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Clickbait Detection Using Bi-LSTM Model
2023 International Conference on Computational Intelligence for Information, Security and Communication Applications (CIISCA), 2023Kapil Kumar Yadav, Nipun Bansal
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Clickbait Spoiler Detection and Generation
Clickbait content typically uses sensationalized language to entice curiosity and stimulate user interaction, often at the expense of user satisfaction. In this paper, we introduce a spoiler generation system designed to neutralize clickbait by disclosing important information in a clear, informative format. Our system combines three primary components:openaire +1 more source
Boost Clickbait Detection Based on User Behavior Analysis
2017Article in the web is usually titled with a misleading title to attract the users click for gaining click-through rate (CTR). A clickbait title may increase click-through rate, but decrease user experience. Thus, it is important to identify the articles with a misleading title and block them for specific users.
Hai-Tao Zheng +4 more
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Clickbait Detection Using Long short-term memory
2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS), 2022Aromal A Balan, Anoop P, AS Mahesh
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Clickbait Headline Detection Using Supervised Learning Method
2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS), 2022null Vincent +3 more
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RGFN: Recurrent Graph Feature Network for ClickBait Detection
2021 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS), 2021Youwei Wang +4 more
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Indonesian Clickbait Detection Using Improved Backpropagation Neural Network
2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2021Bellatasya Unrica Nadia +1 more
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Detection of Clickbait Content Spreaders on Online Social Networks
2022 5th International Conference on Information and Computer Technologies (ICICT), 2022Smita Ghosh +3 more
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