A Review on Fake News Identification in Online Social Networks

In the modern world, people's major source of information has changed to online news, as social media has expanded in popularity across all generations. It has also resulted in the dissemination of fake news. The proliferation of fake news is a growing threat to academics and businesses alike. The exponential growth of fake news has heightened the demand for automated fake news identification in recent years. Several approaches to fake news have yielded promising outcomes. On the other hand, these detection systems cannot explain why they made a prediction. The capacity to discover bias and discrimination in detection algorithms is a crucial benefit of explainability. This survey highlights recent advancements in the detection of explainable fake news. We discuss the shortcomings of existing fake news detection models based on explainable AI (XAI). A multimodal explanationable fake news detection model is also described in our paper.