User Perceptions of Extraversion in Chatbots after Repeated Use

Whilst imbuing robots and voice assistants with personality has been found to positively impact user experience, little is known about user perceptions of personality in purely text-based chatbots. In a within-subjects study, we asked N=34 participants to interact with three chatbots with different levels of Extraversion (extraverted, average, introverted), each over the course of four days. We systematically varied the chatbots' responses to manipulate Extraversion based on work in the psycholinguistics of human behaviour. Our results show that participants perceived the extraverted and average chatbots as such, whereas verbal cues transferred from human behaviour were insufficient to create an introverted chatbot. Whilst most participants preferred interacting with the extraverted chatbot, participants engaged significantly more with the introverted chatbot as indicated by the users' average number of written words. We discuss implications for researchers and practitioners on how to design chatbot personalities that can adapt to user preferences.

• Human-centered computing → Empirical studies in HCI; Natural language interfaces.