International news — 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 89% 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
26 measurements spanning 95 days, net +608. 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 5,442–6,794 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)
Subscribers
Change
10 Nov 2026, 16:46
6,388
-20
7 Nov 2026, 01:17
6,408
-37
4 Nov 2026, 08:35
6,445
-2
1 Nov 2026, 04:01
6,447
-46
29 Oct 2026, 09:28
6,493
-41
26 Oct 2026, 09:36
6,534
-5
23 Oct 2026, 10:07
6,539
-24
20 Oct 2026, 11:05
6,563
-25
17 Oct 2026, 02:30
6,588
-24
13 Oct 2026, 22:20
6,612
-2
8 Oct 2026, 23:40
6,614
-24
2 Oct 2026, 07:37
6,638
+62
16 Sept 2026, 15:18
6,576
+121
12 Sept 2026, 23:58
6,455
+3
8 Sept 2026, 19:39
6,452
+145
3 Sept 2026, 14:19
6,307
+168
30 Aug 2026, 22:46
6,139
+342
27 Aug 2026, 20:25
5,797
+199
24 Aug 2026, 16:45
5,598
-51
20 Aug 2026, 23:55
5,649
first reading
Engagement
86 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 15 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
2.08%
avg views ÷ 6,388 subscribers
Avg views / post
133
43 posts measured
Reaction rate
1.27%
reactions ÷ views · ER floor
Posts in window
43
of 86 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 23 of 43 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 7 November 2026
Posts held
86 (5 August 2026 – 7 November 2026)
Views total
5,709
Reactions total
42
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 10:36 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 44s
Average length
26s
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
93 reactions across 47 posts, in 10 distinct kinds. The most used accounts for 31.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🤔
29
31.2%
👍
23
24.7%
🔥
14
15.1%
👏
10
10.8%
🤯
6
6.45%
❤
4
4.30%
👎
3
3.23%
🎉
2
2.15%
🍓
1
1.08%
🤡
1
1.08%
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 48 of the 86 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 93 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 86 most recent posts we hold, published 5 August 2026 to 7 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: 0 of 43 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).
🖤 Топ-10 нефтяных гигантов мира
Представляем карту крупнейших нефтегазовых бассейнов планеты по суточной добыче. Нефть — это не просто ресурс, а геополитический рычаг и двигатель мировой экономики.
Лидеры добычи (млн баррелей в сутки):
🇸🇦 Восточная Саудовская Аравия — 9,3 млн б/с
🇺🇸 Пермский бассейн (США) — 6,6 млн б/с
🇨🇳 Западная Сибирь (Россия) — 6 млн б/с
🇨🇦 Альберта (Канада) — 4,1 млн б/с
🇮🇷 Ирак / Иран / Кувейт…
Сколько времени уходит на поиск работы в разных странах? 💼🌍
По данным рейтинга 42 стран, медианное время поиска работы в мире составляет около 4,7 месяца. Но разброс огромный: где-то работу находят за несколько недель, а где-то поиск растягивается больше чем на год.
Где ищут быстрее всего:
- 🇲🇽 Мексика — 1,2 месяца, самый быстрый результат в рейтинге.
- 🇺🇸 США — 2,2 месяца.
- 🇨🇦 Канада — 2,4 месяца.
- Около 2,5 ме…
🇺🇸 Госдолг США — 123% ВВП: максимум с пандемии
Государственный долг США достиг исторического максимума в $40,6 трлн. Только за октябрь он вырос на $422 млрд. Отношение долга к ВВП поднялось до 123% — это самый высокий уровень с 2020 года, периода пандемийных стимулов.
Проще говоря: американская экономика за год производит товаров и услуг примерно на $100, а государство уже должно $123. И разрыв продолжает расти.
О…
Зачем Трампу нужна была война с Ираном? 🛢️
Ровно затем же, зачем Бушу нужна была иракская кампания: война создаёт дефицит, дефицит поднимает цены, а высокие цены превращаются в прибыль — причём не для всех, а для тех, кто добывает, перерабатывает и продаёт нефть.
По оценке *The New York Times*, основанной на данных S&P Global Market Intelligence и FactSet, более 50 крупных американских нефтяных и нефтеперерабатываю…
Как фейковое собеседование привело к краже $6,3 млрд у Binance 💼💻
Самая дорогая киберкража в истории могла начаться с обычного приглашения на работу. Разработчик Binance прошёл видеособеседование, пообщался с «генеральным директором» в мессенджере, получил тестовое задание — и скачал на рабочий компьютер заражённый код.
Внутри этого кода была вредоносная программа. Она проникла в инфраструктуру биржи, обошла защитн…
Огуречный стандарт 🥒🌊
Пока экономисты обсуждают альтернативы доллару и SWIFT, мексиканские картели нашли свой способ расчётов с китайскими партнёрами — морскими огурцами.
Да, это животные. Финансовым инструментом они стали чуть позже.
По данным *Foreign Policy*, китайские преступные группы принимают морских огурцов вместо денег. В Китае это дорогой деликатес: отдельные виды могут стоить до $3 000 за килограмм.
Сх…
Showing the 12 most recent of 86 posts we hold for @EconRUDN. 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
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 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.
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.
RUDN student’s life @RUDNstudentslife · 30,166 Telegram ranks this channel #39 of 73 here — alongside 72 others — read 8 September 2026
Книжный день @knijnij_den · 45,999 Telegram ranks this channel #79 of 94 here — alongside 93 others — read 27 August 2026
This channel appears in 2 seed channels' Telegram-generated recommendation lists 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“РУДН: Экономика объединяет” (@EconRUDN), 6,388 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/EconRUDN.
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.