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 ...
Hikmat Ullah Khan +2 more
exaly +3 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
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
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
Game Theoretic Analysis of Ideologically Biased Clickbait or Fake News, and Real News
Operations Research and Decisions, 2020 A decision and game theoretic model is developed for how one and two news organisations strike balances between producing clickbait or fake news, and real news. Each news organisation seeks to attract gullible consumers who consume more clickbait or fake
Kjell Hausken
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
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
Effect of visual imagery in COVID-19 social media posts on users’ perception [PDF]
PeerJ Computer Science, 2022 People receive a wide variety of news from social media. They especially look for information on social media in times of crisis with the desire to assess the risk they face.
Waleed M. Al-nuwaiser
doaj +3 more sources
Impact of YouTube User-Generated Content on News Dissemination and Youth Information Reception. [PDF]
Health ExpectABSTRACT Background User‐generated content (UGC) on YouTube has reshaped news dissemination, fostered engagement, raised concerns about credibility, algorithmic influence and the spread of misinformation. This study addresses the gap in understanding how UGC engagement, trust and algorithmic awareness influence digital news consumption.
Chunqiong W +3 more
europepmc +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