ByteDance Data Platform
Feb 12, 2025 · Fundamentals
Why A/B Tests Fail in Recommendation Systems and How to Fix Them
This article examines the hidden complexities of A/B experiments in short‑video recommendation feeds, explains why traditional designs produce biased results due to learning, double‑sided, and network effects, and presents practical double‑sided and community‑randomized experiment frameworks to obtain unbiased strategy evaluations.
A/B testingCommunity randomizationDouble-sided effects
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