Posted without readable text
custom 52356134908607979453custom 52290588983207254012custom 52584575113751750531

Channel
@universityNeimark
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
715subscribers
+22 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003027765683 |
|---|---|
| Type | Channel |
| Username | @universityNeimark |
| Created | Between 1 August 2025 and 31 October 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 14 August 2026 |
| On Telegram | t.me/universityNeimark |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 10:07 | 715 | +14 |
| 7 Aug 2026, 20:54 | 701 | +8 |
| 6 Aug 2026, 22:17 | 693 | first reading |
13 posts held, back to 28 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 1 pageof 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.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 13 (28 July 2026 – 6 August 2026) |
| Views total | 3,896 |
| Reactions total | 169 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 22:17 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.
169 reactions across 13 posts, in 45 distinct kinds. The most used accounts for 9.47% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| custom 5229058898320725401 | 16 | 9.47% | |
| custom 5366524441935248798 | 8 | 4.73% | |
| custom 5244993862644036891 | 7 | 4.14% | |
| custom 5251326937950881338 | 7 | 4.14% | |
| 💯 | 7 | 4.14% | |
| custom 5235607297517953867 | 6 | 3.55% | |
| custom 5247248273797842459 | 6 | 3.55% | |
| custom 5463256910851546817 | 6 | 3.55% | |
| custom 5235807206770750407 | 5 | 2.96% | |
| custom 5247084231816941656 | 5 | 2.96% | |
| custom 5348583079344612398 | 5 | 2.96% | |
| custom 5362096403667519164 | 5 | 2.96% | |
| custom 5388569280704951127 | 5 | 2.96% | |
| custom 5402324347262108183 | 5 | 2.96% | |
| custom 5303124862015939911 | 4 | 2.37% | |
| custom 5325547803936572038 | 4 | 2.37% | |
| custom 5404519582356480056 | 4 | 2.37% | |
| custom 5438288139951051895 | 4 | 2.37% | |
| custom 5440549371512908812 | 4 | 2.37% | |
| custom 5463054218459884779 | 4 | 2.37% | |
| 25 further kinds | 52 | 30.8% |
Custom emoji. 19 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 areTelegram’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 13 of the 13 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 169reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 13 most recent posts we hold, published 28 July 2026 to 6 August 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.
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Театр, который невозможно показать на сцене 👩🍳 А если спектакль происходит не внутри здания, а внутри самого кампуса? >> С 7 по 9 августа территория коливингов Университета НЕЙМАРК превратится в настоящую театральную площадку. Прямо напротив корпуса №9 пройдёт показ спектакля «Мы» по мотивам романа Евгения Замятина. 💳 Кампус становится частью истории. Архитектура, дворы, пространство вокруг — всё превращается в де…
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Напиши научную статью на тему... // Признайтесь, хотя бы раз хотели заюзать такой способ, когда сидели над курсовой или статьей в два часа ночи. Открываешь чат, вставляешь тему — и через минуту получаешь готовый текст. Ура, проблема решена!!! 😅 НО…. Начинаешь читать и понимаешь: вроде всё написано правильно, а сказать этим текстом нечего. ИИ сегодня действительно умеет многое. ❗️ Он помогает собрать структуру стать…
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«Самое главное для победы — уметь взять себя в руки и вместо просмотра сериальчика пойти ботать» Серёжа Ерошкин начал участвовать в олимпиадах ещё в начальной школе. Интенсивная подготовка помогла ему стать призером регионального этапа ВсОШ по информатике, а позже — поступить в НЕЙМАРК на программу «Сопряжённая разработка программного и аппаратного обеспечения». 👉 Как готовился к олимпиадам? 👉 Что оказалось сложнее…
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Научный факт или миф? В интернете можно найти ответ почти на любой вопрос. При этом некоторые заблуждения живут десятилетиями ⁉️ Сделали небольшой фактчекинг вместе с кандидатом биологических наук, ведущим научным сотрудником Центра нейроморфных вычислений Университета НЕЙМАРК Никитой Григорьевым. #разборНЕЙМАРК
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Все действия были выполнены профессионалами! Пожалуйста, не пытайтесь повторить это дома ⚠️ Студенчество — время шалостей и экспериментов, возможность получить ИнДиВиДуАлЬнЫй опыт :) Соберём весь лор общаги в комм? #КоливингиНЕЙМАРК #СтудЖизньНЕЙМАРК
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💻 Создаём личного ИИ-эксперта для учёбы Чтобы каждый раз не искать нужную информацию на сотнях страниц учебников или конспектов, можно сделать удобную базу знаний по предметам и проектам. Новый инструмент нашли на GitHub, называется book-to-skill. 👉 Загружаете pdf, epub, docx или другой формат в систему; 👉 После обработки можно задавать вопросы и получить ответы прямо по содержимому учебника, без «воды» и выдумок; …
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Некоторые лекции должны оставаться скучными 👆 Каждый хоть раз сидел на паре с мыслью: «Когда уже будет что-нибудь интересное?» Да, было. // Хочется больше практики, кейсов, мемов, интерактива, чтобы препод был на одной волне. И это вполне нормальное желание. Но не все лекции обязаны быть прикольными 🙁 >> Есть темы, которые невозможно превратить в шоу. Потому что их задача — не развлечь, а собрать у вас в голове фун…
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Летний VIP-режим активирован 😎 Когда все разъехались по домам, общага внезапно стала… личной резиденцией. А где вы заспавнились на каникулы? #КоливингиНЕЙМАРК #СтудЖизньНЕЙМАРК
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Showing the 12 most recent of 13 posts we hold for @universityNeimark. 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 — 14,298 of 1,480,688entries 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.
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.
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.
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.
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 14 August 2026 — this entry's latest reading, not the date you are reading this.
“Университет НЕЙМАРК” (@universityNeimark), 715 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/universityNeimark.
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.