Threads is ??????? ???????? ?? ????????apparently deprioritising its algorithmic feed, allowing you to see more posts from people you actually follow. It seems Meta is trying to increase the appeal of its microblogging platform as people search for X alternatives in the wake of the U.S. election.

Head of Instagram Adam Mosseri announced the change in a Threads post on Thursday. Though his initial post did not specify whether he was referring to Threads or Instagram, he implied it was the former in a subsequent reply.

"We are rebalancing ranking to prioritize content from people you follow, which will mean less recommended content from accounts you don’t follow and more posts from the accounts you do starting today," Mosseri wrote. "For you creators out there, you should see unconnected reach go down and connected reach go up."

View on Threads

Many users have compared Threads' announced changes to Twitter spinoff Bluesky, which already defaults to showing users content from accounts they follow. Bluesky CEO Jay Graber has previously stated that it aims to offer a "marketplace of algorithms" users can choose from instead of a single "master algorithm," noting that a chronological feed of accounts you follow is technically an algorithm as well.

"Great to see other social networks copy custom feeds!" Bluesky wrote on its Threads account, apparently in response to Mosseri's announcement. "This is the kind of competition and innovation that's been missing from social for the last decade, because progress has been locked within tech giants. This is what improves our experience online."

love the giant brain super genius action of "maybe people want to read the things posted by the people they follow"

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— the Mountain Goats (@themountaingoats.bsky.social) November 22, 2024 at 1:51 PM

Having experienced them all:Bluesky > Threads > Staring into the middle distance in longing > the emptiness inside > twitter

— John Green (@johngreensbluesky.bsky.social) November 21, 2024 at 8:56 AM

Upon reflection, staring into the middle distance in longing is better than threads.

— John Green (@johngreensbluesky.bsky.social) November 21, 2024 at 9:02 AM

bluesky is so much better at threads then threads.

— Vijay Pemmaraju (@vijay.io) November 21, 2024 at 4:14 PM

A significant number of those abandoning Elon Musk's X have moved to Bluesky, which gained over 700,000 new users to hit 20 million this week. Meanwhile, Mosseri announced that Threads reached 275 million monthly active users at the start of this month — a number Meta is clearly hoping to grow.

"This [ranking rebalancing] is definitely a work in progress — balancing the ability to reach followers and overall engagement is tricky — thanks for your patience and keep the feedback coming," Mosseri wrote on Tuesday.

• BlueSky is pitching itself as a Threads alternative now
• I've barely used Bluesky, and the engagement already feels more real
• Apparently, Threads has a whopping 275 million users
• Meta promises a fix to Threads' engagement bait problem
• 8 Twitter/X alternatives for if you want to get off Elon Musk's wild ride

Threads' decision to back off algorithmically recommended content is a departure from Meta's apparent strategy in recent years. Instagram and Facebook literally doubled down on algorithmic feeds in 2022, with Meta CEO Mark Zuckerberg declaring that both would increase the amount of algorithmically chosen content they displayed twofold. This was despite the overwhelming unpopularity of the algorithmic feed, which Meta was well aware of but determined to power through.

"Now, if you're seeing things in your Feed that are recommendations that you're not interested in, that means that we're doing a bad job ranking, and we need to improve," said Mosseri at the time. "But we're going to continue to try and get better at recommendations because we think it's one of the most effective and important ways to help creators reach more people."

It now seems that, at least for Threads, Meta is finally letting users see more of the content they actually signed up for, and deprioritising algorithmic experimentation.