  Online news media sometimes use misleading headlines to lure users to open
the news article. These catchy headlines that attract users but disappointed
them at the end, are called Clickbaits. Because of the importance of automatic
clickbait detection in online medias, lots of machine learning methods were
proposed and employed to find the clickbait headlines. In this research, a
model using deep learning methods is proposed to find the clickbaits in
Clickbait Challenge 2017's dataset. The proposed model gained the first rank in
the Clickbait Challenge 2017 in terms of Mean Squared Error. Also, data
analytics and visualization techniques are employed to explore and discover the
provided dataset to get more insight from the data.
