2 measurements taken within a single day. 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 195–197 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 11:45
196
no change
7 Aug 2026, 21:03
196
first reading
Engagement
20 posts held, back to 30 April 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 · 30 days
10.9%
avg views ÷ 196 subscribers
Avg views / post
21.3
3 posts measured
Reaction rate
15.6%
reactions ÷ views · ER floor
Posts in window
3
of 20 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 31 July 2026
Posts held
20 (30 April 2026 – 31 July 2026)
Views total
64
Reactions total
10
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 11:45 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
Photos
36
Videos
6
Links
16
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
3m 16s
Average length
1m 38s
Measured directly from 2 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
91 reactions across 17 posts, in 6 distinct kinds. The most used accounts for 75.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
69
75.8%
👍
11
12.1%
🔥
5
5.49%
😁
4
4.40%
💯
1
1.10%
🤔
1
1.10%
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 17 of the 20 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 91reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 30 April 2026 to 31 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.
Как думаете, как ощущает себя человек на картинке справа? Признавайтесь, бывало ли с вами такое? 🙂
Неважно, сколько лет вы уже учили язык. Даже если вы освоились, грамотно используете времена и филигранно вставляете артикли, вы всё равно можете чувствовать себя неуверенно.
Место вашего пребывания вообще не имеет значения: картинная галерея, конференция, small-talk или собеседование. Нехватку подходящих языковых кон…
Мы выбираем одежду под ситуацию.
С речью - то же самое.
Почему вы вроде бы знаете английский, но не всегда можете выразить себя в нужной ситуации?
Это как с гардеробом.
У вас есть вещи, но нечего надеть: нет платья на свадьбу или костюма для важных переговоров.
На самом деле, вам не нужно учить весь английский целиком.
Вам нужен базовый лингвистический гардероб - прочный фундамент: несколько времен, ключевая лекси…
Кстати, я отдельной любовью люблю медицинский английский.
Во-первых, он, как и медицинский русский, опирается на латинский. И многие термины узнаются интуитивно.
Во-вторых, я проходила курс медицинского английского. И у меня есть идея создать отдельную программу для детей и взрослых, где ученики изучали бы названия всех органов тела, врачей разных специальностей и базовые медицинские процедуры: анализы, уколы, капе…
Про английский и наркоз.
За последние пол года я прошла через три наркоза (ничего страшного, плановые процедуры).
После первого наркоза я проснулась и первым делом отправила другу сообщение на английском:
I am back.
Мы посмеялись и забыли.
Но после третьего раза вышло ещё круче.
Я проснулась, увидела что рядом стоит какой-то человек и решила спросить, мой ли это врач. Если это была бы она, я планировала сказать…
Принесла вам сегодня лингвистический horror!👻
Человек уехал в Америку с уровнем А2, а вернулся с уровнем A1. Как такое возможно рассказала в видео ниже! ⬇️
Закрепляем 👇
Дополните каждое предложение одним подходящим словом:
recipe, receipt или prescription.
Потом открывайте спойлер и проверяйте себя ✨
1. I lost the receipt from the clothes shop, so I can’t return my jacket.
2. Could you give me the recipe for this cake? It was amazing.
3. The doctor wrote a prescription for antibiotics.
Showing the 12 most recent of 20 posts we hold for @maria_balaeva_eng. 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
Citation-graph rank — 1,289,166 of 1,548,671entries 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.
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.
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 8 August 2026 — this
entry's latest reading, not the date you are reading this.
“Искусство учиться || Мария Балаева” (@maria_balaeva_eng), 196 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/maria_balaeva_eng.
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.