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Channel

Глава Нуры

@glava_nura

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

21subscribers

+3 since we began measuring on 11 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1004377006220
TypeChannel
Username@glava_nura
CreatedBetween 1 June 2026 and 6 August 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live12 August 2026
Measurements held2
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/glava_nura

Growth

182119.511 Aug 2026, 21:45 — 18 subscribers12 Aug 2026, 11:06 — 21 subscribers11 Aug 2026, 21:4512 Aug 2026, 11:06
2 measurements taken within a single day, net +3. 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 18–21 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 11:0621+3
11 Aug 2026, 21:4518first reading

Engagement

10 posts held, back to 6 August 2026the 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
156.7%
avg views ÷ 21 subscribers
Avg views / post
32.9
10 posts measured
Reaction rate
10.9%
reactions ÷ views · ER floor
Posts in window
10
of 10 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
WindowRolling 30 days · latest post in window 11 August 2026
Posts held10 (6 August 202611 August 2026)
Views total329
Reactions total36
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Aug 2026, 21:45 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.

Reaction mix

36 reactions across 10 posts, in 5 distinct kinds. The most used accounts for 52.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1952.8%
❤‍🔥719.4%
👍411.1%
💯411.1%
🔥25.56%

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 10 of the 10 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 36reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 6 August 2026 to 11 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.

Recent posts

11 Aug 2026, 14:15 UTC27 views2 reactionsread 11 August 2026
Photo

📖 Глава прочитана МУРАКАМИ / ЧАСТЬ 01 📚 «Мои любимые книги Мураками» 🌀 «Трилогия Крысы» 📖 - Слушай песню ветра, Пинбол 🐑 - Охота на овец 💃 - Дэнс, Дэнс, Дэнс 📚 Первые книги «Слушай песню ветра» и «Пинбол, 1973» — кажутся немного скучноватыми. Не совсем понимаешь, куда всё это движется и зачем тебе рассказывают именно эти истории. ✨ Но дальше начинается самое интересное. 🌀 Сюжет постепенно становится более зак

1👍1

11 Aug 2026, 09:26 UTC23 views3 reactionsread 11 August 2026
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📖Глава прочитана ✨ Какой бывает Мураками? ✨ Этим постом начинаю серию постов про книги моего любимого автора. 📚 🇯🇵 Харуки Мураками - японский писатель, которого невозможно читать только в рамках одного жанра. В его книгах смешаны реальность и мистика, повседневность и сюрреализм, а за странными историями кроются глубокие темы одиночества, любви, поиска себя и смысла жизни. 🌙 📖 Я прочитала у него более 10 книг и

2❤‍🔥1

10 Aug 2026, 11:31 UTC133 views6 reactionsread 11 August 2026
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📖Глава прочитана 📚 Книги для уютного вечера Иногда хочется уютную, спокойную книгу на вечер, чтобы ненадолго выпасть из реальности 🤎 Вот моя небольшая подборка таких книг: 📸 «Фотостудия Таккуда» 💭 Очень тёплая и немного меланхоличная история. Здесь много внимания уделено людям, их воспоминаниям и тому, что остаётся за кадром обычных фотографий. 🍬 «Лавка сладостей на Сумеречной аллее» 💭 Сладости, небольшая л

💯42

10 Aug 2026, 07:20 UTC23 views3 reactionsread 11 August 2026
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Коллега порадовала с утра пораньше открыточкой с котиком 🥹🐈 Такие маленькие штуки делают день!

❤‍🔥3

9 Aug 2026, 16:21 UTC20 views5 reactionsread 11 August 2026
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Этим летом настольный теннис стал для меня приятным открытием 🏓 Оказывается, во многих дворах и скверах Петербурга стоят столы, и люди совершенно спокойно выходят поиграть. Почему то, я заметила это только этим летом 😅 Поэтому было приятно решение купить ракетки и наслаждаться игрой на свежем воздухе пока тепло☀️ Вообще, люди в СПБ очень активно проводят время на улице: гуляют, занимаются спортом, катаются на вел

5

9 Aug 2026, 09:17 UTC20 views4 reactionsread 11 August 2026

📖 Глава прочитана «Щегол» — Донна Тартт ✨ О книгах Донны Тартт можно говорить бесконечно. До «Щегла» я уже читала «Тайную историю», и это одна из тех книг, к которым мне точно захочется вернуться (она у меня даже лежит в бумажном варианте вся из исписанная цитатами). Поэтому, начиная «Щегла», я ожидала испытать такие же сильные эмоции, увидеть ту же глубину и невероятную проработку сюжета 🤍 Признаюсь честно, пове

3🔥1

8 Aug 2026, 17:26 UTC22 views5 reactionsread 11 August 2026
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📍 Новая точка на карте 🍲 Впервые попробовала ХоГо - китайское блюдо. Недавно мы с друзьями сходили в «ОгоХого» 🙌 Вам приносят кастрюлю с кипящим бульоном, а ты сам выбираешь, что туда добавить. Мясо, овощи, разные ингредиенты — всё готовится прямо перед тобой. И в этом есть какой-то свой кайф: сидишь, пробуешь, экспериментируешь с сочетаниями и постепенно понимаешь, что тебе нравится больше всего. Честно говоря,

4🔥1

8 Aug 2026, 16:53 UTC22 views3 reactionsread 11 August 2026

📖Глава прочитана 📚 Бумажные книги или ридер? Вечный спор 😂 Если бы кто-то лет 5-7 назад сказал мне, что я буду с удовольствием читать электронные книги, я бы точно не поверила. С самого детства я обожала бумажные книги. ❤️ Для меня чтение — это целый ритуал: текстура, запах книги, думаю кто любит читать, меня поймёт. Поэтому долгое время я даже не рассматривала их. Но примерно год назад я всё-таки решила попро

❤‍🔥3

6 Aug 2026, 12:36 UTC21 views3 reactionsread 11 August 2026
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📍 Новая точка на карте - Осиновецкий маяк 🌊 Маленькое путешествие к Ладоге За 3 года жизни в Петербурге я ни разу не была на Ладожском озере… и вот наконец-то исправила это 🥹🤍 Съездила к Осиновецкому маяку — посмотреть на Ладогу, погулять и просто немного сменить городскую суету на воду 🌊🍃 Я уже была в крепости Орешек несколько лет назад 🏰 Тоже очень классное место — старые стены, история, вода вокруг и какая-то

👍3

Showing the 10 most recent of 10 posts we hold for @glava_nura. 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 — 320,602 of 1,481,217entries 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 4 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.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Глава Нуры” (@glava_nura), 21 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/glava_nura.

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.