Twitter spam account detection based on clustering and classification methods

KS Adewole, T Han, W Wu, H Song… - The Journal of …, 2020 - Springer
Twitter social network has gained more popularity due to the increase in social activities of
registered users. Twitter performs dual functions of online social network (OSN), acting as a …

Detecting agro: Korean trolling and clickbaiting behaviour in online environments

E Been Choi, J Kim, D Jeong, E Park… - Journal of …, 2024 - journals.sagepub.com
This article presents one of the first approaches to provide the understanding of agro (one of
the unique eye-attracting cues) headlines and thumbnails in online video sharing platform …

Interaction-based behavioral analysis of twitter social network accounts

H İş, T Tuncer - Applied Sciences, 2019 - mdpi.com
This article considers methodological approaches to determine and prevent social media
manipulation specific to Twitter. Behavioral analyses of Twitter users were performed by …

CNN-FastText Multi-Input (CFMI) Neural Networks for Social Media Clickbait Classification

C Sharma, G Singh, PS Muttum… - Recent Advances in …, 2024 - benthamdirect.com
Introduction: User-generated video portals, such as YouTube, are facing the challenge of
Clickbait. These are used to lure viewers and gain traffic on specific content. The real …

A Novel Contrastive Learning Method for Clickbait Detection on RoCliCo: A Romanian Clickbait Corpus of News Articles

DM Broscoteanu, RT Ionescu - arXiv preprint arXiv:2310.06540, 2023 - arxiv.org
To increase revenue, news websites often resort to using deceptive news titles, luring users
into clicking on the title and reading the full news. Clickbait detection is the task that aims to …

Local explainability-based model for clickbait spoiler generation

I Panda, JP Singh, G Pradhan - Journal of Computational Social Science, 2025 - Springer
Clickbait involves creating attention-grabbing or deceptive content aimed at generate more
clicks. While effective for driving online traffic, it often results in misinformation, user …

Clickbait Detection Using Long short-term memory

AA Balan, P Anoop, AS Mahesh - 2022 Second International …, 2022 - ieeexplore.ieee.org
The exploitation of clickbait has lately risen on many social media sites. Click bait is catchy
titles or headlines with the primary goal of attracting attention and encouraging visitors to" …

Using machine learning techniques for clickbait classification

J Huette, M Al-Khassaweneh… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Clickbait refers to misleading links that come with sensationalized headlines. The aim of
these links is to attract the viewers' attention and lure them into clicking on them. These …

[PDF][PDF] A Profile Analysis of User Interaction in Social Media Using Deep Learning.

H İş, T Tuncer - Traitement du signal, 2021 - researchgate.net
Accepted: 26 December 2020 It is highly important to detect malicious account interaction in
social networks with regard to political, social and economic aspects. This paper analyzed …

Web-plugin to Detect Clickbait in News Articles using RNN and LSTM

A Krishneth, JD Dharaneesh, S Jisnu… - 2023 5th …, 2023 - ieeexplore.ieee.org
'Clickbaits' are either false or misleading headlines that aim to attract users' attention and
entice them to click on a link or a news article that isn't really interesting as the title makes it …