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Channel

JVB Academy

@JVB_Academy

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

862subscribers

+17 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002471441723
TypeChannel
Username@JVB_Academy
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live30 August 2026
Measurements held6
Confirmed unchanged1 time, most recently 30 August 2026
On Telegramt.me/JVB_Academy

Growth

845862853.57 August 2026 — 845 subscribers8 August 2026 — 845 subscribers8 August 2026 — 846 subscribers16 August 2026 — 850 subscribers24 August 2026 — 853 subscribers30 August 2026 — 862 subscribers7 August 202630 August 2026
6 measurements spanning 23 days, net +17. 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 842–865 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
30 Aug 2026, 13:05862+9
24 Aug 2026, 02:26853+3
16 Aug 2026, 14:26850+4
8 Aug 2026, 05:20846+1
8 Aug 2026, 01:20845no change
7 Aug 2026, 14:48845first reading

Engagement

10 posts held, back to 3 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
12.5%
avg views ÷ 862 subscribers
Avg views / post
107
9 posts measured
Reaction rate
2.53%
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. It is computed over the 2 of 9 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held10 (3 August 20267 August 2026)
Views total966
Reactions total5
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 01:20 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

Video runtime
1m 20s
Average length
1m 20s

Measured directly from 1 video 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

5 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 80.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
480.0%
👏120.0%

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 2 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 5reactions 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 3 August 2026 to 7 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

7 Aug 2026, 11:57 UTC68 viewsread 8 August 2026
Photo

Есть красота, которая требует усилий. А есть та, что выглядит так, будто подарена природой. Juvelook и Lenisna работают так, чтобы никто не догадался, что секрет — в современной косметологии. Как? Гибридные препараты не просто заполняют пустоты и увлажняют кожу — они запускают её естественное обновление. ✨ Juvelook — для тех, кто хочет сохранить тонкость и естественность лица. Разглаживает кожу, возвращает плотност

7 Aug 2026, 07:39 UTC69 viewsread 8 August 2026
Photo

Elravie Premier Ultra Volume Применяется для: 🟣восстановления объемов 🟣моделирования контуров лица 🟣коррекции скул, подбородка, линии челюсти Глубина введения: глубокие слои дермы и субдермальные структуры

6 Aug 2026, 13:08 UTC80 views2 reactionsread 8 August 2026
Photo

Обучающий семинар и мастер-класс «Новая эра гибридных комплексов: PDLLA + HA. Безопасная стимуляция выработки коллагена и мгновенное увлажнение в одну процедуру» 📸 📍Москва, 27 июля Спикер: Алим Русланович Ногеров - к.м.н., доцент, главный врач Nogerov International Clinic, научный руководитель SIAM, международный эксперт по аппаратным и инъекционным технологиям, эксперт JVB-group Хотите тоже пройти обучение по гиб

2

6 Aug 2026, 10:55 UTC90 viewsread 8 August 2026
Photo

Lenisna - гибридный коллагеностимулятор НОВОГО ПОКОЛЕНИЯ позволяет восстанавливать объем наиболее естественным образом 😳Сочетание большей концентрации PDLLA и HA позволяет восстановить контуры и утраченные объемы как на лице, так и на теле 😳Височно-темпоральный лифтинг 😳Устранение дряблости кожи и уплотнение дермы ПРЕИМУЩЕСТВА: 1. Долгосрочная выработка коллагена и восстановление объемов 2. Сниженные риски нежелате

6 Aug 2026, 07:27 UTC107 viewsread 8 August 2026
Photo

Клинический случай до/после от @elravie.crimea Контурная пластика губ с Elravie Premier Deep Line На фото — результат процедуры контурной пластики губ с применением филлера Elravie Premier Deep Line. Что удалось получить? ✔️Гармоничное увеличение объема губ ✔️Четкий и красивый контур ✔️Коррекцию асимметрии ✔️Увлажнение и улучшение качества тканей губ ✔️Естественный результат без эффекта избыточного объема Elravie

5 Aug 2026, 08:10 UTC132 viewsread 8 August 2026
Photo

Elravie Premier Deep Line Используется для: ✅носогубных складок ✅средних и глубоких морщин ✅объемной коррекции ✅морщин марионеток ✅средней части лица ✅лба Глубина введения: средние слои дермы и подкожно-жировая клетчатка.

4 Aug 2026, 13:34 UTC118 views3 reactionsread 8 August 2026
Video

💉27 июля в Москве состоялся обучающий семинар и мастер-класс, посвящённый работе с препаратами Juvelook и Lenisna Участники получили возможность не просто услышать теорию, а увидеть её воплощение — от разбора протоколов до отработки техник под руководством международного эксперта, кандидата медицинских наук Алима Руслановича Ногерова. Узнайте, какие впечатления остались у участников семинара, из нового видео 📷⬆️ Б

2👏1

4 Aug 2026, 10:34 UTC155 viewsread 8 August 2026
Photo

Преимущества Juvelook для ваших пациентов Juvelook — это не только эффективная, но и безопасная процедура для восстановления объёмов и улучшения качества кожи. Основные преимущества, которые стоит учитывать в работе с пациентами: 1. Долгосрочная выработка коллагена и восстановление объёмов. 2. Сниженные риски нежелательных явлений. 3. Видимый результат уже сразу после процедуры. 4. Биосовместимость. Гиалуронат натр

4 Aug 2026, 06:30 UTC147 viewsread 8 August 2026
Photo

Как работают филлеры ELRAVIE Premier Препараты ELRAVIE Premier содержат гиалуроновую кислоту разной концентрации, что позволяет точно подбирать решение под задачу пациента. На уровне тканей они: • улучшают оксигенацию тканей • замедляют процессы старения • притягивают и удерживают влагу • создают физиологичный объём Результат: кожа становится более гладкой, эластичной, с ровным здоровым тоном. 📉Визуально пациент

Showing the 10 most recent of 10 posts we hold for @JVB_Academy. 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 — 554,810 of 1,628,524entries 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

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

“JVB Academy” (@JVB_Academy), 862 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/JVB_Academy.

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.