Emotional Expression in Persuasion by Quadruped Virtual Agents: Toward Cross-Species Design Patterns
2026-08-03 • Human-Computer Interaction
Human-Computer Interaction
AI summaryⓘ
The authors studied how virtual animals like dogs, cats, and horses can persuade people to do tasks like throwing away trash or feeding. They compared how well people understood and acted on the agents' intentions when the animals behaved in species-specific ways, shared behaviors, or only made a single sound (bark). They found that showing emotions and guiding attention helped people understand and change behavior better than just the bark sound. However, it didn’t really matter if the behavior was exactly like each species or shared across animals. This means that for virtual animal helpers, clear emotional cues and easy-to-read intentions are more important than realistic animal movements.
persuasive technologyvirtual agentsquadruped agentsemotional expressionbehavioral intentionpsychological reactanceintention understandingspecies-specific behaviorhuman-AI interaction
Authors
Kaoru Sumi, Souki Osawa
Abstract
Persuasive technologies increasingly use virtual agents to influence attitudes and behavior, but research has focused mainly on humanoid agents. The persuasive design of non-humanoid, quadruped agents remains underexplored, and it is unclear whether emotional expression works consistently across animal species or whether species-specific motion is necessary. We developed virtual dog, cat, and horse agents and compared three behavioral conditions: species-specific behavior, shared behavior across species, and a bark-only baseline. Participants completed everyday tasks involving trash disposal, feeding, and refraining from smartphone use. We evaluated intention understanding, behavioral intention, actual behavior, psychological reactance, discomfort, familiarity, and agent acceptance. In several task contexts, the bark-only baseline produced lower intention-understanding and behavioral scores than the expressive conditions. Emotional expression and attention-guiding cues therefore appear to improve interpretation of agent intention and support behavior change. However, no consistent significant differences emerged between species-specific and shared behavior, suggesting that faithful reproduction of animal-specific motion is not the main determinant of persuasive effectiveness. Psychological reactance and discomfort remained low, while familiarity with an animal species was associated with actual behavior in some conditions. These findings indicate that persuasion by quadruped virtual agents depends more on functional cues, including emotional expression, attention guidance, and intention readability, than on accurate species-specific behavior. The results support cross-species generalizability and provide a basis for reusable design patterns in persuasive technology and human-AI interaction.