A Review: Fake News Detection using Hierarchical Attention Network and Hypergraph Attention

Abstract

This paper aims a survey of some of the detection of Fake News using a Deep Learning(DL) technique and classification based authenticity prediction techniques that to a large extent applied in several ways to news detection applications. Fake?True News Detection is currently a hard subject that is attracting investigation due to its detrimental effects on society. Deep Learning is employed in the crucial and often-used field of Fake News classification. Due to its excellent classification accuracy, the DL based approach has been widely used in the classification of news. Neural Network based – Generative Adversarial Networks (GAN), Long Short Term Memory (LSTM), Recurrent Neural Network (RNN), Hierarchical Attention Network (HAN), and Graph-based CNN (GCN) are some of the Deep Learning approaches that have been taken into consideration in our study and are used for developing a variety of News Detection methods. The study also includes comparative studies on a few news detection and classification methods that have been used to various Fake News prediction issues.