---
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)](https://www.worldvaluessurvey.org/wvs.jsp)**: A global network of social scientists studying changing values and their impact on social and political life.
- **[General Social Survey (GSS-2022)](https://gss.norc.org/About-The-GSS)**: 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)](http://cgss.ruc.edu.cn/English/Home.htm)**: The earliest nationwide and continuous academic survey in China collecting data at multiple levels of society, community, family, and individual.
- **[Ipsos Understanding Society survey](https://www.ipsos.com/en-uk/understanding-society)**: The preeminent online probability-based panel that accurately represents the adult population of the United States.
- **[American Trends Panel](https://www.pewresearch.org/our-methods/u-s-surveys/the-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](https://doi.org/10.25940/ROPER-31120147)**: Surveys a diverse group of 1,023 adults aged 18 or older, including 311 Democrats, 290 Republicans, and 312 independents.
- **[Chinese Social Survey](http://css.cssn.cn/css\_sy/)**: 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](https://www.sciencedirect.com/science/article/pii/S030645732500041X?dgcid=author)

## Purpose
This dataset enables:
1. Evaluation of LLMs' cultural value alignment through survey response simulation
2. Comparison of model-generated preference distributions against human reference data
3. Analysis of how model architecture and training choices impact value alignment
4. 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
1. **Txt Files**: Original survey questions in txt format, maintaining survey integrity
2. **Characters**: Demographic breakdowns including:
   - Age groups (under 29, 30-49, over 50)
   - Gender (male, female)
   - Dominant demographic characteristics per question
3. **Preference Distributions**: Statistical distributions of human responses for benchmark comparison

## Usage Guidelines
For implementation details and code examples, visit our [GitHub repository](https://github.com/alexc-l/DEF-Value-investigation).

## 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: alecliu@ontoweb.wust.edu.cn
- Technical support: [GitHub Issues](https://github.com/alexc-l/DEF-Value-investigation/issues)

## Citation
```bibtex
@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},
}
```