argilla/news-summary

---
language:
- en
license:
- cc-by-nc-4.0
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
task_ids:
- news-articles-summarization
dataset_info:
features:
- name: text
dtype: string
- name: prediction
list:
- name: score
dtype: float64
- name: text
dtype: string
- name: prediction_agent
dtype: string
- name: annotation
dtype: 'null'
- name: annotation_agent
dtype: 'null'
- name: id
dtype: string
- name: metadata
dtype: 'null'
- name: status
dtype: string
- name: event_timestamp
dtype: timestamp[us]
- name: metrics
struct:
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 2563132.0446374374
num_examples: 1000
- name: test
num_bytes: 52331466.955362566
num_examples: 20417
download_size: 33207109
dataset_size: 54894599.0
---
# Dataset Card for "news-summary"

## Dataset Description

- **Homepage:** Kaggle Challenge
- **Repository:** https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset?select=True.csv
- **Paper:** N.A.
- **Leaderboard:** N.A.
- **Point of Contact:** N.A.

### Dataset Summary

Officially it was supposed to be used for classification but, can you use this data set to summarize news articles?

### Languages

english

### Citation Information

Acknowledgements

Ahmed H, Traore I, Saad S. “Detecting opinion spams and fake news using text classification”, Journal of Security and Privacy, Volume 1, Issue 1, Wiley, January/February 2018.
Ahmed H, Traore I, Saad S. (2017) “Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques. In: Traore I., Woungang I., Awad A. (eds) Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environments. ISDDC 2017. Lecture Notes in Computer Science, vol 10618. Springer, Cham (pp. 127-138).

### Contributions

Thanks to [@davidberenstein1957](https://github.com/davidberenstein1957) for adding this dataset.

原始信息汇总

数据集概述

基本信息

• 语言: 英语
• 许可证: CC-BY-NC-4.0
• 大小: 10K<n<100K
• 数据源: 原始数据
• 任务类别: 摘要生成
• 任务ID: news-articles-summarization

数据集特征

• text: 字符串类型
• prediction: 列表类型，包含
  • score: 浮点数类型
  • text: 字符串类型
• prediction_agent: 字符串类型
• annotation: 空值类型
• annotation_agent: 空值类型
• id: 字符串类型
• metadata: 空值类型
• status: 字符串类型
• event_timestamp: 时间戳类型
• metrics: 结构类型，包含
  • text_length: 整数类型

数据集拆分

• 训练集:
  • 大小: 2563132.0446374374字节
  • 样本数: 1000
• 测试集:
  • 大小: 52331466.955362566字节
  • 样本数: 20417

下载与数据集大小

• 下载大小: 33207109字节
• 数据集大小: 54894599.0字节