Effects of Anthropomorphic Design Cues of Chatbots on Users’ Perception and Visual Behaviors

Abstract

Measurement of users’ perception and visual behaviors to anthropomorphic design cues of chatbots can improve our understanding of chatbots and potentially optimize chatbot design. However, as two typical and basic features, how chatbot appearances and conversational styles jointly affect users’ perception and visual behaviors remains unclear. Therefore, this study conducted an eye-tracking experiment to explore users’ perception and visual behaviors. Results indicate that anthropomorphic appearances and human-like conversational styles jointly increased users’ perception of chatbots’ social presence, trust in chatbots, and satisfaction with chatbots. In contrast, on users’ visual behaviors, such a joint effect was not found, although chatbots with higher anthropomorphic appearances and human-like conversational styles triggered more fixation counts and longer dwell time. These findings suggest that anthropomorphic appearance and human-like conversational style can improve users’ perception and attract more visual attention to chatbots. These findings provide theoretical contributions and practical implications for relevant researchers and designers.

Keywords:

• Chatbot appearance
• conversational style
• user perception
• visual behaviors
• eye-tracking

Acknowledgments

We would like to thank all the participants for their involvement in our research. Moreover, we are grateful to extend our gratitude to the editors and the reviewers for their valuable comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant No. 72071035].

Notes on contributors

Jiahao Chen

Jiahao Chen is a PhD student at the Department of Industrial Engineering, School of Business Administration, Northeastern University, China. His research interests include human factors, human-chatbot interaction, user experience design, and human–computer interaction.

Fu Guo

Fu Guo is a professor of Industrial Engineering at School of Business Administration, Northeastern University, China. Her research interests include human factors, Kansei engineering, user experience, human–computer interaction, human–robot interaction, occupational safety and health, and product placement.

Zenggen Ren

Zenggen Ren is a PhD student at the Department of Industrial Engineering, School of Business Administration, Northeastern University, China. His research interests include human factors, Kansei engineering, and human–robot interaction.

Mingming Li

Mingming Li is a PhD candidate at the Department of Industrial Engineering, School of Business Administration, Northeastern University, China. His research interests include human factors, human–robot interaction, user experience design, and human–computer interaction.

Jaap Ham

Jaap Ham is an associated professor in the research group of Human Technology Interaction, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, The Netherlands. He focuses on ambient forms of technology and social forms of technology (such as social robots) to influence people, health behavior, and sustainability.