Education — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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
58 measurements spanning 90 days, net +1,412. 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 28,520–30,356 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)
Subscribers
Change
3 Nov 2026, 15:26
30,144
+7
2 Nov 2026, 13:16
30,137
+16
1 Nov 2026, 13:08
30,121
+8
31 Oct 2026, 13:17
30,113
+12
30 Oct 2026, 14:00
30,101
+6
29 Oct 2026, 15:41
30,095
+22
28 Oct 2026, 16:10
30,073
+18
27 Oct 2026, 18:57
30,055
+32
26 Oct 2026, 17:07
30,023
+54
25 Oct 2026, 14:01
29,969
+8
24 Oct 2026, 13:06
29,961
+19
23 Oct 2026, 16:36
29,942
+4
22 Oct 2026, 14:47
29,938
+13
21 Oct 2026, 11:07
29,925
+1
20 Oct 2026, 08:56
29,924
+26
19 Oct 2026, 05:55
29,898
+32
18 Oct 2026, 09:11
29,866
-6
17 Oct 2026, 10:58
29,872
+17
16 Oct 2026, 07:59
29,855
+15
15 Oct 2026, 09:55
29,840
first reading
Engagement
290 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 145 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.63%
avg views ÷ 30,144 subscribers
Avg views / post
2,900
127 posts measured
Reaction rate
1.10%
reactions ÷ views · ER floor
Posts in window
127
of 290 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 3 November 2026
Posts held
290 (3 August 2026 – 3 November 2026)
Views total
368,840
Reactions total
4,061
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Nov 2026, 11:14 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
32m 14s
Average length
2m 56s
Measured directly from 11 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
10,685 reactions across 285 posts, in 12 distinct kinds. The most used accounts for 45.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
4,812
45.0%
🔥
1,831
17.1%
👏
1,238
11.6%
custom 5251407807890100867
801
7.50%
🥰
580
5.43%
😍
435
4.07%
👍
413
3.87%
custom 5384240400347208864
264
2.47%
🙏
120
1.12%
💯
86
0.805%
custom 5427273773629875247
53
0.496%
🤩
52
0.487%
Custom emoji. 3 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 290 of the 290 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 10,836 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 290 most recent posts we hold, published 3 August 2026 to 3 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.
#студ_жизнь
⚖️ Открыта регистрация на FinLex 2027
Приглашаем студентов юридических факультетов российских вузов на IV Межвузовский студенческий конкурс по проблемам правового регулирования финансовых рынков в России.
FinLex дает возможность проверить знания финансового права, развить навыки юридической аргументации и выступить в модельном судебном заседании.
Кто может участвовать?
🟦студенты 3–4 курсов бакалавриат…
#студ_жизнь
Большие победы начинаются с первого хода...
🔵Твой ход! День настольных игр в МГИМО
📆 3 ноября, 16:00
📍 Шахматная гостиная КЦ
В МГИМО состоится традиционный День настольных игр — мероприятие, где каждый сможет почувствовать командный дух и разделить радость побед.
🔹Участников ждут разнообразные настольные игры, угощения и общение в дружеской атмосфере. Присоединиться могут все желающие вне зависимост…
#ДПО_мгимо
🎓 Управление НКО: новая программа МГИМО
Факультет МБ приглашает студентов 3–4 курсов бакалавриата и 1–2 курсов магистратуры на программу профессиональной переподготовки «Управление некоммерческими организациями».
Условия обучения:
⭐️Продолжительность: 3 семестра
⭐️Формат: гибридный (очно и онлайн)
⭐️Начало занятий: ноябрь 2026 года
Слушатели программы научатся развивать НКО, привлекать финансирование…
#факультеты_мгимо
🔵 МГИМО в деталях – новости факультетов и институтов
От научных дискуссий до культурных проектов – факультеты и институты МГИМО формируют насыщенную университетскую повестку.
▫️ Факультет МО
🟦Закрытие V Научно-образовательного и культурного фестиваля «Неделя МО» 2026
🟦Панельная дискуссия «Think or tank? Международники в условиях неопределенности и как с этим справляться»
🟦Лекция В.Воротникова «…
#сегодня_мгимо
Доброе утро, МГИМО!
📆 Сегодня в Университете:
🔵Старт программы повышения квалификации «Современные подходы и новые технологии в преподавании перевода в эпоху искусственного интеллекта» | онлайн-формат
🔵Международный день торговли 2026 | весь день | кластер «Ломоносов»
📰 Новости:
⚡️Эмин Агаларов стал первым гостем нового проекта Alumni Open Talk в МГИМО
⚡️ Заседание Национального клуба Заслуженных …
#анонсы_мгимо
🟦🟦 Все главные события МГИМО предстоящей недели:
🏷️2 ноября, понедельник
🔵Старт программы повышения квалификации «Современные подходы и новые технологии в преподавании перевода в эпоху искусственного интеллекта» | онлайн-формат
🔵Международный день торговли 2026 | весь день | кластер «Ломоносов»
🏷️ 3 ноября, вторник
🔵Открытие выставки РГХПУ имени С.Г.Строганова | 14:00
🔵Open Talk Д.Джафаровой | 16:…
🔹🔹🔹 с А.В.Торкуновым: Университеты стран БРИКС – новая архитектура будущего
БРИКС – это не только взаимодействие в политике, экономике и торговле. Это ещё и обмен знаниями, совместные исследования и подготовка кадров для общего будущего. Одним из главных инструментов такого сотрудничества становятся университеты.
В новом выпуске программы – академическое сотрудничество стран БРИКС, подготовка специалистов для расту…
#наука_мгимо
🔵 Человек и ИИ: кто задает правила?
27 ноября в рамках НЦМУ «Ценностный суверенитет» состоится научная конференция, посвященная правовым, этическим и гуманитарным вопросам цифровой трансформации.
Ключевые темы конференции:
🔵защита прав, персональных данных и автономии личности
🔵 этические риски ИИ и границы человеческого контроля
🔵влияние цифровых технологий на образование, культуру и самостоятельност…
#студ_жизнь
🔵 Живое наследие: открытие выставки в МГИМО
📆 3 ноября, 14:00
📍 Малая сцена КЦ
В МГИМО состоится торжественное открытие выставки «Строгановский культурный код в сохранении наследия России. Дизайн и народные художественные промыслы».
🔹Совместный проект МГИМО и РГХПУ им.С.Г. Строганова приурочен ко Дню народного единства и посвящен сохранению культурного наследия России, развитию народных художественных…
#ДПО_мгимо
💻 Как преподавать перевод в эпоху ИИ?
📆 2-20 ноября
📍 Онлайн формат
Готовый перевод еще не раскрывает умения студента работать с контекстом, замечать ошибки и обосновывать решения...
Этим вопросам посвящена программа повышения квалификации Школы бизнеса МГИМО «Современные подходы и новые технологии в преподавании перевода в эпоху искусственного интеллекта».
В программе:
🟦возможности и ограничения нейр…
❤9👍6😍5🔥4custom 52514078078901008671
Showing the 12 most recent of 290 posts we hold for @mgimo_university. 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
@mgimo_university edited 11 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
3 September 2026
Most recent edit
3 November 2026
Posts recorded as deleted after publishing
We recorded 1 post on @mgimo_university 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
5 October 2026
Most recent seen missing
5 October 2026
Median time before seen missing
3 days
Seen missing in the last 30 days
1
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 81 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 9 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
САРДАРЯН @sardaryanh · 49,219 Telegram ranks this channel #31 of 90 here — alongside 89 others — read 25 August 2026
Белый Филин @whitefilin · 22,768 Telegram ranks this channel #63 of 94 here — alongside 93 others — read 20 September 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.
Cross-platform identity — Wikidata
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 3 November 2026 — this
entry's latest reading, not the date you are reading this.
“МГИМО. Официально” (@mgimo_university), 30,144 subscribers as measured 3 November 2026. Telegram Register, tgregister.com/channel/mgimo_university.
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.