Telegram RegisterThe public register of Telegram

Channel

Уголок кинопереводчика

@AVTranslationcorner

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

741subscribers

-1 since we began measuring on 9 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1001210415665
TypeChannel
Username@AVTranslationcorner
CreatedBetween 1 March 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live9 August 2026
Measurements held2
Confirmed unchanged1 time, most recently 9 August 2026
On Telegramt.me/AVTranslationcorner

Growth

741742741.59 Aug 2026, 08:31 — 742 subscribers9 Aug 2026, 14:16 — 741 subscribers9 Aug 2026, 08:319 Aug 2026, 14:16
2 measurements taken within a single day, net -1. 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 741–742 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
9 Aug 2026, 14:16741-1
9 Aug 2026, 08:31742first reading

Engagement

15 posts held, back to 12 March 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
15.9%
avg views ÷ 741 subscribers
Avg views / post
118
2 posts measured
Reaction rate
5.88%
reactions ÷ views · ER floor
Posts in window
2
of 15 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. It is computed over the 1 of 2 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 23 July 2026
Posts held15 (12 March 202623 July 2026)
Views total236
Reactions total7
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 08:31 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

Video runtime
8s
Average length
8s

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

173 reactions across 13 posts, in 8 distinct kinds. The most used accounts for 32.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥5632.4%
5028.9%
😁3218.5%
👍169.25%
💯105.78%
👏52.89%
🎉21.16%
🤔21.16%

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 13 of the 15 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 173reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 12 March 2026 to 23 July 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

23 Jul 2026, 10:35 UTC117 viewsread 9 August 2026

И с нашей укладкой ...

Signed Ivan Borshchevsky

23 Jul 2026, 10:35 UTC119 views7 reactionsread 9 August 2026
Forwarded from @voiceactorsonlinePhoto

Вышел фильм якутских кинематографистов с нашей озвучкой в закадре

🔥7

Signed Ivan Borshchevsky

17 May 2026, 14:13 UTC≈1,300 views14 reactionsread 9 August 2026
Photo

Ни дня без строчки. На днях вышла моя монография, в которой я очень подробно анализирую звукофильм "Отец солдата" с позиций лингвистики. Это произведение постоянно упоминается в статьях и пособиях по тифлокомментированию, и очень жаль, что до сего дня оно никем не только не анализировалось, но даже и не цитировалось. Что ж, нам не впервой идти туда, где не ступала нога человека 😉 Надеюсь, эта публикация будет интерес

9👍3🎉2

Signed Ivan Borshchevsky

15 May 2026, 13:01 UTC325 views13 reactionsread 9 August 2026

НАСТОЯЩЕЕ ВРЕМЯ в тифлокомментировании является своего рода "священной коровой" - все говорят, что в тифлокомментарии прошедшее время недопустимо, но... почти все его употребляют (даже не замечая этого). Пришло ли время "сбросить" настоящее время с пьедестала? Я провёл корпусное исследование (39 ч 15 минут видео) фильмов разных жанров, выписал все глагольные формы и посчитал, сколько из них стоит в прошедшем времени.

🔥121

Signed Ivan Borshchevsky

8 May 2026, 12:52 UTC249 views7 reactionsread 9 August 2026

#пронаспишут Очень рад был поучаствовать в программе обучения спортивных комментаторов инклюзивным видам перевода вместе с коллегами - крутейшими специалистами в области тифлокомментирования. Наконец все этапы обучения завершены, и теперь репортажи со спортивных соревнований станут более доступными для болельщиков с особыми потребностями. #заметкикинопереводчика #мамаявтелевизоре #локалфильм https://spartak.com/med

🔥7

Signed Ivan Borshchevsky

30 Apr 2026, 12:15 UTC362 views25 reactionsread 9 August 2026
Photo

Мы?

💯10🔥7😁71

Signed Ivan Borshchevsky

26 Apr 2026, 20:41 UTC400 views7 reactionsread 9 August 2026

Вообще с этими программами забавная ситуация. Любит народ громкий пиар, а результата ноль. Ещё год назад прочитал я в тырнетах, что школьники (!!!) создали программу для тифлокомментирования видео. Прошёл год... но кроме той заметки в соцсетях и пресс-релиза в СМИ так ничего не появилось. Ни на сайте образовательного центра, ни в ВК (где мини-приложение собирались разместить). Пришлось самому экспериментировать 🤣

5🤔2

Signed Ivan Borshchevsky

26 Apr 2026, 20:19 UTC281 views8 reactionsread 9 August 2026

Продолжаю баловаться программированием. Теперь моя ещё сырая программка доступна в интернете на hugging face. ВАЖНО: некоторые провайдеры блокируют этот сайт, хотя другие - нет. Но всё же. Вот ссылка: https://huggingface.co/spaces/IvanBorsh/video-assistant Что и как делать? 1. Бегунком устанавливаем интервал, через который программа будет описывать видео. На скриншоте стоит 4 секунды. 2. Загружаем видео. Пока я рабо

8

Signed Ivan Borshchevsky

25 Apr 2026, 05:31 UTC226 views12 reactionsread 9 August 2026
Video

ТИФЛОКОММЕНТАРИЙ ВИДЕО ОТ НЕЙРОСЕТИ Все балуются программированием - и я решил побаловаться. 😉Вчера вечером написал код, который позволит составлять и озвучивать тифлокомментарии к видео. Программка, конечно, сырая. Путает часы и секунды 😄 Нужно дорабатывать. Но, в целом, описание более или менее точное. Первый блин почти не комом. #заметкикинопереводчика #локалфильм #AI #тифлокомментирование

🔥83😁1

Signed Ivan Borshchevsky

6 Apr 2026, 08:54 UTC292 views15 reactionsread 9 August 2026

Вместе с коллегой и партнёром, режиссёром дубляжа Артёмом Маликовым, выходим на новый уровень! ☝ Мы с Евгенией Шуваловой закончили перевод под дубляж нового фильма. И только потом узнали, что озвучиваться он будет на Мосфильме.😉 Но и сам процесс работы над переводом отличался от обычного. Владимир Аркадьевич Ерёмин, официальный голос Аль Пачино в русском дубляже, очень тщательно работает над ролью. Обычно актёры дуб

10👏5

Signed Ivan Borshchevsky

6 Apr 2026, 08:54 UTC315 views31 reactionsread 9 August 2026
Forwarded from @youvoiceactingPhoto

Сегодня работал на Мосфильме в качестве режиссера дубляжа. Это новая ветвь в моей профессиональной деятельности. Мне посчастливилось поработать с Мэтром, Мастером дубляжа - Владимиром Аркадьевичем Ерёминым, который дублировал самого Аль Пачино. Владимир Аркадьевич является официальным голосом в российском прокате. Для меня это был незабываемый опыт и восторг! Старая школа! Какая детальная работа с текстом, с синхрон

13👍11🔥7

Signed Ivan Borshchevsky

Showing the 12 most recent of 15 posts we hold for @AVTranslationcorner. 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.

Citation-graph rank

Citation-graph rank — 976,572 of 1,345,403entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

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 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.

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 9 August 2026 — this entry's latest reading, not the date you are reading this.

“Уголок кинопереводчика” (@AVTranslationcorner), 741 subscribers as measured 9 August 2026. Telegram Register, tgregister.com/channel/AVTranslationcorner.

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.