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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 11–20 of 31 papers

TitleStatusHype
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
Clickbait Headline Detection in Indonesian News Sites using Multilingual Bidirectional Encoder Representations from Transformers (M-BERT)—0
Clickbait Identification using Neural Networks—0
Crowdsourcing a Large Corpus of Clickbait on Twitter—0
Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?—0
Fishing for Clickbaits in Social Images and Texts with Linguistically-Infused Neural Network Models—0
From Clickbait to Fake News Detection: An Approach based on Detecting the Stance of Headlines to Articles—0
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