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Political News Veracity Dataset
Fraud Detection & Risk Management
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Free
About
This dataset is designed for the purpose of fake news detection, a subtask of text classification. It allows for the analysis of news content to determine its truthfulness, aiming to classify news articles as either real or fake. This is significant for identifying misinformation and aiding in the study of media veracity.
Columns
- title: The headline or title of the news article.
- text: The full textual content of the news article.
- subject: The category or subject area to which the news article belongs.
- date: The publication date of the news article.
Distribution
The dataset is typically provided in a CSV file format. Specific numbers for rows or records are not available from the provided information. It is structured as tabular data.
Usage
This dataset is ideally suited for applications and use cases involving text classification, natural language processing (NLP), and binary classification tasks. It can be used to develop models for fake news detection, and is also relevant for fraud detection and risk management scenarios where the authenticity of textual information is critical.
Coverage
The dataset has a global geographic coverage, with news content reflecting a worldwide scope. The articles provided as samples mainly originate from December 2017, suggesting the dataset primarily covers this period. Demographic scope is not explicitly detailed but relates to general news and political commentary.
License
CC-BY-NC
Who Can Use It
This dataset is intended for use by researchers, data scientists, and machine learning developers who are interested in building and evaluating models for text classification, specifically for the task of identifying fake news. It can support academic research, AI/ML development, and practical applications in media analysis.
Dataset Name Suggestions
- Fake News Detection
- News Authenticity Dataset
- Political News Veracity
- Misinformation Identification
- Truth in Reporting
Attributes
Original Data Source: Fake News Detection
QUALITY