Deep Learning Solution For Detecting Fake News

The proliferation of digital misinformation has evolved into a critical global challenge, undermining democratic processes and public trust. While Artificial Intelligence has accelerated information dissemination, it has also automated the creation of deceptive content. Current verification methods rely heavily on manual fact-checking, which is slow and unscalable. This paper presents Real Time Fake News Detection App, a unified deep-learning framework designed to detect fake news in real-time. By leveraging Natural Language Processing (NLP) transformers and multi-modal analysis, the proposed system bridges the gap between static datasets and real-world application. This review synthesizes the architectural development of the application, demonstrating how context-aware algorithms can streamline the verification process for end-users, reducing cognitive load and limiting the spread of disinformation.