Click me…! The influence of clickbait on user engagement in social media and the role of digital nudging. [PDF]
PLoS ONE, 2022 Clickbait to make people click on a linked article is commonly used on social media. We analyze the impact of clickbait on user interaction on Facebook in the form of liking, sharing and commenting. For this, we use a data set of more than 4,400 Facebook
Anna-Katharina Jung +4 more
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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 Most of the online news media outlets rely heavily on the revenues generated from the clicks made by their readers, and due to the presence of numerous such outlets, they need to compete with each other for reader attention.
Chakraborty, Abhijnan +3 more
core +2 more sources
Identifying Clickbait: A Multi-Strategy Approach Using Neural Networks [PDF]
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018 Online media outlets, in a bid to expand their reach and subsequently increase revenue through ad monetisation, have begun adopting clickbait techniques to lure readers to click on articles.
Anand Ankesh +5 more
core +2 more sources
EDISThis publication provides an overview of clickbait and its characteristics. The publication also discusses a few implications of clickbait use. Written by Nicole Patten, Ricky Telg, and Kevin Kent, and published by the UF/IFAS Department of Agricultural
Nicole Patten, Ricky Telg, Kevin Kent
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ViClickbait-2025: A comprehensive dataset for Vietnamese clickbait detectionMendeley Data [PDF]
Data in BriefViClickbait-2025 is a curated Vietnamese-language dataset developed to facilitate research on automatic clickbait detection. It comprises 3414 headline samples collected through web scraping from eight major Vietnamese online news platforms between 2023 ...
Dai Phuoc Nguyen +3 more
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CLICK-ID: A novel dataset for Indonesian clickbait headlines [PDF]
Data in Brief, 2020 News analysis is a popular task in Natural Language Processing (NLP). In particular, the problem of clickbait in news analysis has gained attention in recent years [1, 2].
Andika William, Yunita Sari
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Deep learning and sentence embeddings for detection of clickbait news from online content [PDF]
Scientific ReportsWith the rise of user-generated content, ensuring the authenticity and originality of online information has become increasingly challenging. Artificial intelligence (AI) and Natural Language Processing (NLP) play a crucial role in large-scale content ...
Amara Muqadas +5 more
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BaitBuster-Bangla: A comprehensive dataset for clickbait detection in Bangla with multi-feature and multi-modal analysis [PDF]
Data in BriefThis study presents a large multi-modal Bangla YouTube clickbait dataset consisting of 253,070 data points collected through an automated process using the YouTube API and Python web automation frameworks.
Abdullah Al Imran +2 more
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Towards better Hebrew clickbait detection: Insights from BERT and data augmentation. [PDF]
PLoS ONEClickbait headlines, designed to entice readers with sensationalized or misleading content, pose significant challenges in the digital landscape. They exploit curiosity to generate traffic and revenue, often at the cost of spreading misinformation and ...
Talya Natanya, Chaya Liebeskind
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Manipulative Means in Clickbait Headlines of Online Media [PDF]
Актуальные проблемы филологии и педагогической лингвистики, 2023 The paper deals with manipulative means in clickbait headlines of online media. The aim of the article is to distinguish and examine the used in implicit clickbaits manipulative means which help to cultivate the reader’s interest and make them pass to ...
Olga V. Loutovinova
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