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Simulating Family Conversations using LLMs: Demonstration of Parenting Styles

2024/03/10 by Frank Tian-Fang Ye, Ye, Frank Tian-fang, Xiaozi Gao +1
Business, Management and Accounting · #Computers and Society (cs.CY) #Dispute Resolution and Class Actions #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.2403.06144

openalex publication_date 2024/03/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This study presents a framework for conducting psychological and linguistic research through simulated conversations using large language models (LLMs). The proposed methodology offers significant advantages, particularly for simulating human interactions involving potential unethical language or behaviors that would be impermissible in traditional experiments with human participants. As a demonstration, we employed LLMs to simulate family conversations across four parenting styles (authoritarian, authoritative, permissive, and uninvolved). In general, we observed that the characteristics of the four parenting styles were portrayed in the simulated conversations. Several strategies could be used to improve the simulation quality, such as including context awareness, employing a few-shot prompting approach or fine-tuning models to cater to specific simulation requirements. Overall, this study introduces a promising methodology for conducting psychological and linguistic research through simulated conversations, while acknowledging the current limitations and proposing potential solutions for future refinement and improvement.

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