#recommender
Live, measured metrics for the hashtag #recommender from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #recommender
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mas.to (Mastodon public tags API) · fetched 2026-09-27 10:55 UTC2 uses by 2 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mas.to (Mastodon public search API) · fetched 2026-09-27 10:55 UTCLive pulse
measured · mas.to (Mastodon tag timeline) · fetched 2026-09-27 10:55 UTCEverything below is measured over the latest 32 public posts (spanning ~33093 hours).
Posting hours (UTC) — busiest: 11:00
Languages: English (28) · German (4)
Avg boosts / post: 5.3
Top of the latest posts
#FollowGraph is a great example of why #Mastodon does not need #algorithms built in. It is a stand-alone #openSource algorithm that is similar to the #follow #recommender on Twitter, except it is not pushed in your face, the algorithm is ex
Correct me if I'm wrong, but seems you can no longer even read about the shift in #recommender algorithm on #twitter on Wikipedia? First time I've really seen the autocracy come for @[email protected] though of course I've seen pop
EU Kids act: The EU’s plan to make the internet safer for kids European Commission President Ursula von der Leyen and Executive Vice-President Henna Virkkunen presented the EU Kids Act on… #Europe #EU #childsafety #EuropeanCommission #Europ
What “recommender” means
WikipediaA recommender system, also called a recommendation engine or content discovery platform is a type of information filtering system that aims to suggest items most relevant for some input or to a particular user. In the context of social media, search engines, and other online services, a recommender system for a given service might sometimes informally but erroneously be referred to as the service's "algorithm". The use of recommender systems is pervasive, with commonly recognised examples includ
“Recommender system” on Wikipedia (CC BY-SA) →#recommender across platforms
every network with a public tag surfaceFollow #recommender straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/recommender