Results 21 to 30 of about 283 (152)
Clickbait Detection in YouTube Videos
CoRR, 2021 YouTube videos often include captivating descriptions and intriguing thumbnails designed to increase the number of views, and thereby increase the revenue for the person who posted the video. This creates an incentive for people to post clickbait videos, in which the content might deviate significantly from the title, description, or thumbnail.
Ruchira Gothankar +2 more
openaire +2 more sources
Stop Clickbait: Detecting and preventing clickbaits in online news media [PDF]
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2016 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Abhijnan Chakraborty +3 more
openaire +4 more sources
BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Dataset
Proceedings of the Conference Recent Advances in Natural Language Processing - Large Language Models for Natural Language Processings, 2023 8 pages, 3 figures, 5 tables, published in Recent Advances in Natural Language Processing ...
Md. Motahar Mahtab +3 more
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Clickbait detection using multiple categorisation techniques [PDF]
Journal of Information Science, 2019 Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempt visitors to click on a particular link either to monetise the landing page or to spread the false news for sensationalisation.
Abinash Pujahari, Dilip Singh Sisodia
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Heuristic Feature Selection for Clickbait Detection
CoRR, 2018 We study feature selection as a means to optimize the baseline clickbait detector employed at the Clickbait Challenge 2017. The challenge's task is to score the "clickbaitiness" of a given Twitter tweet on a scale from 0 (no clickbait) to 1 (strong clickbait).
Matti Wiegmann +4 more
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Clickbait detection using word embeddings
CoRR, 2017 Clickbait is a pejorative term describing web content that is aimed at generating online advertising revenue, especially at the expense of quality or accuracy, relying on sensationalist headlines or eye-catching thumbnail pictures to attract click-throughs and to encourage forwarding of the material over online social networks.
Vijayasaradhi Indurthi, Subba Reddy Oota
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The Good, the Bad and the Bait: Detecting and Characterizing Clickbait on YouTube [PDF]
2018 IEEE Security and Privacy Workshops (SPW), 2018 The use of deceptive techniques in user-generated video portals is ubiquitous. Unscrupulous uploaders deliberately mislabel video descriptors aiming at increasing their views and subsequently their ad revenue. This problem, usually referred to as "clickbait," may severely undermine user experience.
Savvas Zannettou +3 more
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Findings of the Association for Computational Linguistics: EMNLP 2023, 2023 To increase revenue, news websites often resort to using deceptive news titles, luring users into clicking on the title and reading the full news. Clickbait detection is the task that aims to automatically detect this form of false advertisement and avoid wasting the precious time of online users.
Daria-Mihaela Broscoteanu +1 more
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Federated Hierarchical Hybrid Networks for Clickbait Detection
CoRR, 2019 Online media outlets adopt clickbait techniques to lure readers to click on articles in a bid to expand their reach and subsequently increase revenue through ad monetization. As the adverse effects of clickbait attract more and more attention, researchers have started to explore machine learning techniques to automatically detect clickbaits.
Feng Liao +3 more
openaire +3 more sources
Conniving With Continuations: Representing Goals in a Domain‐Specific Language of Thought
Topics in Cognitive Science, EarlyView.Abstract Wanting composes flexibly with knowing: we can want to know, want to know what someone wants, and so on. In this paper, we develop a goal representation that allows for this type of rich integration between goals and other theory‐of‐mind concepts.
Kartik Chandra +3 more
wiley +1 more source