---
language:
- en
license: mit
size_categories:
- 10K<n<100K
task_categories:
- text-classification
- question-answering
- text-generation
dataset_info:
  features:
  - name: label
    dtype:
      class_label:
        names:
          '0': 'true'
          '1': fake
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 82978144
    num_examples: 33672
  - name: test
    num_bytes: 28512596
    num_examples: 11224
  download_size: 67949019
  dataset_size: 111490740
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
tags:
- news
---

# True-Fake-News

<!-- Provide a quick summary of the dataset. -->

These are collected news articles from various sources with curated labels aligning to `true` of `fake` classification.


### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

The dataset contains two types of articles fake and real News. This dataset was collected from realworld sources; the truthful articles were obtained by crawling articles from Reuters.com (News website). As for the fake news articles, they were collected from different sources. The fake news articles were collected from unreliable websites that were flagged by Politifact (a fact-checking organization in the USA) and Wikipedia. The dataset contains different types of articles on different topics, however, the majority of articles focus on political and World news topics.

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [Kaggle Repo](https://www.kaggle.com/datasets/emineyetm/fake-news-detection-datasets/data)


## Uses

<!-- Address questions around how the dataset is intended to be used. -->

Text classification or question answering would be ways to use this dataset.

## Dataset Structure

| Classification | Total Number of Articles | Article Type | Article Count |
|----------------|--------------------------|--------------|---------------|
| Real-News      | 21,417                   | World        | 10,145        |
|                |                          | Political    | 11,272        |
| Fake-News      | 23,481                   | Government   | 1,570         |
|                |                          | Middle East  | 778           |
|                |                          | US           | 783           |
|                |                          | Left-Leaning | 4,459         |
|                |                          | Political    | 6,841         |
|                |                          | General      | 9,050         |