This paper presents an experimental study that analyzes how conversational agents activate human communication in thought-evoking multi-party dialogues between multi-users and multi-agents. A thought-evoking dialogue, which is a kind of interaction in which agents act on user willingness to provoke user thinking, has the potential to stimulate multi-party interaction. In this paper, we focus on quiz-style multi-party dialogues between two users and two agents as an example of a thought-evoking multi-party dialogue. The experiment results showed that the presence of a peer agent significantly improved user satisfaction and increased the number of user utterances. We also found that agent empathic expressions significantly improved user satisfaction, raised user ratings of a peer agent, and increased user utterances. Our findings will be useful for stimulating multi-party communication in various applications such as educational agents and community facilitators.

SUMMARYThis paper presents an experimental study that analyzes how conversational agents activate human communication in thoughtevoking multi-party dialogues between multi-users and multi-agents. A thought-evoking dialogue is a kind of interaction in which agents act to provoke user thinking, and it has the potential to activate multi-party interactions. This paper focuses on quiz-style multi-party dialogues between two users and two agents as an example of thought-evoking multi-party dialogues. The experimental results revealed that the presence of a peer agent significantly improved user satisfaction and increased the number of user utterances in quiz-style multi-party dialogues. We also found that agents' empathic expressions significantly improved user satisfaction, improved user ratings of the peer agent, and increased the number of user utterances. Our findings should be useful for activating multi-party communications in various applications such as pedagogical agents and community facilitators. key words: multi-party interaction, dialogue systems, human-agent interaction, human-robot interaction