metadata

license: cc-by-nc-4.0
task_categories:
  - question-answering
language:
  - zh
  - en
tags:
  - social
  - survey
  - evaluation
  - simulation
pretty_name: DEFSurveySim
size_categories:
  - 1K<n<10K

Dataset Card for DEFSurveySim

Dataset Summary

This dataset comprises carefully selected questions about human value preferences from major social surveys:

World Values Survey (WVS-2023): A global network of social scientists studying changing values and their impact on social and political life.
General Social Survey (GSS-2022): A survey of American adults monitoring trends in opinions, attitudes, and behaviors towards demographic, behavioral, and attitudinal questions, plus topics of special interest.
Chinese General Social Survey (CGSS-2018): The earliest nationwide and continuous academic survey in China collecting data at multiple levels of society, community, family, and individual.
Ipsos Understanding Society survey: The preeminent online probability-based panel that accurately represents the adult population of the United States.
American Trends Panel: A nationally representative online survey panel, consisting of over 10,000 randomly selected adults from across the United States.
USA Today/Ipsos Poll: Surveys a diverse group of 1,023 adults aged 18 or older, including 311 Democrats, 290 Republicans, and 312 independents.
Chinese Social Survey: Longitudinal surveys focus on labor and employment, family and social life, and social attitudes.

The data supports research published on Information Processing & Management titled: Towards Realistic Evaluation of Cultural Value Alignment in Large Language Models: Diversity Enhancement for Survey Response Simulation

Purpose

This dataset enables:

Evaluation of LLMs' cultural value alignment through survey response simulation
Comparison of model-generated preference distributions against human reference data
Analysis of how model architecture and training choices impact value alignment
Cross-cultural comparison of value preferences between U.S. and Chinese populations

Data Structure

DEF_survey_sim/
├── Characters/
│ ├── US_survey/
│ │ ├── Character.xlsx
│ │ └── ...
│ └── CN_survey/
│   ├── Character.xlsx
│   └── ...
├── Pref_distribution/
│ ├── usa_ref_score_all.csv
│ └── zh_ref_score_all.csv
├── Chinese_questionaires.txt
└── English_questionaires.txt

Data Format Details

Txt Files: Original survey questions in txt format, maintaining survey integrity
Characters: Demographic breakdowns including:
- Age groups (under 29, 30-49, over 50)
- Gender (male, female)
- Dominant demographic characteristics per question
Preference Distributions: Statistical distributions of human responses for benchmark comparison

Usage Guidelines

For implementation details and code examples, visit our GitHub repository.

Limitations and Considerations

Surveys were not originally designed for LLM evaluation
Cultural context and temporal changes may affect interpretation
Response patterns may vary across demographics and regions
Limited construct validity when applied to artificial intelligence

Contact Information

Research inquiries: [email protected]
Technical support: GitHub Issues

Citation

@article{LIU2025104099,
title = {Towards realistic evaluation of cultural value alignment in large language models: Diversity enhancement for survey response simulation},
journal = {Information Processing & Management},
volume = {62},
number = {4},
pages = {104099},
year = {2025},
issn = {0306-4573},
doi = {https://doi.org/10.1016/j.ipm.2025.104099},
url = {https://www.sciencedirect.com/science/article/pii/S030645732500041X},
author = {Haijiang Liu and Yong Cao and Xun Wu and Chen Qiu and Jinguang Gu and Maofu Liu and Daniel Hershcovich},
keywords = {Evaluation methods, Value investigation, Survey simulation, Large language models, U.S.-china cultures},
}