Interactive Multi-Persona Analysis for a CollaboraTive Framework Using Large Language Models (IMPACTFUL): A Case Study of South Korea's National Assembly

This study investigates how the large language models (LLMs) can improve collective decision-making activities, specifically within the legislative processes of South Korea's National Assembly. By employing LLMs to assimilate and analyze input from multiple stakeholders' legislative decision-making, this approach increases both transparency and the public's grasp of legislative operations. We introduce an innovative multi-persona collaborative framework that highlights the role of LLMs in enhancing understanding of legislative decisions and paves the way for their broader implementation in various social-scientific contexts.