Clickbait Detection in YouTube Videos
This addresses the issue of users being tricked by misleading content on YouTube, but it appears incremental as it applies existing methods without novel breakthroughs.
The research tackled the problem of detecting clickbait in YouTube videos by experimenting with multiple state-of-the-art machine learning techniques and textual features, but no concrete results or numbers were reported.
YouTube videos often include captivating descriptions and intriguing thumbnails designed to increase the number of views, and thereby increase the revenue for the person who posted the video. This creates an incentive for people to post clickbait videos, in which the content might deviate significantly from the title, description, or thumbnail. In effect, users are tricked into clicking on clickbait videos. In this research, we consider the challenging problem of detecting clickbait YouTube videos. We experiment with multiple state-of-the-art machine learning techniques using a variety of textual features.