Presented at the IEEE/ACM International Conference , this paper focuses on the . The authors developed a machine-learning classifier to automatically detect clickbait. They identified key features that signal a headline is likely bait, such as specific parts of speech (superlatives, intensifiers) and patterns like "X Reasons Why...". 4. "Did clickbait crack the code on virality?" (2022)
3. (2016/2019)
This paper by Kate Scott uses to explain why we click. It argues that clickbait exploits our natural tendency to seek out information that promises a high reward for low cognitive effort. The author highlights how "information gaps" create a sense of urgency that compels readers to click just to resolve their curiosity. 2. "Does Clickbait Actually Attract More Clicks?" (2021) Clickbait