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Learn why a video is recommended For You


At TikTok, we want people to feel empowered creating, connecting, and engaging on our platform. That’s why we equip creators and viewers with a range of features, tools, and resources so they can stay in control of their experience. Today we’re adding to that toolbox with a feature that helps bring more context to content recommended in For You feeds.

See why content is recommended for you

TikTok For You feeds enable people to discover an incredible diversity of ideas, creators, products, and entertainment. Our system recommends content by ranking videos based on a combination of factors based on your activity on our app, which includes adjusting for things you indicate you’re not interested in. Our goal is to serve a range of relevant and entertaining content. To help people understand why a particular video has been recommended to them, we’re rolling out a new tool over the coming weeks. Here’s how it works:

  • In your For You feed, tap on the share panel.
  • Then, tap the question mark icon called “Why this video”
  • From there, you can see reasons why a particular video was recommended to you.

Our recommendation system is powered by technical models, so we tried to make the technical details more easily understandable by breaking down reasons like:

  • user interactions, such as content you watch, like or share, comments you post, or searches
  • accounts you follow or suggested accounts for you
  • content posted recently in your region
  • popular content in your region

This feature is one of many ways we’re working to bring meaningful transparency to the people who use our platform, and builds on a number of steps we’ve taken towards that goal. For instance, we publish guidelines for content categories that are ineligible for recommendation, tools to help customize recommendations, and educational resources that explain how our content recommendations work. Looking ahead, we’ll continue to expand this feature to bring more granularity and transparency to content recommendations.

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