on the user’s motive for emotional sharing. • User motives refine social presence theory for human-AI emotional communication.