A review on fake news detection 3T's: typology, time of detection, taxonomies. [PDF]
Int J Inf Secur, 2023 Rastogi S, Bansal D.
europepmc +1 more source
Clickbait Detection in Tweets Using Self-attentive Network
CoRR, 2017 Clickbait detection in tweets remains an elusive challenge. In this paper, we describe the solution for the Zingel Clickbait Detector at the Clickbait Challenge 2017, which is capable of evaluating each tweet's level of click baiting. We first reformat the regression problem as a multi-classification problem, based on the annotation scheme.
openaire +2 more sources
Détection de clickbait utilisant fusion multimodale et apprentissage par transfert
, 2020 Internet users are likely to be victims to clickbait assuming as legitimate news. The notoriety of clickbait can be partially attributed to misinformation as clickbait use an attractive headline that is deceptive, misleading or sensationalized.
Praboda Chathurangani Rajapaksha, Rajapaksha Waththe Vidanelage
core +1 more source
Analisis Clickbait pada Judul Berita Bahasa Indonesia menggunakan Word2Vec, Node2Vec, dan Support Vector Machine [PDF]
, 2020 Saat ini portal berita daring menjadi salah satu sumber penyedia informasi yang banyak diakses oleh masyarakat Indonesia. Salah satu cara media daring memperoleh pendapatan adalah melalui jumlah traffic pengunjung situs.
Zuhroh, Nurrida Aini
core
Click me…! The influence of clickbait on user engagement in social media and the role of digital nudging. [PDF]
PLoS One, 2022 Jung AK +4 more
europepmc +1 more source
Did clickbait crack the code on virality? [PDF]
J Acad Mark Sci, 2022 Mukherjee P, Dutta S, De Bruyn A.
europepmc +1 more source
Clickbait Spoiler Detection and Generation
Clickbait content typically uses sensationalized language to entice curiosity and stimulate user interaction, often at the expense of user satisfaction. In this paper, we introduce a spoiler generation system designed to neutralize clickbait by disclosing important information in a clear, informative format. Our system combines three primary components:
openaire +2 more sources
A fine-tuned large language model for improved click-bait title detection
, 2023 Department of Computing Sciences, College of EngineeringThe internet has experienced a widespread phenomenon of clickbait, especially on social media platforms and news websites. Clickbait headlines and descriptions attract clicks and generate ad revenue
Sekharan, Chandra N., Vuppala, Pavan Sai
core
Detecting YouTube Clickbait with Transformer Models: A Comparative Study
Clickbait remains a common strategy on YouTube, where video titles are often crafted to maximize viewer engagement. Although transformer-based machine learning technologies have advanced rapidly, studies that specifically investigate clickbait in YouTube
Saputri, Theresia Ratih Dewi +1 more
core +1 more source
TA-BiLSTM: An Interpretable Topic-Aware Model for Misleading Information Detection in Mobile Social Networks. [PDF]
Mob Netw Appl, 2021 Chang S, Wang R, Huang H, Luo J.
europepmc +1 more source