CLICKBAIT DETECTION USING MACHINE LEARNING AND DEEP LEARNING ALGORITHMS

Abstract

Clickbait is a type of providing false content, intentionally to gain a variety of users and get engagement and monetary benefits. It makes users curious to click the link and follow the content in various format like audio, video, text, images. As the online user base is getting bigger and bigger and more and more users are coming online, the unusual activities, scam and clickbait is becoming more common.These clickbait links will take users to some random websites which will have irrelevant information and completely exploits the user experience. The motive behind the clickbait links is to get more views to generate more ad revenue. Clickbait De- tection is a crucial and difficult task to be done. Many researchers have proposed various techniques using deep learning and machine learning techniques like Logistic Regression, Linear Support Vector Machine, Adaboost, Random Forest, Multilayer Perceptron, Convolution Neural Networks(CNN). To give the clear overview about the efficient algorithms, we went through some existing studies over the period of 2016-2022 which proposed various clickbait detection methods.