Clickbait Detection via Large Language Models
Clickbait, which aims to induce users with some surprising and even thrilling headlines for increasing click-through rates, permeates almost all online content publishers, such as news portals and social media. Recently, Large Language Models (LLMs) have emerged as a powerful instrument and achieved tremendous success in a series of NLP downstream ...
Wang, Han +5 more
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Towards reliable online clickbait video detection: A content-agnostic approach
Knowledge-Based Systems, 2019 Online video sharing platforms (e.g., YouTube, Vimeo) have become an increasingly popular paradigm for people to consume video contents. Clickbait video, whose content clearly deviates from its title/thumbnail, has emerged as a critical problem on online video sharing platforms.
Shang, Lanyu +4 more
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Prompt-Tuning for Clickbait Detection via Text Summarization
Clickbaits are surprising social posts or deceptive news headlines that attempt to lure users for more clicks, which have posted at unprecedented rates for more profit or commercial revenue. The spread of clickbait has significant negative impacts on the users, which brings users misleading or even click-jacking attacks.
Deng, Haoxiang +6 more
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What Makes You CLIC: Detection of Croatian Clickbait Headliness
Proceedings of the 10th Workshop on Slavic Natural Language Processing (Slavic NLP 2025)Accepted at Slavic NLP ...
Anđelić, Marija +3 more
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Detecting Clickbait: Here’s How to Do It [PDF]
, 2018 Automatic clickbait detection is a relatively novel task in natural language processing (NLP) and machine learning (ML). “Clickbait” is a hyperlink created primarily to attract attention to its target content. This article introduces a binary classifier, the Language and Information Technology Research Lab (LiT.RL, pronounced “literal”) Clickbait ...
Brogly, Christopher, Rubin, Victoria
openaire
A review on fake news detection 3T's: typology, time of detection, taxonomies. [PDF]
Int J Inf Secur, 2023 Rastogi S, Bansal D.
europepmc +1 more source
Click me…! The influence of clickbait on user engagement in social media and the role of digital nudging. [PDF]
PLoS One, 2022 Jung AK +4 more
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Did clickbait crack the code on virality? [PDF]
J Acad Mark Sci, 2022 Mukherjee P, Dutta S, De Bruyn A.
europepmc +1 more source
TA-BiLSTM: An Interpretable Topic-Aware Model for Misleading Information Detection in Mobile Social Networks. [PDF]
Mob Netw Appl, 2021 Chang S, Wang R, Huang H, Luo J.
europepmc +1 more source
A unified approach for detection of Clickbait videos on YouTube using cognitive evidences. [PDF]
Appl Intell (Dordr), 2021 Varshney D, Vishwakarma DK.
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