Jia-Yue Zhang
Papers
1
Total Citations
6
H-Index
1
About
Jia-Yue Zhang is a researcher at the forefront of social network security and graph-based machine learning. Their work centers on detecting malicious social robots—automated accounts that spread disinformation and threaten information integrity online. Zhang’s most-cited paper, "Semi-GSGCN: Social Robot Detection Research with Graph Neural Network" (2020), introduces a semi-supervised graph convolutional network that leverages relational structures between users to classify bots with high accuracy, even when labeled data is scarce. This contribution addresses a critical gap in supervised detection methods, offering a scalable solution for real-world social platforms. With 6 citations, this foundational work has influenced subsequent studies on graph neural networks for anomaly detection. Zhang’s research directly tackles the growing challenge of information manipulation, making their findings valuable for cybersecurity professionals and platform moderators. By combining graph theory with practical detection frameworks, Jia-Yue Zhang is helping to build more resilient and trustworthy online ecosystems.
Research Focus
Key Achievements
Top Papers
- 1Semi-GSGCN: Social Robot Detection Research with Graph Neural Network6 citations · 2020