#sparxivdigest
Live, measured metrics for the hashtag #sparxivdigest from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #sparxivdigest
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 2026-10-13 19:04 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.social (Mastodon public search API) · fetched 2026-10-13 19:04 UTCNo related tags with measured usage found for #sparxivdigest.
Live pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-13 19:04 UTCEverything below is measured over the latest 40 public posts (spanning ~2376 hours).
Posting hours (UTC) — busiest: 10:00
Languages: English (40)
Avg boosts / post: 1
Used together with
No co-used tags in the sample.
Top of the latest posts
https://arxiv.org/abs/2307.07619 'Stochastic dynamics and the Polchinski equation: an introduction' - Roland Bauerschmidt, Thierry Bodineau, Benoit Dagallier Proving that probability measures satisfy nice concentration properties via functi
https://arxiv.org/abs/2307.07131 'Parallelising Glauber dynamics' - Holden Lee Glauber dynamics (also 'Gibbs sampling') is an MCMC technique for sampling from certain classes of probability distribution, often those conforming to a suitable
https://arxiv.org/abs/2307.07086 'Value-Gradient Iteration with Quadratic Approximate Value Functions' - Alan Yang, Stephen Boyd Certain approaches to reinforcement learning and control focus on { learning, approximation, optimisation, ...
#sparxivdigest across platforms
every network with a public tag surfaceFollow #sparxivdigest 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/sparxivdigest