Twitter plans to expand recommended tweets to all users, including those who may not have seen them in the past
Twitter is now pushing more tweets from accounts users don't already follow into their timelines. The company revealed that it's now surfacing recommendations to all its users …
Context & Ripple Effects
This move completes an arc Twitter has been building for years: it first began placing recommended rather than newest tweets at the top of timelines in 2016, then layered in news links from users' networks in 2018 and nudges like the read-before-retweet prompt in 2020. What was once an opt-out-able experiment at the top of the feed is now the default experience for every user.
The timing matters commercially: with Q2 2022 advertising revenue of $1.08 billion against roughly $4 billion for all of 2021, Twitter's ad business needs more sellable impressions than the follow graph alone generates. Out-of-network recommendations manufacture that inventory.
First-order effects
- Every Twitter user's timeline now mixes in tweets from accounts they don't follow, meaning advertisers gain impression inventory that no longer depends on who a user chose to follow.
- Accounts whose content gets picked up by the recommender can reach non-followers directly, decoupling reach from follower count for the first time at full scale.
Second-order effects
- Creators and brands will start optimizing for what the recommendation algorithm favors rather than for follower growth, shifting where publishers and influencers invest their posting effort.
- Users who preferred a strictly chronological, follow-only feed lose that default entirely — the 2016-era compromise of ranked tweets on top gives way to recommendations throughout.
Third-order effects
- If the pattern holds, Twitter's product becomes an interest-based recommendation engine with the follow graph as one input among many — the structural direction the company later acknowledged by partially open sourcing its recommendation algorithm.
- A fully algorithmic timeline concentrates curation power in Twitter's own ranking choices, raising the stakes for transparency about how those rankings work and whose content they amplify.
The trend: Twitter is finishing a decade-long conversion from a chronological follow-graph feed into an algorithmic recommendation surface, following the same path as its 2016 ranking tests scaled to every user.