Fake news detection in a social network is a growing research area attracting huge awareness. Fake news detection is the process of detecting forms of news containing intention or unintentional misinformation spreading in social media. Deep learning models are the widely used data-driven automatic fake news detection method. Deep learning models do not require pre-processing and feature engineering processes, which are considered advantages over machine learning models.
A novel deep learning approach to improve the detection rate for fake news detection is the hybrid deep learning model. Hybrid deep learning models concatenate several deep learning models to boost the performance of fake news detection. Hybrid deep learning model based fake news detection in social networks improves the state-of-the-art with high accuracy compared to other approaches.