Fake News Detection using Machine Learning and Natural Language Processing
Kushal Agarwalla1, Shubham Nandan2, Varun Anil Nair3, D. Deva Hema4
1Kushal Agarwalla, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, (Tamil Nadu), India.
2Shubham Nandan, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, (Tamil Nadu), India.
3Varun Anil Nair, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, (Tamil Nadu), India.
4D. Deva Hema, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, (Tamil Nadu), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 844-847 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2457037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The web and internet-based life have led the entrance to news data, a lot less demanding and agreeable. Mass-media affects the life of the general public and as it frequently occurs. There are few individuals that exploit these privileges. This prompts the creation of the news articles that are not totally evident or indeed, even totally false. People intentionally spread these counterfeit articles with the help of web-based social networking sites. The fundamental objective of fake news sites is to influence the popular belief on specific issues. The main goal of fake news websites is to affect public opinion on certain matters. Our aim is to find a reliable and accurate model that classifies a given news article as either fake or true
Keywords: Classification algorithm , Fake news detection, Machine learning, Natural language processing.
Scope of the Article: Classification