Memes & entertainment — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 99% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 6 other registered channels. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 34 of the 34 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 322 comparable posts for this entry, running 5 August 2026 to 23 September 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @poshliea. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
66 measurements spanning 96 days, net -2,273. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 28,294–31,249 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 66
Measured (UTC)
Subscribers
Change
11 Nov 2026, 19:59
28,635
-45
9 Nov 2026, 19:59
28,680
-20
8 Nov 2026, 14:19
28,700
-42
7 Nov 2026, 05:27
28,742
-21
6 Nov 2026, 02:00
28,763
-20
5 Nov 2026, 04:00
28,783
-28
4 Nov 2026, 05:01
28,811
-16
3 Nov 2026, 03:18
28,827
-20
2 Nov 2026, 04:09
28,847
-29
1 Nov 2026, 00:46
28,876
-26
30 Oct 2026, 23:01
28,902
-32
29 Oct 2026, 23:36
28,934
-11
28 Oct 2026, 20:47
28,945
-31
27 Oct 2026, 16:58
28,976
-37
26 Oct 2026, 16:38
29,013
-19
25 Oct 2026, 19:06
29,032
-15
24 Oct 2026, 21:16
29,047
-16
24 Oct 2026, 00:14
29,063
-11
23 Oct 2026, 00:04
29,074
-30
21 Oct 2026, 22:27
29,104
first reading
Engagement
428 posts held, back to 5 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 71 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 428 posts for this entry, the most recent from 23 September 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
6m 11s
Average length
19s
Measured directly from 20 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
96 reactions across 59 posts, in 17 distinct kinds. The most used accounts for 32.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
31
32.3%
😁
15
15.6%
😨
10
10.4%
🤬
9
9.38%
💋
8
8.33%
🥰
6
6.25%
🤣
3
3.13%
❤🔥
2
2.08%
🏆
2
2.08%
💯
2
2.08%
🗿
2
2.08%
💔
1
1.04%
😍
1
1.04%
😢
1
1.04%
😱
1
1.04%
🙈
1
1.04%
🙏
1
1.04%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 71 of the 428 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 96 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 428 most recent posts we hold, published 5 August 2026 to 23 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
П23. Как-то у подруги был ДР, ей исполнялось 17, суть в том что она инвалидка, передвигается в инвалидной коляске. И мы с друзьями хотели рофлянуть над ней (он и сама над собой рофлит над счёт что она на коляске), так вот подарили ей кроссы адики. Пару дней назад вижу ее и спросил "как кроссовки? Не давят?" Она ответила, что КРОССОВКИ ПИЗДАТЫЕ, ПРЯМ НА НОГАХ НЕ ЧУВСТВУЮТСЯ)
https://t.me/anekdotbli
Сейчас, как никогда ранее, стало очевидным, что "родительское собрание" - от слова "собирать
https://t.me/anekdotbli
🆓 ПЕРВЫЙ БЕСПЛАТНЫЙ ВПН 🙏 Берите кому надо! 🤗
0₽ РУБЛЕЙ — НАВСЕГДА
Мой папаша был слесарем-алкашом, но мужик крепкий. Все, что он меня научил - бить в рыло. С девушками общаться не умел. Нашел себе одну, гулять пошли, мне хотелось ее удивить как-то, впечатлить. Говорю: "Видишь того бычару, давай я ему морду начищу?". Девушка не испугалась, а взяла меня на слабо. В итоге морду начистили мне, и пока я валялся в крови, девушка ушла в обнимку с тем чуваком, который разбил мне лицо(
htt…
Девушка, вы нам подходите, хотите сняться в рекламе "Колгейта"? А то у нас бобёр заболел...
https://t.me/anekdotbli
ЧЕБУРНЕТ 2030 РЕАЛЕН, но…
этот ВПН твоё спасение! Забери 3 дня бесплатно SUPRA VPN
- Ну чего, болезный? Тихо шифером шурша, крыша едет не спеша? - А вы точно наш психиатр
https://t.me/anekdotbli
🆓 ПЕРВЫЙ БЕСПЛАТНЫЙ ВПН 🙏 Берите кому надо! 🤗
0₽ РУБЛЕЙ — НАВСЕГДА
Д20. Я девственница. Так получилось что не было даже отношений, все постоянно в учебе. Сейчас общаюсь с парнем, и он говорит о том как приедет ко мне, зацелует, нападет и все расспрашивает какой бы я хотела первый секс. Говорит что любит меня, к слову мы не виделись ни разу. И вот что делать не знаю…
https://t.me/anekdotbli
Доктор, я умру?
— Мы все умрём.
— Я имел в виду сегодня.
— Не драматизируйте.
https://t.me/anekdotbli
🆓 ПЕРВЫЙ БЕСПЛАТНЫЙ ВПН 🙏 Берите кому надо! 🤗
0₽ РУБЛЕЙ — НАВСЕГДА
Купил детям шоколад.
Теперь у меня дети, шоколад и чувство вины.
https://t.me/anekdotbli
ЧЕБУРНЕТ 2030 РЕАЛЕН, но…
этот ВПН твоё спасение! Забери 3 дня бесплатно SUPRA VPN
П18. Кто-то в моём возрасте готовится к ЕГЭ, кто-то кайфует в шараге, а кто-то, как мои одноклассницы, залетают, а потом расписываются в ЗАГСе✌️
https://t.me/anekdotbli
Доктор, я умру?
— Мы все умрём. Вопрос в том, успеете ли вы заплатить за приём
https://t.me/anekdotbli
🆓 ПЕРВЫЙ БЕСПЛАТНЫЙ ВПН 🙏 Берите кому надо! 🤗
0₽ РУБЛЕЙ — НАВСЕГДА
Showing the 12 most recent of 428 posts we hold for @anekdotbli. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Posts edited after publishing
@anekdotbli edited 49 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
7 August 2026
Most recent edit
23 September 2026
Posts recorded as deleted after publishing
We recorded 2 posts on @anekdotbli as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
1 September 2026
Most recent seen missing
3 September 2026
Median time before seen missing
33 hours
Seen missing in the last 30 days
0
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@anekdotbli named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@casino named in 2 posts, 13 August 2026 – 15 August 2026
@luckybear named in 1 post, 20 August 2026 – 20 August 2026
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“МНЕ СТЫДНО...” (@anekdotbli), 28,635 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/anekdotbli.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.