#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.

hashtag.org network · sponsored

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.

$10.85/ year · 11-character #name
Claim #recommender — $10.85/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
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Uses / 7 days
Mastodon
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Accounts / 7 days
Mastodon
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Recent posts
Mastodon
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Recent pace
Mastodon · last 0
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Avg reactions / post
Mastodon · last 0
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Reddit posts / month
Reddit search
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Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-09-26 14:56 UTC

No measured public usage for #recommender in the last 7 days. That is a real result, and a good one to know: this hashtag is wide open right now. We show a dash before we ever show a made-up number. Browse the trending index for tags with live measurements.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-09-26 14:56 UTC

No related tags with measured usage found for #recommender.

Live pulse

measured · Mastodon tag timeline · fetched 2026-09-26 14:56 UTC

No recent public posts found for #recommender on Mastodon. Nothing measured, so nothing shown.

What “recommender” means

Wikipedia

A 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 surface

Follow #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