#Hypergraphs
Live, measured metrics for the hashtag #Hypergraphs from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #hypergraphs
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 · mastodon.online (Mastodon public tags API) · fetched 2026-09-12 00:20 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-09-12 00:20 UTCNo related tags with measured usage found for #hypergraphs.
Live pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-09-12 00:20 UTCEverything below is measured over the latest 24 public posts (spanning ~36521 hours).
Posting hours (UTC) — busiest: 09:00
Languages: English (22) · Italian (2)
Avg boosts / post: 0.9
Top of the latest posts
Let's start my activity on Mastodon with great news! I'm thrilled to announce that our paper "A Survey on Hypergraph Representation Learning" has been published in the latest issue of ACM Computing Surveys! Huge thanks to Mirko Polato for h
New paper! We recently introduced a new definition of distance on weighted higher-order networks that accounts for the structural properties of their support hypergraph. Now, we generalize three distance-based network observables, and, usin
New paper. With Ekaterina Vasileva, Liubov Tupikina, Dmitry Fedorov, Daniil Musatov, Andrei Raigorodskii and Stefano Boccaletti. The naive generalization of the concept of distance to hypergraphs is equivalent to applying a clique-projectio
What “hypergraphs” means
WikipediaIn mathematics, a hypergraph is a generalization of a graph in which an edge can join any number of vertices. In contrast, in an ordinary graph, an edge connects exactly two vertices.
“Hypergraph” on Wikipedia (CC BY-SA) →#hypergraphs across platforms
every network with a public tag surfaceFollow #hypergraphs 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/hypergraphs