🎉 Поздравляем с юбилеем профессора-консультанта кафедры «Экономика и финансы» Валентину Ивановну Будину! Желаем успехов и благополучия, Валентина Ивановна! 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤3

Channel
@pnzgu
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Telegram's recommendations · Cross-platform identity · Cite this entry
7,832subscribers
+46 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001316274536 |
|---|---|
| Type | Channel |
| Username | @pnzgu |
| Description | Главные события Пензенского государственного университета |
| Created | 14 November 2019 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 1 November 2026 |
| Measurements held | 23 |
| Confirmed unchanged | 1 time, most recently 1 November 2026 |
| On Telegram | t.me/pnzgu |
Local community — 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 83% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 1 Nov 2026, 19:36 | 7,832 | -12 |
| 29 Oct 2026, 09:36 | 7,844 | -9 |
| 26 Oct 2026, 17:54 | 7,853 | -6 |
| 23 Oct 2026, 21:10 | 7,859 | -3 |
| 20 Oct 2026, 22:36 | 7,862 | -9 |
| 17 Oct 2026, 12:46 | 7,871 | -9 |
| 14 Oct 2026, 22:11 | 7,880 | -19 |
| 11 Oct 2026, 23:55 | 7,899 | -17 |
| 27 Sept 2026, 07:17 | 7,916 | -18 |
| 17 Sept 2026, 16:39 | 7,934 | +3 |
| 13 Sept 2026, 20:16 | 7,931 | -2 |
| 10 Sept 2026, 05:35 | 7,933 | -5 |
| 1 Sept 2026, 08:52 | 7,938 | +7 |
| 29 Aug 2026, 04:24 | 7,931 | +26 |
| 25 Aug 2026, 18:43 | 7,905 | +30 |
| 22 Aug 2026, 14:33 | 7,875 | +18 |
| 18 Aug 2026, 22:24 | 7,857 | +4 |
| 16 Aug 2026, 08:45 | 7,853 | -5 |
| 12 Aug 2026, 15:34 | 7,858 | +37 |
| 9 Aug 2026, 17:23 | 7,821 | first reading |
80 posts held, back to 29 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 22 pages of Telegram’s post history, 20 posts per page.
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 4 of 6 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 November 2026 |
|---|---|
| Posts held | 80 (29 July 2026 – 3 November 2026) |
| Views total | 5,046 |
| Reactions total | 14 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Nov 2026, 23:44 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.
Lifetime counters from Telegram’s own channel header, read 3 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.
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.
621 reactions across 73 posts, in 22 distinct kinds. The most used accounts for 53.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 329 | 53.0% | |
| 👍 | 65 | 10.5% | |
| 🎉 | 52 | 8.37% | |
| 🕊 | 30 | 4.83% | |
| ❤🔥 | 26 | 4.19% | |
| 🔥 | 26 | 4.19% | |
| 🙏 | 20 | 3.22% | |
| 🥴 | 17 | 2.74% | |
| 👏 | 12 | 1.93% | |
| 😁 | 8 | 1.29% | |
| 🤓 | 8 | 1.29% | |
| 😍 | 6 | 0.966% | |
| 😢 | 6 | 0.966% | |
| 🤔 | 5 | 0.805% | |
| 👀 | 2 | 0.322% | |
| 😭 | 2 | 0.322% | |
| 🥱 | 2 | 0.322% | |
| 👌 | 1 | 0.161% | |
| 💯 | 1 | 0.161% | |
| 😎 | 1 | 0.161% | |
| 2 further kinds | 2 | 0.322% |
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 78 of the 80 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 650 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 80 most recent posts we hold, published 29 July 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.
🎉 Поздравляем с юбилеем профессора-консультанта кафедры «Экономика и финансы» Валентину Ивановну Будину! Желаем успехов и благополучия, Валентина Ивановна! 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤3
🎙 Студенты и выпускники ПГУ поют в межнациональном ансамбле «Мелодия Дружбы» Ансамбль «Мелодия Дружбы» объединяет представителей разных народов Пензенской области. Коллектив уже известен такими выступлениями и клипами, как «Матушка» («Матушка-земля»), «День Победы» и «Моя Россия». Руководитель ансамбля — выпускница ПГУ 2025 года, руководитель вокального ансамбля «Мизгель» Мениря Тинчурина говорит: У нас поют предст…
❤🔥3❤1🔥1
Чем запомнился визит Заместителя Министра науки и высшего образования РФ Ольги Викторовны Петровой в Пензенский государственный университет — в видео Дениса Никитина.
😍5
В Пензенском государственном университете комната матери и ребёнка открылась почти год назад. Была рада посетить комнату и убедиться в том, насколько комфортные условия созданы для семей студентов и преподавателей. Прямо из комнаты вместе с коллегами и детишками ПГУ вышли на видеосвязь с БГТУ «Военмех» имени Д.Ф. Устинова, где новое семейное пространство открылась как раз сегодня – пространство заботы и воспитания б…
Заместитель министра науки и высшего образования Ольга Викторовна Петрова, с которой мы сегодня обсуждали социальные проекты для студентов, дала высокую оценку ПГУ — университету, который я называю локомотивом высшего образования Пензенской области. Она отметила, что Пензенский государственный университет очень достойно представляет родной регион. ⚪️ При этом мы видим большой потенциал для дальнейшего движения впере…
❤1
Благодарю руководство, преподавателей и студентов Пензенского государственного университета, а также коллег из правительства Пензенской области за тёплый приём! Вместе с коллегами почтили память героев Великой Отечественной войны. Открыли в вузе новое студенческое пространство «Простор», тепло пообщались со студентами. Спасибо ребятам за диалог! Совсем скоро стартуем на площадке ПГУ региональное совещание по апроба…
🏛 Студенты ПГУ на каникулах побывали с большой экскурсией в Санкт-Петербурге В августе 150 активистов, участников творческих, общественных объединений, волонтёров и спортсменов — посетили музеи, дворцовые комплексы и Петергоф в день 305-летия запуска фонтанов. Поездка организована в рамках традиции поощрять успешных студентов. 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤7❤🔥3🎉1🔥1🤔1😍1
🏡 ПГУ стал площадкой работы федеральных экспертов «Семейной столицы России» В рамках второго этапа конкурса эксперты посетили ПГУ. В ноябре 2025 года в вузе открыли комнату матери и ребёнка, в университете зарегистрировано более 100 студенческих семей, свыше 30 из них с детьми. 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤🔥2
🎓 На программы магистратуры в ПГУ зачислены более 750 студентов 25–26 августа изданы приказы о зачислении 759 человек: 327 на бюджет, 432 на платные места. Самыми популярными стали направления в сфере ИТ, ИИ, психологии и биологии. Среди поступивших есть граждане Марокко, Индии, Китая, Туниса и Йемена. 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤5👌1🥱1😨1
🏫 Августовские форумы в Пензе стали диалоговой площадкой для педагогов в преддверии нового учебного года 18–20 августа прошёл областной форум, 25 августа — городской. Представители ПГУ выступили с докладами об итоговой аттестации по литературе, предметных дефицитах и стратегиях подготовки к экзаменам. 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤2
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❤8👍1
🧠 Приглашаем учёных ПГУ к участию в Национальной премии «Лидеры искусственного интеллекта — 2026» Четвёртая Национальная премия открыла приём заявок. Для учёных предусмотрены номинации «Молодой учёный» и новая номинация «Первая публикация» для первых авторов значимых исследований. Участие бесплатное, заявки принимаются до 1 октября. 🔗 Читайте на сайте ➡️ Подпишитесь — ПГУ в MAX
❤3👍1
Showing the 12 most recent of 80 posts we hold for @pnzgu. 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.
@pnzgu edited 1 post 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.
We recorded 1 post on @pnzgu 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 8 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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.
This channel appears in 14 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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.
| Label | Penza State University |
|---|---|
| Description | Russian university |
| X / Twitter | @PenzaGU |
| Official site | http://www.pnzgu.ru/ |
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 1 November 2026 — this entry's latest reading, not the date you are reading this.
“ПГУ | Официально” (@pnzgu), 7,832 subscribers as measured 1 November 2026. Telegram Register, tgregister.com/channel/pnzgu.
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.