Interrupted time series analysis of clickbait on worldwide news websites, 2016-2023

Autor: McCutcheon, Austin, Brogly, Chris
Rok vydání: 2024
Předmět:
Druh dokumentu: Working Paper
Popis: 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.
Databáze: arXiv