Is it a click bait? Let's predict using Machine Learning

Abstract

In this era of digitisation, news reader tend to read news online. This is because, online media instantly provides access to a wide variety of content. Thus, people don't have to wait for tomorrow's newspaper to know what's happening today. Along with these virtues, online news have some vices as well. One such vice is presence of social media posts (tweets) relating to news articles whose sole purpose is to draw attention of the users rather than directing them to read the actual content. Such posts are referred to as clickbaits. The objective of this project is to develop a system which would be capable of predicting how likely are the social media posts (tweets) relating to new articles tend to be clickbait.

M.Tech Thesis defended at BITS, Pilani

References in corpus (6)

• Convolutional Neural Network Architectures for Matching Natural Language Sentences
• Clickbait Detection in Tweets Using Self-attentive Network
• Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models
• A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based Features
• Clickbait Identification using Neural Networks
• Identifying Clickbait Posts on Social Media with an Ensemble of Linear Models