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Clickbait Detection

Clickbait detection is the task of identifying clickbait, a form of false advertisement, that uses hyperlink text or a thumbnail link that is designed to attract attention and to entice users to follow that link and read, view, or listen to the linked piece of online content, with a defining characteristic of being deceptive, typically sensationalized or misleading (Source: Adapted from Wikipedia)

Papers

Showing 2130 of 31 papers

TitleStatusHype
Heuristic Feature Selection for Clickbait Detection0
Identifying Clickbait: A Multi-Strategy Approach Using Neural Networks0
A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News ArticlesCode0
A Two-Level Classification Approach for Detecting Clickbait Posts using Text-Based FeaturesCode0
BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal AnalysisCode0
BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait DatasetCode0
Clickbait Detection in Tweets Using Self-attentive NetworkCode0
Using Neural Network for Identifying Clickbaits in Online News MediaCode0
We Built a Fake News / Click Bait Filter: What Happened Next Will Blow Your Mind!Code0
We used Neural Networks to Detect Clickbaits: You won't believe what happened Next!Code0
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