Fake News Detection in Social Media Using Deep Neural Networks

Abstract

            In the contemporary era, there has been increased usage of social networks through which news are spreading faster. They became virtual platforms for instant communications. Even governments and organizations are using social networks to convey intended news to people. It is good to have such media in order to improve communication across communities or people. However, there are some incidents where it is proved that fake news is spread by some people intentionally. Such news is created to damage impression of an organization or person or agency. This became a tool to damage products and services of opponents in case of businesses. Dissemination of fake news has its consequences and there is need for preventing it in social media. In literature there are many methods found to prevent spreading of fabricated news. However, in the wake of computation innovations and deeplearning methods, it is possible to improve the state of the art. Towards this end, in this paper, we proposed a framework for fake news detection using Convolutional Neural Network (CNN) which is one of the deep learning methods. A prototype application is built using Python data science platform to show the utility of the proposed system. The empirical results revealed that the proposed algorithm showed better performance over its predecessors.