persuasion

# Dataset Card for Persuasion Dataset

## Dataset Summary
The Persuasion Dataset contains claims and corresponding human-written and model-generated arguments, along with persuasiveness scores.
This dataset was created for research on measuring the persuasiveness of language models, as described in this blog post: [Measuring the Persuasiveness of Language Models](https://www.anthropic.com/news/measuring-model-persuasiveness).

## Dataset Description

The dataset consists of a CSV file with the following columns:
- **worker\_id**: Id of the participant who annotated their initial and final stance on the claim.
- **claim**: The claim for which the argument was generated.
- **argument**: The generated argument, either by a human or a language model.
- **source**: The source of the argument (model name or "Human").
- **prompt\_type**: The prompt type used to generate the argument.
- **rating\_initial**: The participant's initial rating of the claim.
- **rating\_final**: The participant's final rating of the claim after reading the argument.

## Usage
```python
from datasets import load_dataset
# Loading the data
dataset = load_dataset("Anthropic/persuasion")
```
## 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:

```
@online{durmus2024persuasion,
author = {Esin Durmus and Liane Lovitt and Alex Tamkin and Stuart Ritchie and Jack Clark and Deep Ganguli},
title = {Measuring the Persuasiveness of Language Models},
date = {2024-04-09},
year = {2024},
url = {https://www.anthropic.com/news/measuring-model-persuasiveness},
}

```

# 说服数据集（Persuasion Dataset）数据集卡片

## 数据集概览
说服数据集（Persuasion Dataset）收录了主张、对应人类撰写及大语言模型（Large Language Model，LLM）生成的论证文本，以及说服力评分。本数据集专为衡量大语言模型说服力的研究而构建，相关细节可参阅博文《衡量大语言模型的说服力（Measuring the Persuasiveness of Language Models）》，链接为：https://www.anthropic.com/news/measuring-model-persuasiveness。

## 数据集详情
本数据集以CSV文件形式存储，包含以下字段：
- **worker_id**：对目标主张标注初始与最终立场的参与者唯一标识编号。
- **claim**：用于生成论证的目标主张。
- **argument**：生成的论证文本，可由人类或大语言模型生成。
- **source**：论证文本的来源（模型名称或「Human」）。
- **prompt_type**：用于生成论证的提示词类型。
- **rating_initial**：参与者在阅读论证前对该主张的初始评分。
- **rating_final**：参与者在阅读论证后对该主张的最终评分。

## 使用方法
python
from datasets import load_dataset
# 加载数据集
dataset = load_dataset("Anthropic/persuasion")

## 联系方式
如有任何疑问，可发送邮件至[e-mail]。

## 引用格式
若需引用本研究或本数据集，可使用以下BibTeX条目：

@online{durmus2024persuasion,
author = {Esin Durmus and Liane Lovitt and Alex Tamkin and Stuart Ritchie and Jack Clark and Deep Ganguli},
title = {Measuring the Persuasiveness of Language Models},
date = {2024-04-09},
year = {2024},
url = {https://www.anthropic.com/news/measuring-model-persuasiveness},
}