How Facebook Evaluates Its Newsfeed Recommendations: Metrics, Models, and User Surveys

Facebook evaluates its Newsfeed recommendation quality through three pillars—machine-learning model metrics like AUC, extensive product data KPIs such as DAU and interaction rates, and user-survey feedback—while maintaining long-term backtests and emphasizing the risks of relying on a single metric.

A/B testingKPIRecommendation Systems

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