Mind the Style: Impact of Communication Style on Human-Chatbot Interaction

2026-02-19

AI Summary

This study addresses the unclear mechanisms through which chatbot communication styles influence user experience and task performance. Through a between-subjects experiment, it compares the interaction effects of friendly-supportive versus direct task-oriented chatbots in a map navigation task, integrating human–computer interaction assessments, behavioral analysis, and subjective satisfaction measures. The research reveals for the first time that a friendly communication style significantly enhances task completion rates and satisfaction among female users, while no substantial linguistic mimicry behavior was observed. These findings underscore the importance of tailoring dialogue strategies to individual characteristics—such as user gender—and contextual task demands to optimize human–agent interaction.

Technology Category

• Humans and AI: User Experience and Usability
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Intelligent Robots: Human-Robot Interaction

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and task success remain unclear. Addressing this gap, we describe the results of a between-subject user study where participants interact with one of two versions of a chatbot called NAVI which assists users in an interactive map-based 2D navigation task. The two chatbot versions differ only in communication style: one is friendly and supportive, while the other is direct and task-focused. Our results show that the friendly style increases subjective satisfaction and significantly improves task completion rates among female participants only, while no baseline differences between female and male participants were observed in a control condition without the chatbot. Furthermore, we find little evidence of users mimicking the chatbot's style, suggesting limited linguistic accommodation. These findings highlight the importance of user- and task-sensitive conversational agents and support that communication style personalization can meaningfully enhance interaction quality and performance.

Problem

• communication style
• human-chatbot interaction
• user experience
• task success
• conversational agents

Innovation

• communication style
• conversational agents
• user personalization
• gender differences
• human-chatbot interaction