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
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
Clickbait Detection Using Deep Recurrent Neural Network [PDF]
Applied Sciences, 2022 People who use social networks often fall prey to clickbait, which is commonly exploited by scammers. The scammer attempts to create a striking headline that attracts the majority of users to click an attached link.
Abdul Razaque +5 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
Leverage knowledge graph and GCN for fine-grained-level clickbait detection. [PDF]
World Wide Web, 2022 Clickbait is the use of an enticing title as bait to deceive users to click. However, the corresponding content is often disappointing, infuriating or even deceitful. This practice has brought serious damage to our social trust, especially to online media, which is one of the most important channels for information acquisition in our daily life ...
Zhou M, Xu W, Zhang W, Jiang Q.
europepmc +4 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
Clickbait Detection in Indonesia Headline News Using IndoBERT and RoBERTa
Jurnal Riset Informatika, 2023 This paper explores clickbait detection using Transformer models, specifically IndoBERT and RoBERTa. The objective is to leverage the models specifically for clickbait detection accuracy by employing balancing and augmentation techniques on the dataset ...
Muhammad Edo Syahputra +2 more
doaj +2 more sources
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
doaj +2 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
Clickbait detection in news headlines using RoBERTa-Large language model and deep embeddings [PDF]
Scientific ReportsThe integration of Large Language Models with Artificial Intelligence is transforming digital news analysis, particularly through progressions in natural language processing.
Fawaz Khaled Alarfaj +3 more
doaj +2 more sources