Update README.md

README.md

@@ -1,3 +1,80 @@
 ---
 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 described in: [Towards Realistic Evaluation of Cultural Value Alignment in Large Language Models: Diversity Enhancement for Survey Response Simulation]()
+
+## 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
+TODO
+```