A Comparative Study on Clickbait Detection using Machine Learning Based Methods

Abstract

Clickbait is a type of providing false content, intended to attract a variety of users and get engagement and monetary benefits. It makes users curious to click the link and follow the content in various formats like audio, video, text, and images. Clickbait detection is a critical and difficult task. Many researchers have proposed various techniques using deep learning techniques and machine learning techniques like Logistic Regres- sion, Linear Support Vector Machine, Adaboost, Multilayer Per- ceptron, Random Forest, Convolution Neural Networks(CNN), and Recurrent Convolutional Neural Networks (RCNN). To give a clear overview of the efficient algorithms, we went through some existing studies from 2016–2022, which proposed various clickbait detection methods. This review gives an exhaustive study of existing methods and also suggests some recommendations for further enhancements to be done by combining the various deep learning techniques and machine learning techniques.