Spam / Abuse Detection — Notes
Functional
- Score signups, posts, reviews, messages, payments.
- Rule + ML hybrid.
- Decision: allow / step-up / shadow-ban / block / queue review.
- Feedback loop from reports / chargebacks.
Non-functional
- p99 decision < 100 ms on hot path.
- False positive rate critical (UX impact).
- Adversarial environment — adaptive model freshness.
Trade-offs
- Rules explainable + fast but rigid; ML accurate but opaque.
- Shadow ban vs hard ban: shadow is less hostile but ethically debated.
- Latency budget forces feature pre-computation.
Refs
- "Spam fighting at scale" papers (Akismet, Gmail).
- Yelp / Reddit / X engineering posts.
- ByteByteGo "Design spam detection".