Multimodal Fake News Detection Using Deep Learning Methods

Digital platforms have created such a strong presence of fake news that it became challenging to recognize what genuinely happened from fabricated content. A deep learning based multimodal fake news detection system examines news content through text and images according to this research. The model depends on LSTM networks together with a CNN network for processing text content and imaging information respectively. The system achieves better understanding of news articles through mutual strengths between textual and visual content analysis. The combination of different data types through this method leads to better detection accuracy according to our experimental results.