Social media platforms are giving users more say over what appears in their feeds
Qwenews.com – For many people, social media recommendations can become uncomfortably precise. A user expecting a baby may find their feed suddenly dominated by pregnancy videos, nursery ideas and birth experiences. Useful at first, that stream of content can quickly feel overwhelming.
Instagram now gives people a more direct way to respond. Users can tell the app they want less content on topics such as “pregnancy” or “birth,” while still choosing to retain recommendations on related subjects, including “newborn parenting hacks.” The feature is part of a broader shift across social media: platforms are adding tools that let people influence the recommendations shaping their daily scrolling.
Instagram and Facebook, both owned by Meta, are joined by YouTube, TikTok and newer services such as Divine in offering ways to customize prominent recommendation feeds or build feeds around particular interests. The changes reflect growing demand for more control after years in which major platforms moved away from feeds based primarily on followed accounts.
Combining discovery with personal choice
The appeal of recommendation systems is straightforward. They can introduce users to creators and subjects they may never have found through the accounts they already follow. But automated feeds can also make people feel as if the platform, rather than the user, is making the important choices.
“What we’ve really tried to focus on is: how can we recreate the sense of agency that you had when you were controlling the accounts that you followed, but in a world that still gives you the benefits of recommendations,”
Instagram Vice President of Product Tessa Lyons said the goal is to preserve opportunities for discovery while restoring that sense of user agency.
Improved artificial intelligence tools are helping services interpret plain-language feedback. Instead of relying only on signals such as viewing time, likes, shares and follows, platforms can increasingly process a person’s stated request to see more or less of a topic.
“We’re able to do something we’re never able to do before, which is actually enable people to use human language… to say, like, I want to see more of this topic or less of this topic,”
Lyons said. She added that platforms previously could not reliably identify the most relevant material even when someone named a subject such as “tennis.”
That distinction matters to users trying to fine-tune a feed without abandoning recommendations altogether. Someone interested in fitness, for example, may want workout guidance but not repeated posts about a particular diet trend. A parent may welcome practical child-care ideas while choosing not to see emotionally intense birth-related videos. Direct controls offer a clearer signal than simply skipping posts one at a time.
A response to frustration with algorithmic feeds
The industry’s renewed focus on feed settings marks a notable departure from the direction many large platforms took in recent years. Chronological timelines based on followed accounts were often replaced or subordinated by recommendation systems designed to predict what would keep people engaged.
Social media companies have vast amounts of activity data, including information generated both on and off their services. Their algorithms have been built on the premise that this data can forecast a user’s interests more effectively than a manually selected list of accounts. That approach can benefit engagement, but it has also produced persistent complaints that feeds can veer toward irrelevant, repetitive or harmful material.
Recommendations aimed at younger users have drawn especially serious scrutiny when they promote troubling content. More broadly, dissatisfaction has intensified as AI takes a larger role in organizing what people encounter online.
“People have gotten fed up with AI feeding them stuff,”
said Tim Weninger, a computer science and engineering professor at the University of Notre Dame who studies AI and social media.
“They miss the old days … They just want to be able to follow what they follow and see the latest updates.”
The reaction is also part of a wider public backlash against AI, Weninger said. For users, the practical question is less about how a recommendation model works than whether it can be corrected when it gets their interests wrong.
Different approaches to shaping recommendations
Instagram had already taken a partial step toward greater feed choice in 2022, when it restored chronological viewing options through its “following” and “favorites” feeds. Those views show posts only from accounts users choose. However, the app returns to its recommended main feed whenever it is opened, leaving the algorithmic experience as the default.
TikTok introduced its own controls last June with “manage topics.” The tool allows users to adjust, using a sliding scale, how much content from broad categories should appear in their main feed. Categories include fashion and beauty as well as health and fitness. It does not fully eliminate a subject, but it provides TikTok with a more explicit indication of a user’s preferences.
The platform also introduced “smart keyword filtering.” When a user flags a keyword, videos containing that term can be removed from the feed, along with videos that include similar or related terms. The feature can be particularly helpful when a person wants to reduce exposure to a recurring theme without having to identify every possible variation manually.
Instagram expanded on that idea months later with “your algorithm.” The setting displays topics the app believes interest a user and lets that person add subjects they want to encounter more often or identify ones they would prefer to avoid. Initially limited to Reels, “your algorithm” now applies across Instagram and has recently been extended to Facebook.
These tools do not mean social feeds are returning entirely to the pre-algorithm era. Recommendations remain central to how major platforms surface content. But the emerging model gives users more opportunities to intervene, whether they want to narrow an unwanted topic, reinforce a current interest or simply regain some of the predictability once provided by chronological feeds.
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