Evaluating the Generalization Capabilities of Community Models for Malicious Content Detection on Social Media

Community models for malicious content detection on social media graphs often perform well on benchmark datasets but struggle to generalize to new graphs, domains, and tasks. A novel few-shot subgraph sampling approach is proposed to better assess inductive generalization capabilities of these models.