To decide which of these things should appear higher in Juan’s News Feed, we need to predict what matters most to him and which content carries the highest value for him. ![]() His favorite Page published an interesting article about the best way to view the Milky Way at night, while his favorite cooking Group posted four new sourdough recipes.Īll this content is likely to be relevant or interesting to Juan because he has chosen to follow the people or Pages sharing it. Another friend, Saanvi, posted a video from her morning run. Since Juan’s login yesterday, his friend Wei posted a photo of his cocker spaniel. To understand how this works in practice, let’s start with what happens for one person logging in to Facebook: We’ll call him Juan. These predictions are based on a variety of factors, including what and whom you’ve followed, liked, or engaged with recently. Put simply, the system determines which posts show up in your News Feed, and in what order, by predicting what you’re most likely to be interested in or engage with. As we move through each stage, the ranking system narrows down those thousands of candidate posts to the few hundred that appear in someone’s News Feed at any given time. In reality, the ranking system is not just one single algorithm it’s multiple layers of ML models and rankings that we apply in order to predict the content that’s most relevant and meaningful for each user. When this happens, we need to find new solutions. When you open up Facebook, that process happens in the background in just the second or so it takes to load your News Feed.Īnd once we’ve got all this working, things change, and we need to factor in new issues that arise, such as clickbait and the spread of misinformation. So we have trillions of posts and thousands of signals - and we need to predict what each of those people wants to see in their feed instantly. Now consider that for each person on Facebook, there are thousands of signals that we need to evaluate to determine what that person might find most relevant. We are now talking about trillions of posts across all the people on Facebook. For each of those people, there are more than a thousand “candidate” posts (or posts that could potentially appear in that person’s feed). More than 2 billion people around the world use Facebook. What’s So Hard About This?įirst, the volume is enormous. We are sharing new details about how our ranking system works and the challenges of building a system to personalize the content for more than 2 billion people and show each of them content that is relevant and meaningful for them, every time they come to Facebook. But under the hood, the machine learning (ML) ranking system that powers News Feed is incredibly complex, with many layers. We publicly share many of the details and features of News Feed. But there’s still quite a lot that’s misunderstood. Most people understand that there’s an algorithm at work, and many know some of the factors that inform that algorithm (whether you like a post or engage with it, etc.). When it comes to the News Feed algorithm, there are many theories and myths.
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