Fake News Detection Using MultiChannel Deep Neural Networks

Meenakshi A. Thalor, Mayuri Garad
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Abstract

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.
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利用多通道深度神经网络检测假新闻
假新闻已成为当今数字时代的一个普遍问题,给信息的完整性和可信度带来了巨大挑战。在本研究中,我们提出了一种利用多通道深度神经网络(MC-DNN)检测假新闻的新方法。我们的研究旨在利用深度学习和多数据源的力量,解决传统假新闻检测方法的局限性。
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