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Twitter adds “Who to follow” section in Android and iOS timelines that appears depending on how frequently you use the service

Roberto Baldwin / Engadget :

Engadget Roberto Baldwin

Context & Ripple Effects

This is another step in Twitter's 2015 campaign to make the home timeline a curated surface rather than a purely chronological stream: months after rolling out "While you were away" recap cards to iOS, the company is now injecting "Who to follow" modules directly into the feed on Android and iOS. The twist is the gating logic — the module appears depending on how frequently a given person uses the service, so the timeline itself is adapting per user.

That frequency signal matters because it shows Twitter treating the timeline as an intervention point for re-engagement, not just content delivery. The same playbook continues afterward with the dedicated Connect tab for account suggestions and event-grouped modules like Happening Now.

First-order effects

  • Lighter-usage Twitter users on mobile start seeing follow recommendations embedded mid-timeline, while heavier users see the surface less often — the same account gets a different feed based purely on its owner's activity cadence.

Second-order effects

  • Accounts that win algorithmic suggestion slots gain a distribution channel that doesn't depend on existing followers, and every subsequent curated module (recaps, Connect, Happening Now) competes for the same timeline real estate that organic tweets previously owned alone.

Third-order effects

  • The pattern points toward algorithmic curation becoming the default experience — a trajectory that runs all the way to 2023, when Twitter reversed course and began defaulting users to the last timeline they had open instead of the algorithmic feed, effectively making chronological order an opt-in choice rather than the baseline.

The trend: Social timelines are shifting from uniform chronological streams to per-user adaptive surfaces, with platforms using activity signals to decide when to interleave algorithmic recommendations into the feed.