A Contemporary Survey of Machine Learning Techniques for Fake News Identification

Fake News is a grave problem in the society. The excessive reli-ance of people on internet for news is a huge motivation for spreading fake news on the internet and social media that creates a need for differentiat-ing it from the real. To fill this security void, various Machine Learning, Artificial Intelligence, Natural Language Processing and other related in-formation and technology tools are currently being researched to segregate one from another. In this paper, we establish fake news as a problem, study the classification of fake news into different types, methods of classifying news as fake or real with excessively studying ‘Style Based’ methods. We will also study about the machine learning and natural language features and metrics that are used in classification and see how machine learning can be applied to check this problem. Finally, we will be applying some of these methods on Indian news and find out how they perform.

Keywords: Fake News, Machine Learning, Artificial Intelligence

Suggested Citation: Suggested Citation

Meel, Priyanka and Mishra, Mohnish and Vishwakarma, Dr. Dinesh K., A Contemporary Survey of Machine Learning Techniques for Fake News Identification (June 2019). Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence (ICAEEC) 2019, Available at SSRN: https://ssrn.com/abstract=3575453 or http://dx.doi.org/10.2139/ssrn.3575453