Results 1 to 10 of about 1,638 (207)
Clickbait Convolutional Neural Network [PDF]
Symmetry, 2018 With the development of online advertisements, clickbait spread wider and wider. Clickbait dissatisfies users because the article content does not match their expectation. Thus, clickbait detection has attracted more and more attention recently. Traditional clickbait-detection methods rely on heavy feature engineering and fail to distinguish clickbait ...
Hai-Tao Zheng +2 more
exaly +3 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
doaj +7 more sources
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
doaj +2 more sources
Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection
IEEE Access, 2022 When people use social networks, they often fall prey to a clickbait scam. The scammer attempts to create a striking headline that attracts the majority of users and attaches a link.
Abdul Razaque +2 more
exaly +3 more sources
Automatic Detection of Clickbait Headlines Using Semantic Analysis and Machine Learning Techniques
Applied Sciences (Switzerland), 2023 Clickbait headlines are misleading headiness designed to attract attention and entice users to click on the link. Links can host malware, trojans and phishing attacks. Clickbaiting is one of the more subtle methods used by hackers and scammers. For these
Ali Al Bataineh
exaly +3 more sources
Applied Sciences (Switzerland), 2021 The widespread usage of social media has led to the increasing popularity of online advertisements, which have been accompanied by a disturbing spread of clickbait headlines.
Mohammed Al-Sarem +2 more
exaly +3 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources