Results 71 to 80 of about 387 (173)
KazFakeCorpus: A Bilingual Corpus with Multi-Level Semantic Annotation for Fake News Detection
Big Data and Cognitive ComputingThis paper addresses the lack of bilingual annotated resources for automatic fake news detection in the Kazakh–Russian media space, as well as the limitations of binary annotation, which does not always allow disinformation to be represented as a complex
Zhanar Lamasheva +5 more
doaj +1 more source
Detecting "Clickbait" News on Social Media Using Machine Learning Algorithms
, 2019 Clickbait, which has become very common in social media in recent years, is a technique which uses exaggerated and unreal headlines in order to manipulate people and attract them to their websites.
Genc, Sura, Sürer, Elif
core +1 more source
Deteksi Clickbait Dengan Sentence Scoring Based on Frequency Di Detik.Com
, 2020 - The clickbait phenomenon has become one of the powerful ways to increase the number of readers for a website. With the increasing number of visitors to the site, the higher the income on the website.
Raharjo, S. (Suwanto) +2 more
core +1 more source
INTRODUCTION. LETTERS IN THE WEB OF LIFE: TOWARDS AN ECOLOGICAL PHILOLOGY
German Life and Letters, Volume 78, Issue 3, Page 277-288, July 2025.
Conor Brennan, Caitríona Ní Dhúill
wiley +1 more source
Flagging clickbait in Indonesian online news websites using fine-tuned transformers
, 2023 Click counts are related to the amount of money that online advertisers paid to news sites. Such business models forced some news sites to employ a dirty trick of click-baiting, i.e., using hyperbolic and interesting words, sometimes unfinished sentences
Jannah, Sa'idah Zahrotul +7 more
core +1 more source
Clickbait Detection via Large Language Models
Clickbait, which aims to induce users with some surprising and even thrilling headlines for increasing click-through rates, permeates almost all online content publishers, such as news portals and social media. Recently, Large Language Models (LLMs) have emerged as a powerful instrument and achieved tremendous success in a series of NLP downstream ...
Yi Zhu 0006 +5 more
openaire +2 more sources
The Effect of Monetary Incentives on Health Care Social Media Content: Study Based on Topic Modeling and Sentiment Analysis. [PDF]
J Med Internet Res, 2023 Maleki N, Padmanabhan B, Dutta K.
europepmc +1 more source
Clickbait detection in social media
, 2018 Θέμα αυτής της Εργασίας είναι η αναγνώριση των Μηνυμάτων Δολωμάτων στα Κοινωνικά Δίκτυα, ένα φαινόμενο που κατακλύζει ολοένα και περισσότερο τα τελευταία.
Στρογγύλης, Σταμάτιος
core
Detecting Clickbait: Here’s How to Do It [PDF]
, 2018 Automatic clickbait detection is a relatively novel task in natural language processing (NLP) and machine learning (ML). “Clickbait” is a hyperlink created primarily to attract attention to its target content. This article introduces a binary classifier, the Language and Information Technology Research Lab (LiT.RL, pronounced “literal”) Clickbait ...
Brogly, Christopher, Rubin, Victoria
openaire
ClickGuard: A Trustworthy Adaptive Fusion Framework for Clickbait Detection
CoRRThe widespread use of clickbait headlines, crafted to mislead and maximize engagement, poses a significant challenge to online credibility. These headlines employ sensationalism, misleading claims, and vague language, underscoring the need for effective detection to ensure trustworthy digital content.
Chhavi Dhiman +4 more
openaire +2 more sources