Fake News Detection System using NLP and Machine Learning

Information dissemination practices have significantly transformed in the digital age. The ability to instantly share and disseminate news has been facilitated by the advent of the internet, smartphones, and social networking sites. While such advancements have brought about numerous benefits to information dissemination practices, they have also introduced the phenomenon of fake news. Fake news is news content that is disseminated as genuine news while in actuality being misleading or outright false. It is typically used to influence people into having certain views on issues or situations or create misinformation among them. Fake news has become a huge menace across the world, especially concerning politics, healthcare, education, and social coexistence. Fake news can be spread faster than genuine news since it acts like an epidemic. The traditional approaches for detecting fake news, such as fact-checking manually, have not proven to be efficient due to the inability of humans to handle the massive volumes of data produced by digital platforms on a daily basis. As such, there is a need for more automation tools for detecting and filtering fake news efficiently and effectively. This project aims to address the above challenge by developing an automated system for detecting fake news through Natural Language Processing and Machine Learning.