TruthGuard is an innovative solution designed to tackle the challenge of misinformation in the digital age. Utilizing advanced machine learning algorithms, TruthGuard evaluates the authenticity of articles, helping users distinguish between genuine and fake news. This project aims to contribute to the integrity of information on the internet by providing a tool for verifying the reliability of content.
- Article Verification: Analyze articles to determine their authenticity.
- Machine Learning Integration: Leverages various ML algorithms to assess content credibility.
- User-Friendly Interface: Easy-to-use interface for submitting articles for verification.
TruthGuard uses a combination of machine learning algorithms, including Decision Trees and Logistic Regression to analyze the text of articles. The system examines various features such as the writing style, source credibility, and content analysis to assess the likelihood of an article being genuine or fake.
- Python 3.x
- Dependencies: scikit-learn, numpy, pandas, and PyTorch.
- Clone the repository:
git clone https://github.com/kaaliharsh/TruthGuard
- Install the required dependencies:
pip install -r requirements.txt
Provide instructions on how to use the application, including any necessary commands or scripts to run the analysis.
We welcome contributions to the TruthGuard project. If you're interested in contributing, please read our contributing guidelines located in the CONTRIBUTING.md file.
For any queries or further information, please contact us at harshdeepgupta2002@gmail.com.