Article

Inferring the Public Mind: Accuracy and Biases in Out-of-Sample Public Opinion Estimation with Large Language Models

2025-10-20

Abstract excerpt

<p>The emergence of large language models (LLMs) offers a promising cost-effective alternative for assessing public opinion. However, most prior research has focused on simulating individual personas using past surveys, leaving it unclear whether LLMs can accurately estimate out-of-sample public opinion at the societal level. We address this gap with three studies that systematically evaluate the accuracy, bias, a...

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Literature Corpus work: 0e44f304-894c-560d-acf9-e07a4bb16778
DOI: 10.31234/osf.io/3g2tu_v1

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