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Channel

Вавилонская рыбка

@locaroundtheworld

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

5,728subscribers

+37 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001765974764
TypeChannel
Username@locaroundtheworld
Created13 September 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live5 November 2026
Measurements held25
Confirmed unchanged1 time, most recently 5 November 2026
On Telegramt.me/locaroundtheworld

Topic

Other / unclassifiable — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 71% 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.

Growth

5,6615,7415,7016 August 2026 — 5,691 subscribers6 August 2026 — 5,692 subscribers9 August 2026 — 5,687 subscribers12 August 2026 — 5,683 subscribers15 August 2026 — 5,675 subscribers19 August 2026 — 5,669 subscribers22 August 2026 — 5,666 subscribers25 August 2026 — 5,668 subscribers28 August 2026 — 5,670 subscribers31 August 2026 — 5,661 subscribers4 September 2026 — 5,675 subscribers9 September 2026 — 5,701 subscribers13 September 2026 — 5,699 subscribers18 September 2026 — 5,703 subscribers27 September 2026 — 5,715 subscribers5 October 2026 — 5,729 subscribers12 October 2026 — 5,735 subscribers15 October 2026 — 5,741 subscribers18 October 2026 — 5,733 subscribers20 October 2026 — 5,736 subscribers24 October 2026 — 5,735 subscribers27 October 2026 — 5,729 subscribers30 October 2026 — 5,732 subscribers2 November 2026 — 5,726 subscribers5 November 2026 — 5,728 subscribers5,7286 August 20265 November 2026
25 measurements spanning 91 days, net +37. 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 5,649–5,753 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)SubscribersChange
5 Nov 2026, 00:545,728+2
2 Nov 2026, 02:595,726-6
30 Oct 2026, 04:275,732+3
27 Oct 2026, 11:365,729-6
24 Oct 2026, 04:365,735-1
20 Oct 2026, 21:595,736+3
18 Oct 2026, 05:265,733-8
15 Oct 2026, 07:575,741+6
12 Oct 2026, 07:165,735+6
5 Oct 2026, 18:375,729+14
27 Sept 2026, 20:145,715+12
18 Sept 2026, 04:205,703+4
13 Sept 2026, 15:185,699-2
9 Sept 2026, 16:225,701+26
4 Sept 2026, 08:365,675+14
31 Aug 2026, 23:585,661-9
28 Aug 2026, 23:345,670+2
25 Aug 2026, 21:435,668+2
22 Aug 2026, 18:445,666-3
19 Aug 2026, 03:245,669first reading

Engagement

37 posts held, back to 11 July 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 9 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
25.8%
avg views ÷ 5,728 subscribers
Avg views / post
1,480
5 posts measured
Reaction rate
4.01%
reactions ÷ views · ER floor
Posts in window
5
of 37 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
WindowRolling 30 days · latest post in window 31 October 2026
Posts held37 (11 July 2026 – 31 October 2026)
Views total7,380
Reactions total296
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken4 Nov 2026, 19:45 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
1m 38s
Average length
25s

Measured directly from 4 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

2,636 reactions across 36 posts, in 19 distinct kinds. The most used accounts for 26.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤69126.2%
😁50319.1%
❤‍🔥46017.5%
🤣38714.7%
🔥2318.76%
🏆742.81%
👍682.58%
🍾481.82%
😱471.78%
👏351.33%
💯331.25%
🥰250.948%
💔90.341%
🤯80.303%
😈50.19%
💋40.152%
🤔40.152%
🐳20.076%
🤬20.076%

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 37 of the 37 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 2,693 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 37 most recent posts we hold, published 11 July 2026 to 31 October 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: 0 of 5 posts held from the last 30 days (0%) 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).

31 Oct 2026, 12:41 UTC680 views30 reactionsread 4 November 2026
Forwarded from @spinthewheel17Photo

Выпуск 15. Сопричастность Зачем искать своих людей в профессии, поддерживать общение и ходить на мероприятия, если не ради новых заказов? Нетворкинг мы уже обсуждали, поэтому в этот раз о другом: об ощущении цели и миссии, без которого работа быстро превращается в рутину, и о sanity check, когда нужно свериться с коллегами, что адекватно, а что нет. Заодно рассказали, как появились два подкаста и зачем переводчику …

❤19❤‍🔥6🔥4👍1

Signed Lena *Pingusya*

30 Oct 2026, 09:52 UTC≈1,310 views95 reactionsread 4 November 2026
Photo

Good news, everyone! Я ошиблась и мне это доказали) Я уже дважды писала о пазл-рогалике Blue Prince. Сначала о том, как эту игру, на мой взгляд, невозможно локализовать. Потом был коллаб-интервью с Nitablade, которая реально взялась за эту задачу. Ну а теперь мне пришла весть, что локализация готова и вышла на Стиме! Уже можно качать и оценивать результат. Мораль этой истории: в локализации нет ничего невозможного…

❤‍🔥68🏆14🍾7❤3🤔3

Signed Lena *Pingusya*

17 Oct 2026, 08:34 UTC≈1,570 views21 reactionsread 4 November 2026
Forwarded from @spinthewheel17Photo

Выпуск 14. Профдеформация На барабане выпала тема «Профдеформация». Выяснили, почему переводчику сложно просто наслаждаться оперой, если над сценой идут субтитры на двух языках, кто такие добраньские быки и при чём тут шахматы, а ещё зачем городу огромный билборд с надписью «cult». Обсудили, как к шестидесяти стать crazy parrot lady и что общего у танцевального номера в блестящих розовых костюмах с песней про фальш…

🔥9❤8🥰3😱1

Signed Lena *Pingusya*

15 Oct 2026, 13:41 UTC≈1,750 views125 reactionsread 4 November 2026
Photo

Не знаю, Дискорд, сложно сказать! А вот заголовки лучше все-таки согласовывать с основным текстом...

🤣79💯22😁16😈5😱2❤1

Signed Lena *Pingusya*

9 Oct 2026, 13:53 UTC≈2,070 views25 reactionsread 4 November 2026
Forwarded from @spinthewheel17Photo

Выпуск 13. Перевод и преподавание На этой неделе вернулись к раскручиванию барабана, и нам выпала тема, которую предложил подписчик: «Преподавание, когда ты переводчик». Обсудили распространённый миф: если знаешь язык, значит, можешь и переводить, и преподавать. Поговорили о peer-to-peer обучении и о том, где проходит граница между «учимся вместе» и обманом, особенно когда обучение платное. Рассказали, кто, где и ч…

❤‍🔥11❤7👏6😱1

Signed Lena *Pingusya*

7 Oct 2026, 07:02 UTC≈2,190 views114 reactionsread 4 November 2026
Photo

Пиксаровские мультфильмы в китайском прокате имеют приставку "Всеобщая Мобилизация" или ХХХ总动员, где XXX — название того или иного мультфильма. Все началось с Toy Story (1995), которую в китайском прокате назвали 玩具总动员 Wánjù zǒngdòngyuán (Всеобщая мобилизация игрушек). Странный выбор, но мы ранее с вами уже сталкивались с "теплыми убийцами", "империей хакеров", так что не нужно удивляться. Все же есть ниточки для эт…

❤54😁44🔥14👏2

Signed Lena *Pingusya*

30 Sept 2026, 15:41 UTC≈2,060 views64 reactionsread 4 November 2026
Photo

Меж тем, сегодня у меня двойной праздник - ведь сегодня ещё и Международный день подкастов. Отличный повод открыть для себя наш подкаст с Варей Васильевой "Крутите барабан!". Этот подкаст - парная импровизация на рандомные темы о взрослой жизни, работе и самореализации. Две ведущих, две разные точки зрения и разный опыт. А ещё у нас короткие выпуски и крутые джинглы. Подписывайтесь, если ещё не!

🍾35❤19❤‍🔥6💋2💔2

Signed Lena *Pingusya*

30 Sept 2026, 09:23 UTC≈2,670 views230 reactionsread 4 November 2026
Photo

Есть ощущение, что наша профессия за последние годы успела умереть раз восемь. Сначала её должны были убить машинный перевод, потом нейросети, потом ещё что-нибудь обязательно должно было убить окончательно. А мы всё ещё здесь. Просто каждый раз меняемся и находим новую сферу ответственности. Наверное, в этом и есть наша суперсила: переводчики удивительно хорошо умеют меняться вместе с профессией, осваивать новое и…

❤‍🔥150❤49🏆19👏6💯3🤣1😁1😱1

Signed Lena *Pingusya*

29 Sept 2026, 06:42 UTC≈1,920 views73 reactionsread 4 November 2026
Photo

В менеджерской ипостаси много работаю с Notion, в том числе делаю запись и транскрипцию \ суммаризацию всех важных звонков. Регулярно обнаруживаю в транскриптах вот этих челиков)) И хотя мысль о человечках, которые успевают все быстренько записать и отредачить, забавляет - на самом деле это всего лишь след данных, на которых обучалась LLM для распознавания речи. Подобный кейс с ДимаTormozok описан на Пикабу

😁51❤15👍5🤯2

Signed Lena *Pingusya*

26 Sept 2026, 07:02 UTC≈2,230 views28 reactionsread 4 November 2026
Forwarded from @spinthewheel17Photo

Выпуск 12. Неуспешный неуспех В этот раз барабан крутить не стали — тема вытекает из предыдущей сама собой. После успешного успеха говорим о неуспешном неуспехе. Обменялись историями неудач: потерянное «нет» в юридическом документе, убитая шутка в переводе сериала и гневное письмо от зрителя, а ещё несколько недель работы без выходных, которые закончились комом в горле и мыслями об инсульте. Обсудили, почему люди о…

❤‍🔥18👏6💔2❤1😱1

Signed Lena *Pingusya*

25 Sept 2026, 12:31 UTC≈2,020 views105 reactionsread 4 November 2026
Photo

В СПб обнаружен кофе для локализаторов

😁81❤20🤯4

Signed Lena *Pingusya*

22 Sept 2026, 13:17 UTC≈2,330 views20 reactionsread 4 November 2026
File

Прикольная преза про выбор вендоров для локализации от чешского коллеги Petr Čermoch

👍15❤5

Signed Lena *Pingusya*

Showing the 12 most recent of 37 posts we hold for @locaroundtheworld. 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.

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 7 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.

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

LinguoHunter | Вакансии для переводчиков
@linguohunter · 25,446
Telegram ranks this channel #20 of 92 here — alongside 91 others — read 14 September 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 5 November 2026 — this entry's latest reading, not the date you are reading this.

“Вавилонская рыбка” (@locaroundtheworld), 5,728 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/locaroundtheworld.

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.