#synthetictext

Live, measured metrics for the hashtag #synthetictext 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 #synthetictext

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 · 13-character #name
Claim #synthetictext$5.00/yrBuy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
6
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 6
0.2
Avg reactions / post
Mastodon · last 6

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-28 22:55 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 · fosstodon.org (Mastodon public search API) · fetched 2026-07-28 22:55 UTC

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-28 22:55 UTC

Everything below is measured over the latest 6 public posts (spanning ~21084 hours).

Top of the latest posts

  • This is precisely the right model to have for LLMs. They are optimizing for "is this a suitable reply to this entry text". And *the entire conversation* is fed back as the new entry text. It is still remarkable that the result of that optim

    Dr. Juande Santander-Vela@[email protected]112025-09-09 15:13 UTCView post →
  • Just about everything that I read in English these days, including news reports and op-eds, are all AI generated text. It seems no one is writing anything anymore. Plastic plastic everywhere. #SyntheticText

    kayaniv hsal@[email protected]002025-11-09 10:05 UTCView post →
  • Just came across this insightful article on watermarking for large language models! 📝 It explores how watermarking can help distinguish between human and AI-generated text, ensuring responsible usage. A great read for anyone interested in

    Debby@[email protected]012024-10-25 09:05 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/synthetictext