Adaptive Causal Coordination Detection for Social Media: A Memory-Guided Framework with Semi-Supervised Learning

This paper proposes a memory-guided framework with semi-supervised learning for detecting adaptive causal coordination on social media. The approach aims to identify complex, evolving coordination patterns, which is critical for understanding and mitigating the spread of misinformation and coordinated malicious activities online.