Isolate the algorithm.
See what it actually changes.

Narro is user-curated social media. A participant adds the profiles they already follow on Instagram, TikTok, YouTube, X, Facebook, or LinkedIn, and Narro shows only the posts from those specific profiles, in the order they were posted. No ranking, no recommendations, no ads. The accounts don't change. The algorithm does.

That makes some comparisons possible that are hard to run today: across platforms, over months instead of a single lab session, or against the same accounts' ordinary, algorithmic feed.

What can an algorithm-free, cross-platform feed measure that platforms can't?

Narro shows a participant only the posts from the accounts they already follow on Instagram, TikTok, YouTube, X, Facebook, or LinkedIn, in the order they were posted, with nothing ranked or recommended. The same no-algorithm setup works on each of the six platforms, on its own or mixed into one feed. That turns what the algorithm changes from a guess into something you can measure, and compare across platforms in one study.

What this opens up

Run the same study on more than one platform

You can build a feed for Instagram, another for TikTok, another for LinkedIn, each with the same setup and no algorithm. That lets you test whether an effect shows up on more than one platform, instead of being stuck with whichever one happens to give you API access. Platforms aren't linked to each other: adding someone's TikTok doesn't pull in their Instagram. Each feed only shows posts from the specific profiles you add to it.

Separate who someone follows from how it's ranked

Which accounts someone follows and how a platform ranks their posts are normally stuck together, so you only ever see one bundled with the other. Narro is the same accounts, delivered chronologically instead of ranked, which gives a study something to compare against a participant's ordinary, algorithmic feed of those same accounts.

Track exposure over weeks, with WILO

WILO, short for Where I Left Off, marks the last post a participant read and picks up from exactly there next time. Paired with a feed that has a real end, that means nothing gets missed and nothing repeats between sessions, so exposure stays consistent across a study that runs for weeks instead of one lab sitting.

Pull the feed into your own analysis, with RSS

Every Narro feed also has a plain RSS 2.0 URL. That's a standard, auditable way to archive a feed over the course of a study or run it through your own text or image analysis, without building a scraper.

Share a feed without asking for a login

The public feed view turns a feed into a link. A participant, a class, or a collaborator can open it and see the posts without creating an account or handing over platform credentials, which makes recruiting easier and consent conversations simpler.

Add Narro to your research tools

We'll follow up to talk through configuration and the academic rate.

Just want to look around? Try Narro yourself

The variable, stated plainly

A social network is just the accounts a person chose to follow. Social media is the ranking, recommendation, and advertising layer platforms build on top of that. On every major platform, the two are stuck together.

Narro pulls them apart. That's the whole idea behind user-curated social media: keep the accounts, remove the algorithm. Ranked versus not ranked is the exact comparison most algorithm studies want to test, and now it's a feed you can build instead of a theory you can only model.

What a lab actually gets

  • A feed only ever shows posts from the profiles you specifically added to it. Nothing else, and nothing missing.
  • Four view modes, masonry, list, grid, and gallery, so you can standardize how a feed looks across a study.
  • No tracking, no ads, no hidden ranking. Easy to check and write into a methods section or an IRB application.
  • We'll work with you on study design, and there's a discounted academic rate for the PI and study participants.

Common questions

What new kinds of studies does an algorithm-free feed make possible?
A few things that are hard to study today: whether an effect holds across platforms, not just one; what happens over real weeks instead of a single lab session; or how a chronological feed of a participant's own accounts compares to their ordinary, algorithmic feed of those same accounts.
Is there a real-world control condition for algorithmic-effects research?
Yes. Narro shows a participant only the posts from the Instagram, TikTok, X, YouTube, Facebook, or LinkedIn accounts they already follow, in the order they were posted, with nothing ranked or recommended. The accounts stay the same. Only the algorithm is gone.
Can a study include profiles from more than one platform?
Yes. Narro treats Instagram, TikTok, YouTube, X, Facebook, and LinkedIn profiles the same way, so a study can build a separate feed per platform or mix profiles from several into one. Platforms aren't linked to each other: adding someone's TikTok doesn't pull in their Instagram. You add each profile yourself.
What is WILO?
WILO stands for Where I Left Off. It marks the last post a participant read in a feed and picks up from exactly there next time, so nothing gets missed or repeated between sessions. That keeps exposure consistent in a study that runs over days or weeks.
Does Narro track users or collect engagement data?
No. Narro doesn't track users, doesn't sell data, and doesn't require a platform login to follow public accounts. Posts appear in the order they were posted, with nothing hidden or ranked, so it's easy to check and describe in a methods section or an IRB application.
Is Narro free for researchers or study participants?
No. There's a discounted academic rate for the PI and study participants, set up directly with us. It costs less than the standard price, but it isn't free.
Can I export feed data for analysis?
Every Narro feed has a plain RSS 2.0 URL you can pull into your own pipeline or use to archive the feed over the course of a study.
What happens after I submit the form?
It goes straight to our team as an inquiry. We'll follow up at the email you give us to talk through whether Narro fits, what configuration would look like, and the academic rate.

Bring the question you're trying to isolate.

Not a researcher? See the other reasons people use Narro