Fake News Detection Using MultiChannel Deep Neural Networks

Fake news has become a pervasive issue in today's digital age, posing significant challenges to information integrity and trustworthiness. In this study, we propose a novel approach for the detection of fake news using MultiChannel Deep Neural Networks (MC-DNNs). Our research aims to address the limitations of traditional fake news detection methods by leveraging the power of deep learning and multiple data sources.