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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".