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EngineeringMar 18, 2026

Friend Bubbles: Enhancing Social Discovery on Facebook Reels

Facebook's Friend Bubbles feature enhances social discovery on Facebook Reels by showcasing content liked or reacted to by a user's friends, making it easier to connect over shared interests. The system uses machine learning to estimate relationship strength and rank content, combining social and interest signals to recommend personalized content. This feature creates a feedback loop that improves recommendations and strengthens social connections, fostering meaningful engagement and conversation. The Friend Bubbles recommendation system includes components such as Viewer-Friend Closeness and Video Relevance, which work together to surface relevant, friend-interacted content. The system uses complementary machine learning models to identify which connections a person feels closest to, and incorporates context-specific closeness prediction models to capture closeness in context. To rank high-quality friend content effectively, the system sources inventory by expanding the top of the funnel to ensure sufficient candidate volume, and enables models to incorporate viewer-friend relationship strength and learn downstream engagement on videos with social bubbles. A continuous feedback loop ensures that the system improves its understanding of

SocialScale

1 min

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