Results 121 to 130 of about 283 (152)
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Clickbait Detection Based on Word Embedding Models
2018In recent years, social networking platform serves as a new media of news sharing and information diffusion. Social networking platform has become a part of our daily life. As such, social media advertising budgets have explosively expanded worldwide over the past few years. Due to the huge commercial interest, clickbait behaviors are commonly observed,
Vorakit Vorakitphan +2 more
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Detecting Clickbait on Online News Sites
2019The aim of this study is to detect misleading news headlines and social media posts prepared to manipulate readers. The rapid expansion of digitalization has accelerated the transition from written news sources to the digital world. Previously printed newspapers and magazines were moved to the virtual environment, each with their own social media ...
Ayşe Geçkil +3 more
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Clickbait Detection Using Swarm Intelligence
2019Clickbaits are the articles containing catchy headlines which lure the reader to explore full content, but do not have any useful information. Detecting clickbaits solely by the headline without opening the link, can serve as a utility for users over internet. This can prevent their time from useless surfing caused by exploring clickbaits.
Deepanshu Pandey +2 more
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Clickbait detection using deep learning
2016 2nd International Conference on Next Generation Computing Technologies (NGCT), 2016Clickbaits, in social media, are exaggerated headlines whose main motive is to mislead the reader to “click” on them. They create a nuisance in the online experience by creating a lure towards poor content. Online content creators are utilizing more of them to get increased page views and thereby more ad revenue without providing the backing content ...
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Detecting Clickbaits Using Deep Forest
2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP), 2022Vlad Cofaru, Adrian Groza
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Clickbait Detection via Prompt-Tuning With Titles Only
IEEE Transactions on Emerging Topics in Computational IntelligenceJipeng Qiang, Xindong Wu, Yi Zhu
exaly +3 more sources
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 0002 +4 more
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A deep model based on Lure and Similarity for Adaptive Clickbait Detection
Knowledge-Based Systems, 2021Ke Yu, Xiaofei Wu
exaly