AI-Augmented Surveys: Leveraging Large Language Models and S…
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- DOI 10.48550/arxiv.2305.09620
- OpenAlex ID W4377009982
- Type Preprint
- Language EN
- Published 16 May 2023
- Source arXiv (Cornell University)
- Publisher Cornell University
- Countries 1
- Institutions 2
- Added 19 May 2023
- Updated 29 Oct 2026
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AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction
Preprint 2023 EN Green
Nationally representative surveys track public opinion, yet they ask only a limited set of questions each year, limiting its potential to capture historical changes. To fill this gap, we develop a large language model (LLM)-based framework for predicting missing responses in repeated cross-sectional surveys by incorporating embeddings for questions, respondents, and survey periods. We introduce tw…
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2 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Kim, Junsol | University of Chicago (US) | — |
| 2 | Byungkyu Lee | New York University (US) |
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