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Found 4 papers, 0 papers with code
BotSSCL: Social Bot Detection with Self-Supervised Contrastive Learning
To address these challenges, we propose a novel framework for social Bot detection with Self-Supervised Contrastive Learning (BotSSCL).
False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations
While researchers from various disciplines have investigated different manipulation-triggering elements of OSNs (such as understanding information diffusion on OSNs or detecting automated behavior of accounts), these works have not been consolidated to present a comprehensive overview of the interconnections among these elements.
Machine Learning-based Automatic Annotation and Detection of COVID-19 Fake News
Existing work neglects the presence of bots that act as a catalyst in the spread and focuses on fake news detection in 'articles shared in posts' rather than the post (textual) content.
A Review of Computer Vision Methods in Network Security
Network security has become an area of significant importance more than ever as highlighted by the eye-opening numbers of data breaches, attacks on critical infrastructure, and malware/ransomware/cryptojacker attacks that are reported almost every day.
