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.

翻译：对话代理日益成为日常数字交互的中介，但其沟通风格对用户体验和任务完成度的影响尚不明确。为填补这一研究空白，本文报告了一项被试间用户研究的结果，参与者与名为NAVI的聊天机器人（协助用户在基于交互式地图的二维导航任务中）的两个版本之一进行交互。两个聊天机器人版本仅在沟通风格上存在差异：一种风格友好且具支持性，另一种则直接且以任务为中心。研究结果表明，友好风格仅能提升女性参与者的主观满意度并显著提高其任务完成率，而在无聊天机器人的控制条件下未观察到女性与男性参与者之间存在基线差异。此外，我们几乎没有发现用户模仿聊天机器人风格的证据，表明语言适应效应有限。这些发现凸显了开发对用户和任务敏感的对话代理的重要性，并证实沟通风格的个性化能够有效提升交互质量与任务表现。