#topicmodelling

Live, measured metrics for the hashtag #topicmodelling from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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Own #topicmodelling

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.

$5.00/ year · 14-character #name
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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
9
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 9
0
Avg reactions / post
Mastodon · last 9

Day-by-day usage

measured · mas.to (Mastodon public tags API) · fetched 2026-07-29 00:57 UTC
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27
0
07-28

0 uses by 0 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 2026-07-29 00:57 UTC

No related tags with measured usage found for #topicmodelling.

Live pulse

measured · mas.to (Mastodon tag timeline) · fetched 2026-07-29 00:57 UTC

Everything below is measured over the latest 9 public posts (spanning ~31319 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (6) · French (2) · German (1)

Avg boosts / post: 1.6

Top of the latest posts

  • It is quite fun to occasionally come back to using #slurm to send commands to a super computer node. Let's see if running a #TopicModelling script with a V100 GPU reduces the running time from 80+ hours to a few minutes, as I expect :)

    Tuomas Väisänen 📼🧟‍♂️@[email protected]♥ 0↻ 02026-06-03 10:58 UTCView post →

  • Published at #IRRJ: "Exploring Embedding Interpretability by Correspondences Between Topic Models and Text Embeddings" by Meng Yuan, Lida Rashidi, and Justin Zobel. #InformationRetrieval, #EmbeddingInterpretability, #Explanability, #TopicMo

    IRRJ@[email protected]♥ 0↻ 22025-12-10 09:07 UTCView post →

  • Bien que #Rstats soit le cousin pauvre de #Python en traitement de texte (#NLP), rien n'empêche de l'utiliser pour la modélisation thématique (#topicmodelling). Dans cet exemple, je montre aussi comment soumettre le résultat de l'analyse à

    André Ourednik@[email protected]♥ 0↻ 02024-06-01 12:44 UTCView post →

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/topicmodelling