Fake News Detection Using BERT with Integration for Android

The exponential growth of social media platforms has made the dissemination of misinformation a major concern. This study presents a machine learning-based approach for fake news detection using a fine-tuned BERT (Bidirectional Encoder Representations from Transformers) model. My work focuses on optimizing BERT alone for textual fake news detection and deploying the model in an Android environment using Tensor Flow Lite (TFLite). The model achieves high accuracy in real-time inference, making it practical for mobile deployment. Experimental results show that BERT performs robustly on fake news datasets, providing a reliable classification of news articles as real or fake.