Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.06376 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- Clickbait is deceptive text that can manipulate web browsing, creating an information gap between a link and target page that literally baits a user into clicking. Clickbait detection continues to be well studied, but analyses of clickbait overall on the web are limited. A dataset was built consisting of 451,033,388 clickbait scores produced by a clickbait detector which analyzed links and headings on primarily English news pages from the Common Crawl. On this data, 5 segmented regression models were fit on 5 major news events and averaged clickbait scores. COVID and the 2020 US Election appeared to influence clickbait levels.