Do LLMs Ask the Right Questions? Evaluating GPT-Generated Surveys as Instruments for Measuring Social Attitudes
Understanding human beliefs and social attitudes often relies on carefully designed survey instruments. Recent work has suggested that large language models (LLMs) could automate parts of this process by generating surveys at scale, raising questions about the comparability of such instruments to literature-grounded, human-designed surveys. We present a controlled empirical comparison between GPT-generated surveys and established survey baselines across three social domains: climate change, immi
Researchers compared GPT-generated surveys to human-designed ones across three social domains. The GPT-generated surveys captured dominant attitudinal divisions, but showed differences in belief structure resolution. They suggest LLM-generated surveys are suited for exploratory and large-scale analyses.
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