How YouTube Recommendation Algorithm Works

The YouTube algorithm works for homepage recommendations by considering three key factors:

personalization

performance
satisfaction.

Personalization: This facet involves analyzing a user's viewing habits, especially the channels they are subscribed to. For instance, if a person watches an Alex Harmozi video, the algorithm identifies other videos that have been watched by viewers of Alex Harmozi. YouTube then ranks these related videos and generates a list of potentially interesting content for the viewer.

2. Performance: YouTube collects real-time data on how a video is performing. It tracks whether the viewer regularly watches content from a particular channel and observes how similar users react to the video. This includes metrics such as:

- Did the viewer click on the video?

- How long did they watch it?

- Did they like or dislike it?

- Did they click "not interested"?

- Did they scroll past it?

3. Satisfaction: Not all watch time is equal in value. To evaluate satisfaction, YouTube conducts surveys and feedback mechanisms. This helps gauge how enjoyable and satisfying a video is to the viewer.

All of these elements work together to determine which video is presented to a user on their homepage. The algorithm's goal is to provide a personalized and enjoyable experience by suggesting videos that align with the viewer's interests and preferences.

I got this info from YouTube employee "TODD" who works in the YouTube recommendations system

and I hope this will help you to understand YouTube better

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