Preserving integrity in online social networks

A Halevy, C Canton-Ferrer, H Ma, U Ozertem… - Communications of the …, 2022 - dl.acm.org
Preserving integrity in online social networks Page 1 92 COMMUNICATIONS OF THE ACM |
FEBRUARY 2022 | VOL. 65 | NO. 2 review articles THE GOAL OF online social networks is to …

A unified approach for detection of Clickbait videos on YouTube using cognitive evidences

D Varshney, DK Vishwakarma - Applied Intelligence, 2021 - Springer
Clickbait is one of the form of false content, purposely designed to attract the user's attention
and make them curious to follow the link and read, view, or listen to the attached content …

Did clickbait crack the code on virality?

P Mukherjee, S Dutta, A De Bruyn - Journal of the Academy of Marketing …, 2022 - Springer
Although clickbait is a ubiquitous tactic in digital media, we challenge the popular belief that
clickbait systematically leads to enhanced sharing of online content on social media. Using …

Identifying clickbait: A multi-strategy approach using neural networks

V Kumar, D Khattar, S Gairola, Y Kumar Lal… - The 41st international …, 2018 - dl.acm.org
Online media outlets, in a bid to expand their reach and subsequently increase revenue
through ad monetisation, have begun adopting clickbait techniques to lure readers to click …

Automatic detection of clickbait headlines using semantic analysis and machine learning techniques

M Bronakowski, M Al-Khassaweneh, A Al Bataineh - Applied Sciences, 2023 - mdpi.com
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 …

Towards reliable online clickbait video detection: A content-agnostic approach

L Shang, DY Zhang, M Wang, S Lai, D Wang - Knowledge-Based Systems, 2019 - Elsevier
Online video sharing platforms (eg, YouTube, Vimeo) have become an increasingly popular
paradigm for people to consume video contents. Clickbait video, whose content clearly …

A deep model based on lure and similarity for adaptive clickbait detection

J Zheng, K Yu, X Wu - Knowledge-Based Systems, 2021 - Elsevier
With the rapid development of the Internet and the intensified competition in the media,
media professionals or self-media editors often attract attentions and clicks by clickbait news …

Predicting clickbait strength in online social media

V Indurthi, B Syed, M Gupta… - Proceedings of the 28th …, 2020 - aclanthology.org
Ho** for a large number of clicks and potentially high social shares, journalists of various
news media outlets publish sensationalist headlines on social media. These headlines lure …

Rumor and clickbait detection by combining information divergence measures and deep learning techniques

C Oliva, I Palacio-Marín, LF Lago-Fernández… - Proceedings of the 17th …, 2022 - dl.acm.org
In this article we address the challenge of detecting the generation and spreading of
misleading information in the specific scenario of clickbait. Our contribution consists of a …

Tık odaklı habercilik çerçevesinde ekonomi haberlerinin incelenmesi

M Küçükvardar - Türkiye İletişim Araştırmaları Dergisi, 2023 - dergipark.org.tr
Gazeteciler haberlerini ilgi çekici kılmak ve geniş bir takipçi kitlesine ulaşmak için farklı
iletişim yöntemlerine başvurmaktadır. Bunlardan biri olan tık odaklı habercilik, okuyucuların …