Literature — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 74% 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.
Views per post sit far above this size band
35,600 average views per post against 35,872 subscribers — an engagement rate of 99.2%. Across the 8,315 registered channels in the same cohort — 31,623–99,997 subscribers, posting mainly in Russian — the middle half sit between 5.08% and 20.8%, with a median of 10.5%.
What this was computed from
Window
30 days (6 October 2026 – 5 November 2026)
Posts measured
135 of 135 published in the window (0 exact, 135 rounded by Telegram)
Views totalled
4,804,580
Mature posts only
99.2% over 135 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 5 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.
Growth
59 measurements spanning 93 days, net +855. 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 33,386–46,187 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 59
Measured (UTC)
Subscribers
Change
6 Nov 2026, 14:26
35,859
-13
5 Nov 2026, 10:59
35,872
-10
4 Nov 2026, 10:44
35,882
-3
3 Nov 2026, 07:37
35,885
-5
2 Nov 2026, 05:07
35,890
-2
1 Nov 2026, 01:21
35,892
+3
31 Oct 2026, 04:16
35,889
+1
30 Oct 2026, 03:05
35,888
+19
29 Oct 2026, 00:17
35,869
+22
26 Oct 2026, 23:08
35,847
+1
25 Oct 2026, 22:17
35,846
+14
24 Oct 2026, 23:27
35,832
+25
23 Oct 2026, 23:39
35,807
-13
22 Oct 2026, 23:10
35,820
-21
21 Oct 2026, 21:17
35,841
+17
20 Oct 2026, 17:31
35,824
+41
19 Oct 2026, 14:15
35,783
-5
18 Oct 2026, 15:46
35,788
+23
17 Oct 2026, 19:09
35,765
+3
16 Oct 2026, 21:56
35,762
first reading
Engagement
421 posts held, back to 3 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 167 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
95.7%
avg views ÷ 35,859 subscribers
Avg views / post
34,300
133 posts measured
Reaction rate
0.249%
reactions ÷ views · ER floor
Posts in window
133
of 421 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 6 November 2026
Posts held
421 (3 August 2026 – 6 November 2026)
Views total
4,562,270
Reactions total
11,339
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 17:31 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
≈2,250
Videos
≈37
Links
≈3,140
Lifetime counters from Telegram’s own channel header, read 6 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
51s
Average length
51s
Measured directly from 1 video 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
35,962 reactions across 406 posts, in 7 distinct kinds. The most used accounts for 47.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
17,042
47.4%
💔
7,189
20.0%
🤡
3,632
10.1%
👍
2,759
7.67%
👾
2,684
7.46%
🥴
2,216
6.16%
👎
440
1.22%
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 421 of the 421 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 37,491 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 421 most recent posts we hold, published 3 August 2026 to 6 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 19 of 133 posts held from the last 30 days (14.3%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Пропавшую картину Джорджии О'Кифф нашли в шкафу за шубами
Едва ли вы найдете в платяном шкафу Нарнию, но есть небольшой шанс обнаружить там шедевр живописи на три миллиона долларов. Именно это случилось с одной американкой, когда она помогала по дому своей пожилой тете.
Тетя, разумеется, о картине знала: когда-то давно, в 1960-х, она получила ее в подарок от матери (в тот момент работа О'Кифф стоила всего 3800 долл…
Netflix не может отпустить «Очень странные дела». Ждите приквел
Вышел тизер сериала «Иные миры» — предыстории «Очень странных дел». В ролике не показали примерно ничего: только велосипед с портативным радиоприемником, очередную закрытую территорию и странную молнию в небе. «До Хоукинса был Мэрион», — сказано в лаконичном описании. Мэрион — это, видимо, очередной городок, где творятся необъяснимые вещи.
Действие при…
Мертвеца принимают за арт-объект в трейлере «Галеристки» с Натали Портман и Дженной Ортегой
Самый потешный трейлер, который вы увидите на этой неделе. Режиссерка Кэти Янь, снявшая кинокомикс «Хищные птицы» для DC и номинированный на «Эмми» эпизод «Наследников», поставила черную комедию о современном искусстве.
Сюжет такой. Героиня Натали Портман, галеристка Полина Полински, готовилась представить стенд на междунаро…
«Киру всё заебало» Сергея Лебеденко — новый роман издательства «Медузы». Его уже можно заказать!
Две хорошие новости: мы продолжаем выпускать художественную литературу и сегодня в художественной линейке нашего издательства стало одним романом больше. Книга называется «Киру всё заебало», ее написал Сергей Лебеденко, журналист, редактор, автор книжного телеграм-канала «Книгижарь». Главная героиня романа — 30-летняя уч…
Сериал «Айда» о казанской банде не вышел в срок. Его критиковали депутат и полковник МВД
Привет, это Антон. Сегодня ночью зрители онлайн-кинотеатра Start ждали большую премьеру: криминальный сериал «Айда» о казанской банде «Тяп-ляп».
Эта банда возникла в семидесятые годы и, по всей видимости, положила начало «казанскому феномену» — тех самых молодежных группировок, о которых рассказывает сериал «Слово пацана». Прое…
Боб Дилан встретился с папой Львом XIV. Сложно делать вид, что у исторической фотографии нет мемного потенциала
Pitchfork, например, публикует заголовок: «Боб Дилан (в худи) встретился с папой». А GQ и вовсе язвят, что нобелевский лауреат пришел на встречу «в костюме Тимоти Шаламе». Злые люди!
Встреча прошла в Ватикане 4 ноября. Сейчас идет европейское турне 85-летнего Дилана — между миланским и римскимшоу он решил…
Обозреваем порно! Ну ладно, это кликбейт. Просто рассказываем о карьере Тинто Брасса
4 ноября умер Тинто Брасс — итальянский режиссер, снявший «Калигулу» и множество других эротических фильмов. Предположу, что многие из вас могли их увидеть в ночном эфире НТВ или РЕН-ТВ.
На самом деле его история куда сложнее: в свое время он работал во Французской синематеке, это повлияло на его видение киноискусство прямым образо…
«Рокки — это я» — фильм о съемках «Рокки» и бедственном положении Сильвестра Сталлоне. Художественный! И обнадеживающий
Привет, это Софья. Для начала поделюсь рецензией Антона Долина на фильм «Рокки — это я» (с 19 ноября в российском прокате). Судя по тексту, картина о съемках знаменитой боксерской драмы устроена очень просто, в ней нет никакой сложносочиненной морали: терпение и труд все перетрут. Такой вывод.
И …
В Германии известный архитектор построил музей для одной-единственной картины
Британский архитектор и притцкеровский лауреат Дэвид Чипперфилд — автор реконструкции Нового музея в Берлине — спроектировал павильон для частного музея Würth 2 в городке Кюнцельзау, где будут показывать только одну картину.
Расположенное рядом основное здание Würth 2 тоже построено по проекту Чипперфилда: смотрите, как оно изящно утоплен…
❤169👍15🥴6👾5
Signed Антон Хитров
Showing the 12 most recent of 421 posts we hold for @plottwist_m. 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
@plottwist_m edited 5 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
13 August 2026
Most recent edit
4 November 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 12 registered channels — 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.
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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Plot” (@plottwist_m), 35,859 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/plottwist_m.
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.
