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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

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Showing 1–10 of 31 papers

TitleStatusHype
Clickbait Identification using Neural Networks—0
Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?—0
Federated Hierarchical Hybrid Networks for Clickbait Detection—0
Clickbait Headline Detection in Indonesian News Sites using Multilingual Bidirectional Encoder Representations from Transformers (M-BERT)—0
Crowdsourcing a Large Corpus of Clickbait on Twitter—0
Clickbait Detection in YouTube Videos—0
Clickbait Detection using Multiple Categorization Techniques—0
Clickbait detection using word embeddings—0
Clickbait Detection with Style-aware Title Modeling and Co-attention—0
Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models—0
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