October 12, 2025Open Access

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation

View Full Paper

Ask AI

Bookmark

LLMs can generate demographically coherent responses in surveys, enhancing data collection methods.
The study evaluates different simulation methods, including partial and full attribute simulations, for response accuracy.
LLM-S^3 is introduced as a comprehensive benchmark for assessing survey simulations across various sociological domains.
Findings indicate that context and prompt design significantly impact the fidelity of simulations generated by LLMs.

Discussion

No takes yet. Share an insight, caveat, or question.

Implication

This analysis evaluates large language models' ability to generate accurate responses for virtual surveys, suggesting new methods for cost-effective sociological research.

Cite This Study

Zhao et al. (2025) studied this question.

synapsesocial.com/papers/68ec1be02b8fa9b2b78ad027 https://doi.org/10.48550/arxiv.2509.06337

View Full Paper

Ask AI

Bookmark

Implication

This analysis evaluates large language models' ability to generate accurate responses for virtual surveys, suggesting new methods for cost-effective sociological research.

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation

Key Points

Discussion

Implication

Cite This Study

Large Language Models as Virtual Survey Respondents: Evaluating Sociodemographic Response Generation

Key Points

Discussion

Implication

Cite This Study

Also Consider

Also Consider