computational social science

Modeling Community Attitude through Reaction Tone: A Human-AI Collaborative Framework for Evaluating LLM Alignment with Linguistic Behaviors in Online Communities

This research introduces CARE (Community-Aware Reaction Evaluation), a framework designed to benchmark large language models' (LLMs) ability to simulate community discourse against authentic human responses to real-world news. Through human-AI collaboration, the study identifies a "realism gap," showing that explicit community prompts do not inherently enhance the fidelity of LLM simulations.