Clickbait Detection for YouTube Videos
Contribution to a Book
Advances in Information Security
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.
Ruchira Gothankar, Fabio Di Troia, and Mark Stamp. "Clickbait Detection for YouTube Videos" Advances in Information Security (2022): 261-284. https://doi.org/10.1007/978-3-030-97087-1_11