29 citations · 31 across the 5 of their papers we have counts for
5 papers
Think-Before-Speak: From Internal Evaluation to Public Expression in Multi-Agent Social Simulation
Kaiqi Yang, Tai-Quan Peng, Sanguk Lee +1
LLM-based multi-agent simulation offers a promising way to study social interaction, deliberation, and collective opinion dynamics. However, many existing dialogue simulation frame…
Embracing Dialectic Intersubjectivity: Coordination of Different Perspectives in Content Analysis with LLM Persona Simulation
Taewoo Kang, Kjerstin Thorson, Tai-Quan Peng +3
This study attempts to advancing content analysis methodology from consensus-oriented to coordination-oriented practices, thereby embracing diverse coding outputs and exploring the…
Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models
Tai-Quan Peng, Kaiqi Yang, Sanguk Lee +4
As large language models (LLMs) become increasingly embedded in civic, educational, and political information environments, concerns about their potential political bias have grown…
Exploring Social Desirability Response Bias in Large Language Models: Evidence from GPT-4 Simulations
Sanguk Lee, Kai-Qi Yang, Tai-Quan Peng +2
Large language models (LLMs) are employed to simulate human-like responses in social surveys, yet it remains unclear if they develop biases like social desirability response (SDR)…
Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias
S. Lee, T. Q. Peng, M. H. Goldberg +4
Large language models (LLMs) have demonstrated their potential in social science research by emulating human perceptions and behaviors, a concept referred to as algorithmic fidelit…