AI RESEARCH
Designing Synthetic Discussion Generation Systems: A Case Study for Online Facilitation
arXiv CS.LG
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ArXi:2503.16505v4 Announce Type: replace-cross A critical challenge in social science research is the high cost associated with experiments involving human participants. We identify Synthetic Discussion Generation (SDG), a novel Natural Language Processing (NLP) direction aimed at creating simulated discussions that enable cost-effective pilot experiments and develop a theoretical, task-agnostic framework for designing, evaluating, and implementing these simulations. We argue that the use of.