#textmining
Live, measured metrics for the hashtag #textmining from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #textmining
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 · fosstodon.org (Mastodon public tags API) · fetched 2026-09-11 15:01 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-09-11 15:01 UTCNo related tags with measured usage found for #textmining.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-09-11 15:01 UTCEverything below is measured over the latest 40 public posts (spanning ~12257 hours).
Posting hours (UTC) — busiest: 09:00
Languages: English (20) · German (12) · French (8)
Avg boosts / post: 2.3
Top of the latest posts
Promovierende aufgepasst: Ihr seid euch unsicher, ob Topic Modeling das richtige für eure computergestützten Auswertungen ist? Oder doch lieber (nicht) Netzwerkanalyse? Und welche Alternativen gäbe es? Am 17. 11. (16-17:30 Uhr) habt Ihr die
📢 Webinar: An introduction to #AVOBMAT A user-friendly platform for scalable, #multilingual #textmining and #metadata analysis, designed to support research and teaching in #DH. Hosted by @gwdg. Explore it at👉 https://avobmat.hu 📆 Wed 11
A vacancy for a Data Officer within Dogs Trust's data science and analytics research team has gone live this morning: - £37,130 per annum - Fully remote (within UK) - #SQL + #Python and/or #RStats experience sought, alongside #NLP / #TextMi
What “textmining” means
WikipediaText mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.
“Text mining” on Wikipedia (CC BY-SA) →#textmining across platforms
every network with a public tag surfaceFollow #textmining 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/textmining