Fake News Detection Using Passive Aggressive Classifier (PAC) & Neural Network: A Hybrid Approach

In this digital age, the proliferation of fake news represents a significant challenge. Our research introduces a hybrid detection system that employs an optimized Passive Aggressive Classifier (PAC), fine-tuned through various parameters, alongside Artificial Neural Networks (ANN). This enhanced PAC is designed to identify and counteract misinformation on social media and anonymous websites. By analyzing articles verified by fact-checkers, the system accurately pinpoints linguistic signs of fake news, ensuring precise content classification. Our initiative supports informed public dialogue by providing immediate detection and rationale for content identified as potentially false. Trained on a comprehensive dataset that includes text, titles, and authorship, our robust framework adeptly evaluates the veracity of online articles. Through the application of advanced machine learning and natural language processing techniques, we tackle the rapid spread of false information, aiming to protect the digital information sphere and guarantee access to dependable and accurate news.