Using Neural Network to Detect Clickbait

Online news media sometimes use misleading headlines to lure users into opening the
news articles. These catchy headlines that attract users but disappoint at the end, are called
clickbaits. Most of the time, they look far more interesting than the real article in order to
entice clicks from the readers or motivate them to subscribe. Online news media rely on
revenue generated by users clicking on their articles. Due to the importance of automatic
clickbait detection on social media, many machine learning methods have been proposed
and employed to find clickbait headlines. In machine learning and other related fields,
there have been extensive studies on identifying bad quality content on the web such as
spam and fake web pages. However, clickbaits are not necessarily spam or fake pages,
but they can be genuine pages delivering low-quality content with exaggerated titles. We
propose to use neural network to detect clickbaity links and warn the user to avoid those
pages.