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
These are collected news articles from various sources with curated labels aligning to true of fake classification.
Dataset Description
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]
- Repository: Kaggle Repo
Uses
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 |