5 measurements spanning 11 days, net +39. 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 3,374–3,426 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Aug 2026, 05:52
3,420
+16
14 Aug 2026, 21:38
3,404
+10
11 Aug 2026, 18:13
3,394
+14
8 Aug 2026, 13:52
3,380
-1
7 Aug 2026, 14:46
3,381
first reading
Engagement
13 posts held, back to 2 May 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 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
48.9%
avg views ÷ 3,420 subscribers
Avg views / post
1,670
3 posts measured
Reaction rate
4.46%
reactions ÷ views · ER floor
Posts in window
3
of 13 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 21 July 2026
Posts held
13 (2 May 2026 – 21 July 2026)
Views total
5,020
Reactions total
224
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 23:25 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.
Reaction mix
571 reactions across 13 posts, in 12 distinct kinds. The most used accounts for 60.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
343
60.1%
🔥
80
14.0%
🥰
40
7.01%
👍
32
5.60%
❤🔥
27
4.73%
👏
21
3.68%
🙏
18
3.15%
🤩
5
0.876%
🍾
2
0.35%
⚡
1
0.175%
🎉
1
0.175%
🕊
1
0.175%
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 571reactions 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 2 May 2026 to 21 July 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.
Telegram Stars
Stars received
4
across the posts below
Posts paid on
3
of 13 we hold a reading for · 23%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @marinazharikovaaa. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 13 most recent posts we hold for this entry, published 2 May 2026 to 21 July 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Я вернулась 🥺
Из-за большого количества работы я не вела канал, но теперь я снова здесь!
Буду показывать вам успехи своих поступающих, они самые лучшие и поступили в LMU, TUM, RWTH Aachen и другие университеты Германии и уже в октябре начнут обучение 😭🤍
очень люблю свою работу
ОТЗЫВЫ
ПОШАГОВЫЙ ПЛАН ПОСТУПЛЕНИЯ В УНИВЕРСИТЕТЫ ГЕРМАНИИ ⬇️
🟢где искать программы?
🟢как подать документы?
🟢бесплатные курсы немецкого🇩🇪
🟢получение визы
🟢и многое другое уже в файле
Сохраняйте, чтобы не потерять 📌
Как проходит поступление в этом году?
Из-за большого количества работы я не успеваю вести канал, но вернусь, когда все документы студентов будут поданы в университеты Германии. Сейчас начинается самая активная и сложная работа, так как все получают аттестаты и можно отправлять заявления. Много поступающих на зимний семестр 2026/2027
Несколько советов родителям будущих студентов: после успешного поступления ребята б…
Медицина в Германии - поступление на направления Humanmedizin, Zahnmedizin
Учеба и поступление одни из самых сложных, так как чаще всего иностранцы получают только 5% мест в общем конкурсе. Здесь работают исключительно документы, баллы, конкуренция, национальная квота и социальные параметры
Что может помочь?
возможность подаваться в большое количество вузов, а также готовность идти на запасные направления или в ча…
Успехи поступающих: приглашения на зимний семестр этого года💌
🟢Рената — поступила в RWTH Aachen на направление «физика» после двух лет обучения в МГУ
🟢Кирилл — посещает языковые курсы при университете Karlsruhe KIT и готовится к вступительным экзаменам Studienkolleg
🟢Вика — учится в немецкой гимназии, но решили поступать на медицину через Studienkolleg. Она получила школьный аттестат в прошлом году и мы смогли под…
Если вы планируете учёбу в Германии, дни открытых дверей (Tag der offenen Tür)— отличный способ познакомиться с вузом, программами и преподавателями до поступления
Проводятся как обычные (на кампусе), так и онлайн-мероприятия, где можно поучаствовать online
На таких днях можно:
✨встретиться со студентами и профессорами
✨посмотреть аудитории и лаборатории
✨узнать требования для поступления
✨задать вопросы лично
Де…
В моем канале нет рекламы и всё, что я делаю - бесплатно, но сегодня хочу рассказать вам про Веру (сестру моей поступающей) — преподавателя английского и специалиста по США🇺🇸
Если вы думаете про поступление в Германию, английский вам точно пригодится: для англоязычных программ в Германии, международных обменов, эссе, интервью и будущей карьеры.
Вера ведёт канал про английский, США и возможности для студентов.
Так…
🎤 подкаст: опыт обучения в Studienkolleg Heidelberg, M-Kurs
в прошлом году Лера успешно поступила в Studienkolleg и сегодня мы встретились с ней, чтобы она поделилась своим опытом поступления и обучения в Германии 🏫
путь Леры:
🟢сдача Goethe Zertifikat В2 и получение визы
🟢языковые курсы в Германии
🟢поступление в несколько Studienkolleg
подробнее здесь
в начале июля Лера сдает FSP и планируем поступление в Universit…
🔥15❤4❤🔥2👏1
Showing the 12 most recent of 13 posts we hold for @marinazharikovaaa. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 645,597 of 1,549,376entries 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.
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
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.
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 18 August 2026 — this
entry's latest reading, not the date you are reading this.
“Учеба в Германии | Поступление 🇩🇪 | Studienkolleg” (@marinazharikovaaa), 3,420 subscribers as measured 18 August 2026. Telegram Register, tgregister.com/channel/marinazharikovaaa.
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.