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Instagram launches a new feature that lets users customize the topics influencing their Reels algorithm, reshaping content curation and discovery.

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Instagram has launched a groundbreaking feature that empowers users to directly personalize the algorithm behind their Reels feed, marking a significant evolution in how content is curated and consumed on the platform. The new controls, initially available to select users, allow Instagram members to specify topics they want to see more or less of, fundamentally changing the user experience and expanding customization in social media discovery.

Direct Algorithm Customization Comes to Instagram Reels

Instagram’s latest update introduces a new user interface in the Reels tab that invites users to “tune your algorithm.” After updating to the latest version of the app, users can access the settings via the Reels tab, where they are presented with a description of how the current algorithm interprets their activity and interests. Users can then actively add topics of preference—such as “Pet parenting” or “Relationship humor”—and remove topics they prefer to avoid, refining the types of videos that appear in their Reels feed.

Upon accessing this feature, users are given a categorized list of topics generated from their past activity and engagement on Instagram. They can augment this list, adding new interests or removing existing ones to increase or decrease representation on their feed. This approach moves curation tools beyond mere like/dislike or “see less” options, providing granular control over future recommendations. The change can be shared to stories, letting friends know about the new level of personalization.

Broader Implications and Future Expansion

Adam Mosseri, Instagram’s head, announced that this capability is currently being tested with Reels and is expected to expand to the Explore section in the near future. In addition, Meta is exploring similar controls for Threads, its text-based platform, paving the way for even further user agency across its services. The move is seen as a response to user demand for increased transparency and influence over recommendation systems, as well as concerns about algorithmic echo chambers and unwanted content exposure.

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