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

Erik Derner, Dalibor Kučera, Aditya Gulati, Ayoub Bagheri, Nuria Oliver

TL;DR

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 show that the friendly style increases subjective satisfaction and significantly improves task completion rates among female participants only.

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.

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

TL;DR

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 show that the friendly style increases subjective satisfaction and significantly improves task completion rates among female participants only.

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.
Paper Structure (65 sections, 4 figures, 18 tables)

This paper contains 65 sections, 4 figures, 18 tables.

Table of Contents

  1. Introduction
  2. Related work
  3. Communication style in conversational agents
  4. Social alignment and linguistic accommodation
  5. Gender and relational orientation in HCI
  6. Effects of prior chatbot experience on expectations and evaluations
  7. Research Questions
  8. RQ1 - Communication style and user outcomes
  9. RQ2 – Moderation by user characteristics
  10. RQ3 – Linguistic accommodation
  11. User study
  12. Task: Map-based 2D navigation as a testbed for communication style
  13. Design
  14. Map-based 2D navigation task
  15. Control condition (no chatbot)
  16. ...and 50 more sections

Figures (4)

  • Figure 1: Overview of the study design. Participants completed a fictional map-based 2D navigation task to locate an embassy on a map (top). They followed static instructions (Control) or they interacted with one of the two versions of the chatbot NAVI, differing only in the communication style: Friendly (supportive, warm) or Direct (concise, task-focused). Both objective and subjective measures (bottom-left) were collected to address three research questions (bottom-right).
  • Figure 2: Explanations of the user interface presented to the participants in the control condition, including the map legend.
  • Figure 3: Explanations of the user interface used by the participants to interact with NAVI.
  • Figure 4: Excerpts of exemplary conversations with the friendly (left) and direct (right) versions of NAVI.