ALIKAH- A Clickbait and Fake News Detection System using Natural Language Processing

Abstract

Nowadays, social media is a very important thing in our daily lives. People can't even think about a second without social media. Because of their busy life, people depend more on social media for information, thus increasing its popularity. Social media can be considered as a two-sided coin having its own advantage and disadvantage. These media help people to connect with their family or friends around the world. But the other side of the social media has many disadvantages. It can be considered as the cause of many problems in our society. One such major issue is the fake news. People were unable to distinguish the true and fake news and also about the credibility of the news and the news provider. They blindly believe the news without knowing the truth and they share the news with others. As a result, the fake news spread faster than the true news. By this, many people and organizations get affected. So, in a world of increasing fake news, a fake news detection system is an essential thing. This project deals with fake news. The system is a Webapp named ALIKAH- a clickbait and fake news detection system. It is just like social media network where the news providers can provide the news. This system distinguishes the fake and true news among the news provided in the Alikah system. There are three modules in this system-the admin, news providers and the users. Admin manages and monitors the system and its functionalities. News providers can provide the news to this system after getting permission from the admin and the user can view, like, comment, report and subscribe to the news and the news provider. Neural network is used as the classifier. This system detects the fake news by checking the credibility of the news provider, monitoring the comments and also by checking the relation of the heading and content of the news provided. It also helps to detect the fake news spreading on other social media like Facebook, by using its heading and content. This system definitely will be a beneficiary to the people and organizations which get affected by the news and also help to find the providers of these news.