#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.
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.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-09-28 23:56 UTC1 uses by 1 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 2026-09-28 23:56 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-09-28 23:56 UTCEverything below is measured over the latest 40 public posts (spanning ~12789 hours).
Posting hours (UTC) — busiest: 12:00
Languages: English (30) · German (3) · Italian (2) · French (1) · Tibetan (1) · Spanish (1)
Avg boosts / post: 2
Top of the latest posts
A note of caution about the dictator and his sexual acts with Bill Clinton. Be aware of unconscious biases and idioms about homophobia and sex shaming. It’s easy to make a target of the dictator because this contradicts fascist ideals. And
#EU is acting against the #addicting #algorithm and #manipulation #facebook and #instagram (among others) impose to the EU citizens. The users shall have the #rights to obtain all the parameters of the algorithms used to influence them and
Morgen gibt es unsere neue Folge! In dieser haben wir uns mit Katharina Leyrer über die Repräsentation von Minoritäten in #Sammlungen unterhalten, #Biases in Forschungsdaten, #ValueSensitiveDesign, #Informationsethik und vieles weitere mehr
What “biases” means
Wiktionary · Wikipediabiases/ˈbaɪəsɪz/
- nounInclination towards something; predisposition, partiality, prejudice, preference, predilection.
- verbTo place bias upon; to influence.
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 surfaceFollow #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