Simulating Family Conversations using LLMs: Demonstration of Parenting Styles
<|reference_start|>Simulating Family Conversations using LLMs: Demonstration of Parenting Styles: 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.<|reference_end|>
@article{ye2024simulating,
    title={Simulating Family Conversations using LLMs: Demonstration of Parenting
  Styles},
    author={Frank Tian-fang Ye (1), Xiaozi Gao (2) ((1) Department of Applied
  Social Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, (2)
  Department of Early Childhood Education, The Education University of Hong
  Kong, Hong Kong SAR)},
    journal={arXiv preprint arXiv:2403.06144},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.06144},
    primaryClass={cs.CY}
}