YouTube changes the way it recommends content to users

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YouTube is testing custom data sources to address inaccuracy of recommendation algorithms, helping users proactively control the content they want to watch.

YouTube is rolling out a new experimental feature called Your Custom feed - your custom data source to address the issue of users dissatisfied with video recommendations based on current algorithms.

This is considered an effort of the platform in bringing a more accurate and proactive personalized experience to more than 2 billion global users.

For many years, YouTube's suggestion algorithm has been criticized for sometimes misinterpretating viewer behavior.

Just watch a few Disney videos, YouTube can immediately think you are a crazy fan and flood your homepage with similar content, whether your true interests are broader or completely different.

Such deviations make many people feel that the proposal does not accurately reflect their needs.

The new testing feature allows users to set up their own content they want to watch. In the testing interface, next to the " homepage" button, the "Your Custom Data Source" section will appear.

When clicking, users can enter reminders such as cuisine, documentary, technology, travel alone to orient the type of video to appear in the main source.

This approach shifts users from a passive waiting algorithm to a proactive experience design.

For example: if you type cooking, YouTube will prioritize displaying related videos in subsequent visits, making the content more suitable for personal needs and reducing unrelated recommendations.

In addition to the new personalization feature, YouTube has also recently tightened management of content viewing behavior. The platform has limited the number of times Shorts are rolled per day to help young people control their usage time.

At the same time, YouTube has promoted the AI redigation tool in the YouTube Create application, allowing users to automatically process, cut, and arrange raw footage, helping creators optimize the video production process.

This experiment shows that YouTube is expanding its personalized approach, making efforts to reduce dependence on traditional algorithms and putting more control into the hands of users.

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