Nozaki, Y.（野崎 優樹） (2025).
Sharing motives shape interface preferences for social sharing of Emotion with conversational AI.
対話型AIに感情の社会的共有を行う際の動機がインターフェースの選好に及ぼす影響
Computers in Human Behavior: Artificial Humans, Article 100229.
https://doi.org/10.1016/j.chbah.2025.100229
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.