Anthropic/llm_global_opinions|全球调查数据集|社会研究数据集

---
license: cc-by-nc-sa-4.0
language:
- en
size_categories:
- 1K<n<10K
---
# Dataset Card for GlobalOpinionQA

## Dataset Summary
The data contains a subset of survey questions about global issues and opinions adapted from the [World Values Survey](https://www.worldvaluessurvey.org/) and [Pew Global Attitudes Survey](https://www.pewresearch.org/).

The data is further described in the paper: [Towards Measuring the Representation of Subjective Global Opinions in Language Models](https://arxiv.org/abs/2306.16388).

## Purpose
In our paper, we use this dataset to analyze the opinions that large language models (LLMs) reflect on complex global issues.
Our goal is to gain insights into potential biases in AI systems by evaluating their performance on subjective topics.

## Data Format
The data is in a CSV file with the following columns:
- question: The text of the survey question.
- selections: A dictionary where the key is the country name and the value is a list of percentages of respondents who selected each answer option for that country.
- options: A list of the answer options for the given question.
- source: GAS/WVS depending on whether the question is coming from Global Attitudes Survey or World Value Survey.

## Usage
```python
from datasets import load_dataset
# Loading the data
dataset = load_dataset("Anthropic/llm_global_opinions")
```
## Disclaimer
We recognize the limitations in using this dataset to evaluate LLMs, as they were not specifically
designed for this purpose. Therefore, we acknowledge that the construct validity of these datasets when applied to LLMs may be limited.

## Contact
For questions, you can email esin at anthropic dot com

## Citation
If you would like to cite our work or data, you may use the following bibtex citation:

```
@misc{durmus2023measuring,
title={Towards Measuring the Representation of Subjective Global Opinions in Language Models},
author={Esin Durmus and Karina Nyugen and Thomas I. Liao and Nicholas Schiefer and Amanda Askell and Anton Bakhtin and Carol Chen and Zac Hatfield-Dodds and Danny Hernandez and Nicholas Joseph and Liane Lovitt and Sam McCandlish and Orowa Sikder and Alex Tamkin and Janel Thamkul and Jared Kaplan and Jack Clark and Deep Ganguli},
year={2023},
eprint={2306.16388},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```

原始信息汇总

数据集概述

名称：GlobalOpinionQA

来源：数据集包含从World Values Survey和Pew Global Attitudes Survey中选取的关于全球问题和意见的调查问题子集。

目的：用于分析大型语言模型（LLMs）在复杂全球问题上的意见反映，以洞察AI系统在主观话题上的潜在偏见。

数据格式：CSV文件，包含以下列：

• question：调查问题的文本。
• selections：字典，键为国家名，值为该国家选择每个答案选项的受访者百分比列表。
• options：给定问题的答案选项列表。
• source：GAS/WVS，表示问题来源是Global Attitudes Survey还是World Value Survey。

许可证：cc-by-nc-sa-4.0

语言：英语

大小：1K<n<10K

引用：

@misc{durmus2023measuring, title={Towards Measuring the Representation of Subjective Global Opinions in Language Models}, author={Esin Durmus and Karina Nyugen and Thomas I. Liao and Nicholas Schiefer and Amanda Askell and Anton Bakhtin and Carol Chen and Zac Hatfield-Dodds and Danny Hernandez and Nicholas Joseph and Liane Lovitt and Sam McCandlish and Orowa Sikder and Alex Tamkin and Janel Thamkul and Jared Kaplan and Jack Clark and Deep Ganguli}, year={2023}, eprint={2306.16388}, archivePrefix={arXiv}, primaryClass={cs.CL} }