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Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
Published on: December 23, 2025
Users' prompting strategies and ChatGPT's contextual adaptation shape conversational information-seeking experiences
Haoning Xue1,2, Yoo Jung Oh3, Xinyi Zhou4
1Department of Communication, University of Utah, Utah, USA. haoning.xue@utah.edu.
None:
Conversational AI, such as ChatGPT, is increasingly used for information seeking. However, little is known about how ordinary users actually prompt and how ChatGPT adapts its responses in real-world conversational information seeking (CIS). In this study, a nationally representative sample of 937 U.S. adults engaged in multi-turn CIS with ChatGPT on both controversial and non-controversial topics across science, health, and policy contexts. We analyzed both users' prompting strategies and the communication styles of ChatGPT's responses. The findings revealed behavioral signals of digital divide: only 19.1% of users employed prompting strategies, and these users were disproportionately more educated and Democrat-leaning. Further, ChatGPT demonstrated contextual adaptation: responses to controversial topics contain more cognitive complexity and more external references than to non-controversial topics. Notably, cognitively complex responses were perceived as less favorable but produced more positive issue-relevant attitudes. This study highlights disparities in user prompting behaviors and shows how user prompts and AI responses together shape information-seeking with conversational AI.
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