6 citations · 7 across the 2 of their papers we have counts for
4 papers
Muti-scale Graph Neural Network with Signed-attention for Social Bot Detection: A Frequency Perspective
Shuhao Shi, Kai Qiao, Zhengyan Wang +4
The presence of a large number of bots on social media has adverse effects. The graph neural network (GNN) can effectively leverage the social relationships between users and achie…
RF-GNN: Random Forest Boosted Graph Neural Network for Social Bot Detection
Shuhao Shi, Kai Qiao, Jie Yang +3
The presence of a large number of bots on social media leads to adverse effects. Although Random forest algorithm is widely used in bot detection and can significantly enhance the…
Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection
Shuhao Shi, Kai Qiao, Jie Yang +3
The presence of a large number of bots in Online Social Networks (OSN) leads to undesirable social effects. Graph neural networks (GNNs) are effective in detecting bots as they uti…
MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmark
Shuhao Shi, Kai Qiao, Jian Chen +5
The development of social media user stance detection and bot detection methods rely heavily on large-scale and high-quality benchmarks. However, in addition to low annotation qual…