AMFB: Attention based multimodal Factorized Bilinear Pooling for multimodal Fake News Detection

Fake news is the information or stories that are intentionally created to deceive or mislead the readers. In recent times, Fake news detection has attracted the attention of researchers and practitioners due to its many-fold benefits, including bringing in preventive measures to tackle the dissemination of misinformation that could otherwise disturb the social fabrics. Social media in recent times are heavily loaded with multimedia news and information. People prefer online news reading and find it more informative and convenient if they have access to multimedia content in the forms of text, images, audio, and videos. In early studies, researchers have proposed several fake news detection mechanisms that mostly utilize the textual features and not proper to learn multimodal (textual + visual) shared representation.