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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 110 of 31 papers

TitleStatusHype
Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inference0
Prompt-tuning for Clickbait Detection via Text Summarization0
BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait DatasetCode0
BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal AnalysisCode0
A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News ArticlesCode0
Clickbait Detection via Large Language ModelsCode0
Know Better – A Clickbait Resolving Challenge0
Clickbait Detection in YouTube Videos0
Clickbait Headline Detection in Indonesian News Sites using Multilingual Bidirectional Encoder Representations from Transformers (M-BERT)0
Clickbait Detection with Style-aware Title Modeling and Co-attention0
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