newsmediabias/fake_news_elections_labelled_data

Dataset Card for Election-Related Fake News Classification

Dataset Summary

This dataset is designed for the task of fake news classification in the context of elections. It consists of news articles, social media posts, and other text sources related to various elections worldwide. Each entry in the dataset is labeled as 'fake' or 'real' based on its content and the veracity of the information presented.

https://arxiv.org/abs/2312.03750

Languages

English

Data Instances

A typical data instance comprises:

• Text: The content of the news article or post.
• Label: A binary label, where '0' indicates 'real' news and '1' indicates 'fake' news.

Example:

{
  "text": "The president announced a new policy today...",
  "label": REAL
}

Annotation process

Annotations were performed by using LLMs and which is verified by subject matter experts who checked each text as 'real' or 'fake' based on factual accuracy and context.

Social Impact of Dataset

This dataset plays a crucial role in combating the spread of misinformation during elections, which is vital for maintaining the integrity of democratic processes.

Discussion of Biases

There may be biases in the dataset due to the predominance of certain sources or the subjective nature of some news categorizations.

Citation

If you use this dataset in your research, please cite it as follows:

@article{rahman2023analyzing,
  title={Analyzing the Influence of Fake News in the 2024 Elections: A Comprehensive Dataset},
  author={Rahman, Mizanur and Raza, Shaina},
  journal={arXiv preprint arXiv:2312.03750},
  year={2023}
}