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論文タイトル：Does the favorite-anime-character-imitating chatbot support a user’s self-disclosure?
著者：Zhongming Qin, Megumi Yasuo, Junjie Shan, Kazuho Yamaura, Yoko Nishihara
概要：This study aims to support people’s self-disclosure by using a chatbot that imitates animated characters. Although self-disclosure is required during important life events, people tend to have few opportunities to express their own thoughts.
In this paper, we implemented a chatbot that could imitate different actual anime characters using a large language model (LLM). By having users take on conversations with their favorite characters, we observed its effect in supporting users’ self-disclosure. We prepared 11 anime characters’ setting prompts and provided a user interface to chat with the chatbot. In evaluation experiments, we compared the support effect of favorite and unfavorite characters on users’ self-disclosure. Experimental results showed that the acceptance rate of the chatbot’s given hints increased if the participants chose their favorite anime characters. We found that chatting with a favorite anime character chatbot could support participants’ self-disclosure more effectively.
書誌情報：27th International Conference on Human-Computer Interaction, pp. 137-147
発表日：2025年6月27日