#ImageForensics

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

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1
Uses / 7 days
Mastodon
1
Accounts / 7 days
Mastodon
40
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 40
0
Avg reactions / post
Mastodon · last 40
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-11-09 20:03 UTC
1
11-03
0
11-04
0
11-05
0
11-06
0
11-07
0
11-08
0
11-09

1 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 2026-11-09 20:03 UTC

No related tags with measured usage found for #imageforensics.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-11-09 20:03 UTC

Everything below is measured over the latest 40 public posts (spanning ~7183 hours).

Posting hours (UTC) — busiest: 00:00

00:0012:0023:00

Languages: English (40)

Avg boosts / post: 0.7

Top of the latest posts

  • Forensically, one of the ways to tell a photo is not the original is to check whether it has been resaved. Editing almost always means a resave: the app decodes the JPEG, you change something, and it compresses the whole picture again when

    kennethbspringer.au@kennethspringer@infosec.exchange♥ 0↻ 12026-11-03 08:04 UTCView post →

  • #ImageForensics, an easy one! Spot the two identical panels.

    Elisabeth Bik@elisabethbik.bsky.social@bsky.brid.gy♥ 0↻ 02026-07-29 00:08 UTCView post →

  • Eighteen panels, each one showing a different sample. But - can you spot the overlapping panels? This one is not too hard. #ImageForensics

    Elisabeth Bik@elisabethbik.bsky.social@bsky.brid.gy♥ 0↻ 02026-07-02 18:55 UTCView post →

#imageforensics across platforms

every network with a public tag surface

Follow #imageforensics 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.

X (Twitter) ↗Instagram ↗TikTok ↗Facebook ↗LinkedIn ↗YouTube ↗Threads ↗Bluesky ↗Mastodon ↗Reddit ↗Pinterest ↗Tumblr ↗

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/imageforensics