Friend Bubbles: 增强 Facebook Reels 上的社交发现
- Friend bubbles in Facebook Reels highlight Reels your friends have liked or reacted to, helping you discover new content and making it easier to connect over shared interests.
- Facebook Reels 中的 Friend bubbles 会突出显示你的朋友点赞或互动过的 Reels，帮助你发现新内容，并更容易通过共同兴趣建立联系。
- This article explains the technical architecture behind friend bubbles, including how machine learning estimates relationship strength and ranks content your friends have interacted with to create more opportunities for meaningful engagement and connection.
- 本文解释了 friend bubbles 背后的技术架构，包括 machine learning 如何估计关系强度并对您的朋友互动过的内容进行排名，以创造更多有意义的参与和连接机会。
Friend bubbles enhance the social experience on Facebook Reels by helping you discover content your friends enjoy, creating a shared viewing experience and sparking new conversations. With a quick tap on a bubble, you can start a one-on-one conversation with any friend who has engaged with that Reel.
朋友气泡通过帮助您发现朋友喜欢的 content，从而提升 Facebook Reels 上的社交体验，创造共享观看体验并引发新对话。只需轻点气泡，您就可以与任何互动过该 Reel 的朋友开始一对一对话。
This feature combines social and interest signals to recommend more relevant, personalized content while making it easier to start conversations with the people who matter most to you. When videos connect to both personal interests and friend-related interests, they create a feedback loop that improves recommendations and strengthens social connections.
此功能结合社交信号和兴趣信号来推荐更相关、个性化的内容，同时使与您最重要的人开始对话变得更容易。当视频连接个人兴趣和朋友相关兴趣时，它们会创建一个反馈循环，从而改善推荐并加强社交联系。
An Overview of the Friend Bubbles System Architecture
Friend Bubbles 系统架构概述
The friend bubbles recommendation system includes several components that work together to surface relevant, friend-interacted content by blending video-quality signals with social-graph signals:
friend bubbles 推荐系统包括几个协同工作的组件，通过融合视频质量信号与 social-graph 信号，来呈现相关的、朋友互动过的内容：
- Viewer-Friend Closeness (Whose Interactions Matter Most): Identifies which friends’ interactions are most likely to interest the viewer.
- Viewer-Friend Closeness (Whose Interactions Matter Most)： 识别哪些朋友的互动最可能引起观看者的兴趣。
- Video Relevance (What ...