#biases

Live, measured metrics for the hashtag #biases 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 #biases

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.

$520.70/ year · 6-character #name
Claim #biases — $520.70/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
—
Uses / 7 days
Mastodon
—
Accounts / 7 days
Mastodon
—
Recent posts
Mastodon
—
Recent pace
Mastodon · last 0
—
Avg reactions / post
Mastodon · last 0
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-09-25 23:15 UTC

No measured public usage for #biases in the last 7 days. That is a real result, and a good one to know: this hashtag is wide open right now. We show a dash before we ever show a made-up number. Browse the trending index for tags with live measurements.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-09-25 23:15 UTC

No related tags with measured usage found for #biases.

Live pulse

measured · Mastodon tag timeline · fetched 2026-09-25 23:15 UTC

No recent public posts found for #biases on Mastodon. Nothing measured, so nothing shown.

What “biases” means

Wiktionary · Wikipedia

biases/ˈbaɪəsɪz/

  • nounInclination towards something; predisposition, partiality, prejudice, preference, predilection.
  • verbTo place bias upon; to influence.
Full entry on Wiktionary →

Bias is a disproportionate weight in favor of or against an idea or thing, usually in a way that is inaccurate, closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average.

“Bias” on Wikipedia (CC BY-SA) →

#biases across platforms

every network with a public tag surface

Follow #biases 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/biases