Modelling user trust in chatbots: the role of anthropomorphic cues and social responses in information services

Abstract

Introduction. Chatbots, as an emerging form of information technology, are increasingly integrated into information services worldwide, yet how their anthropomorphic design features shape users’ psychosocial responses remains underexplored. This study builds on the Computers Are Social Actors (CASA) paradigm and examines the effects of chatbots’ anthropomorphic cues on users’ perceived social presence, parasocial interaction, and trust in chatbots. Method. A between-subjects experiment was conducted with 195 participants randomly assigned to interact with either a human-like or a machine-like chatbot. Analysis. The data were analysed using SPSS and AMOS. The main analyses included reliability and validity testing, descriptive and correlation analyses, and mediation analysis conducted with the PROCESS macro. Results. Participants in the human-like chatbot group reported higher levels of social presence. Anthropomorphism significantly affected social presence, which in turn indirectly contributed to trust. Social presence served as a key mediator linking anthropomorphism to trust, whereas parasocial interaction did not demonstrate a significant effect. Conclusion. These findings extend the applicability of the CASA paradigm in human-AI interaction and offer implications for improving user experience, optimising chatbot effectiveness, and guiding human-centred information system design. This study also underscores the importance of fostering responsible and ethical use of chatbot technologies.