Synthetic Replacements for Human Survey Data? The Perils of Large Language Models
James Bisbee,
Joshua D. Clinton,
Cassy Dorff
et al.
Abstract:Large language models (LLMs) offer new research possibilities for social scientists, but their potential as “synthetic data” is still largely unknown. In this paper, we investigate how accurately the popular LLM ChatGPT can recover public opinion, prompting the LLM to adopt different “personas” and then provide feeling thermometer scores for 11 sociopolitical groups. The average scores generated by ChatGPT correspond closely to the averages in our baseline survey, the 2016–2020 American National Election Study… Show more
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