#mangarecommendations

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

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
10
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 10
0
Avg reactions / post
Mastodon · last 10
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · mastodon.social (Mastodon public tags API) · fetched 2026-09-02 03:23 UTC
0
08-27
0
08-28
0
08-29
0
08-30
0
08-31
0
09-01
0
09-02

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · mastodon.social (Mastodon public search API) · fetched 2026-09-02 03:23 UTC

No related tags with measured usage found for #mangarecommendations.

Live pulse

measured · mastodon.social (Mastodon tag timeline) · fetched 2026-09-02 03:23 UTC

Everything below is measured over the latest 10 public posts (spanning ~32512 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (10)

Avg boosts / post: 0.4

Top of the latest posts

  • One easy way to discover new manga is to browse by genre rather than searching for a specific title. If you normally read action, try fantasy or supernatural next. You might find something completely different from your usual choices. #Mang

    MyMangaList@mymangalist♥ 0↻ 12026-08-17 14:03 UTCView post →

  • 📚 Looking for your next manga? Explore different genres, discover popular series, and find new manga to add to your reading list. Read Free Manga: https://www5.mymangalist.org/home #Manga #MangaReading #MangaRecommendations

    MyMangaList@mymangalist♥ 0↻ 02026-08-17 14:02 UTCView post →

  • https://www.wacoca.com/kpop/1533023/videos/2026-06-13/ #manga #nana #anime #mangacollecting #funkoanime #booktok #mangarecommendations #mangaedit #KoreanActresses #ナナ（Nana） #韓国女優

    Kpop in Japan@[email protected]♥ 0↻ 02026-06-13 14:52 UTCView post →

#mangarecommendations across platforms

every network with a public tag surface

Follow #mangarecommendations 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/mangarecommendations