Comparing dialogue motivation in human–human and human–robot conversations: Role of topic depth and relationship closeness

Dialogue robots are increasingly used in various applications, such as entertainment, welfare, and education. This study investigated factors influencing user motivation to engage in dialogue with robots, focusing on three key variables: topic depth, relationship closeness, and whether the conversation partner is human or a robot. An online experiment involving 183 participants revealed the following patterns: (1) dialogue motivation tended to decrease as the topic became deeper in both human–human and human–robot interactions; (2) dialogue motivation tended to increase with greater relationship closeness in both interaction types; (3) the effect of relationship closeness on dialogue motivation tended to be more pronounced for deep topics than shallow ones; and (4) people were more likely to prefer humans for shallow topics but favor robots for deeper discussions. These findings enhance theoretical understanding of dialogue motivation in human–robot interactions and provide insights into optimizing the application of dialogue robots across different domains. • Motivation tends to decrease as topic depth increases in human and robot interactions. • Motivation tends to increase with closer relationships in human and robot interactions. • Relationship closeness has a stronger effect on motivation for deep topics than shallow ones. • Humans tend to be preferred for shallow topics; robots tend to be preferred for deeper ones.