rangeva/Webz.io_News_Dataset_Repository

---
task_categories:
- text-classification
pretty_name: Webz.io News Dataset Repository
size_categories:
- 100M<n<1B
---
# Webz.io News Dataset Repository

[https://github.com/Webhose/free-news-datasets](https://github.com/Webhose/free-news-datasets)

## Introduction

Welcome to the [Webz.io](https://webz.io) News Dataset Repository! This repository is created by [Webz.io](https://webz.io) and is dedicated to providing free datasets of publicly available news articles. We release new datasets weekly, each containing around 1,000 news articles focused on various themes, topics, or metadata characteristics like sentiment analysis, and top IPTC categories such as finance, sports, and politics.

## Dataset Overview

- **Weekly Releases:** New dataset available every week.
- **Thematic Focus:** Datasets based on specific themes, topics, or metadata.
- **Rich Metadata:** Includes sentiment analysis, categories, publication dates.
- **Diverse Sources:** Articles from a wide range of news websites.

## Usage

The datasets are free for academic, research, and journalistic purposes:

- **Data Analysis:** For statistical analyses, trend identification, and pattern recognition.
- **Machine Learning:** Suitable for training NLP models, sentiment analysis, etc.
- **Journalistic Research:** Helps journalists in data-driven storytelling.

## Accessing the Datasets

- Browse the repository.
- Find a dataset that suits your needs.
- Download the dataset with its detailed description and metadata file.

## Contribution

Contributions are welcome! If you have suggestions or want to contribute, please open an issue or a pull request.

## Support

For questions or support, raise an issue in the repository.

---

原始信息汇总

Webz.io News Dataset Repository

数据集概述

• 定期更新： 每周发布新的数据集。
• 主题聚焦： 数据集基于特定的主题、话题或元数据。
• 丰富的元数据： 包括情感分析、分类、发布日期等。
• 多样化的来源： 文章来自广泛的新闻网址。

使用场景

数据集可用于学术、研究和新闻报道目的：

• 数据分析： 用于统计分析、趋势识别和模式识别。
• 机器学习： 适用于训练自然语言处理模型、情感分析等。
• 新闻研究： 帮助记者进行数据驱动的报道。

访问数据集

• 浏览仓库。
• 找到适合需求的数据集。
• 下载数据集及其详细的描述和元数据文件。

贡献

欢迎贡献！如果有建议或想贡献，请提交问题或拉取请求。

支持

如有问题或需要支持，请在仓库中提出问题。