Results 111 to 120 of about 2,206 (147)

Enhanced Clickbait Detection through Ensemble Machine Learning Techniques

open access: yesProcedia Computer Science
Neetu Sardana   +2 more
openaire   +1 more source

LSTMCNN: A hybrid machine learning model to unmask fake news. [PDF]

open access: yesHeliyon
Dev DG   +4 more
europepmc   +1 more source

Clickbait detection in Hebrew

Lodz Papers in Pragmatics, 2023
Abstract The prevalence of sensationalized headlines and deceptive narratives in online content has prompted the need for effective clickbait detection methods. This study delves into the nuances of clickbait in Hebrew, scrutinizing diverse features such as linguistic and structural features, and exploring various types of clickbait in ...
Talya Natanya, Chaya Liebeskind
openaire   +1 more source

Clickbait Detection

Proceedings of the 7th International Conference on Software and Information Engineering, 2018
Clickbait is a term that describes deceiving web content that uses ambiguity to provoke the user into clicking a link. It aims to increase the number of online readers in order to generate more advertising revenue. Clickbaits are heavily present on social media platforms wasting the time of users.
Suhaib R. Khater   +3 more
openaire   +1 more source

CA-CD: context-aware clickbait detection using new Chinese clickbait dataset with transfer learning method

Data Technologies and Applications, 2023
PurposeA clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals.
Hei-Chia Wang   +2 more
openaire   +1 more source

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