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Channel

МЛМ РЕВОЛЮЦИЯ 11.05-15.05

@mlmforum1

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

6,112subscribers

-50 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001630974962
TypeChannel
Username@mlmforum1
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live25 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 25 August 2026
On Telegramt.me/mlmforum1

Growth

6,1126,1626,1376 August 2026 — 6,162 subscribers6 August 2026 — 6,161 subscribers9 August 2026 — 6,155 subscribers12 August 2026 — 6,142 subscribers16 August 2026 — 6,128 subscribers19 August 2026 — 6,120 subscribers22 August 2026 — 6,117 subscribers25 August 2026 — 6,112 subscribers6 August 202625 August 2026
8 measurements spanning 19 days, net -50. 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 6,105–6,170 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
25 Aug 2026, 13:436,112-5
22 Aug 2026, 23:246,117-3
19 Aug 2026, 07:246,120-8
16 Aug 2026, 02:066,128-14
12 Aug 2026, 09:186,142-13
9 Aug 2026, 11:116,155-6
6 Aug 2026, 13:526,161-1
6 Aug 2026, 10:476,162first reading

Engagement

20 posts held, back to 24 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 9 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.63%
avg views ÷ 6,112 subscribers
Avg views / post
222
8 posts measured
Reaction rate
0.477%
reactions ÷ views · ER floor
Posts in window
8
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. It is computed over the 3 of 8 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 6 August 2026
Posts held20 (24 June 20266 August 2026)
Views total1,774
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 03:29 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

11 reactions across 8 posts, in 3 distinct kinds. The most used accounts for 54.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
654.5%
🔥327.3%
👍218.2%

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 9 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 11reactions 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 24 June 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.

Recent posts

4 Aug 2026, 14:20 UTC259 views0 reactionsread 12 August 2026

Если вы лидер, подумайте о своих новичках. Представьте: через пару месяцев вы даёте человеку не просто инструкцию «делай контент», а готовую систему. Как писать. Как отвечать на возражения. Как готовиться к встречам. Как анализировать переписки. Вчера на мастер-классе увидел, что это работает. 45 человек, реальные задачи. Теперь запускаю мастер-группу — 6 недель практики. Записал короткий обзор: https://www.youtu

3 Aug 2026, 16:15 UTC269 viewsread 12 August 2026

Пока идёт эфир, поймал себя на мысли. Многие вещи кажутся очевидными только после того, как увидишь их в работе. Именно поэтому сегодня я решил не рассказывать, а показать. Показываю, как использую нейросети для: • анализа переписок; • создания контента; • подготовки выступлений; • других ежедневных задач. Если хотите подключиться — ещё не поздно. 👉 Регистрация обязательна: https://app-c82081.aircoding.ai/

3 Aug 2026, 14:20 UTC233 viewsread 12 August 2026

Через полтора часа начинаем. Сегодня на реальных примерах покажу, как нейросеть может помочь сетевику: — не сидеть часами над постом; — разобрать переписку, в которой кандидат пропал; — подготовить первое сообщение без шаблонного спама; — из одной идеи получить сразу несколько публикаций; — быстрее подготовиться к эфиру или встрече. И главное — покажу свою систему работы изнутри, а не только готовые результаты

3 Aug 2026, 10:59 UTC270 views2 reactionsread 12 August 2026
Video message

Video message, posted without a caption

👍1🔥1

3 Aug 2026, 09:31 UTC202 viewsread 12 August 2026

Если честно, контент давно перестал быть моей ежедневной проблемой. Не потому что стало больше вдохновения. А потому что появилась система. Теперь одна идея может превратиться в: • пост; • карусель; • сценарий для Reels; • первые сообщения кандидатам; • идеи следующих публикаций. И при этом времени уходит меньше, чем раньше на подготовку одного поста. Сегодня вечером впервые покажу, как эта система устроена

2 Aug 2026, 18:15 UTC205 viewsread 12 August 2026

Если честно… Мне кажется, большинство сетевиков тратят слишком много времени на контент. Сесть. Придумать тему. Переделать. Опубликовать. Через день всё сначала. А ведь можно построить систему, в которой контент перестает быть ежедневной проблемой. Именно такую систему я сейчас собираю для себя. Я называю ее маленьким контент-заводом. Когда нейросети помогают не только написать один пост, а постоянно создав

1 Aug 2026, 11:40 UTC236 viewsread 12 August 2026

Завтра в 12:00 проведу бесплатный мастер-класс. Но сначала одна мысль. Нейросети не заменяют сетевика. Они освобождают его от рутины. Мне кажется, большинство до сих пор используют нейросети как поисковик. «Напиши пост.» «Придумай идею.» «Сделай картинку.» Иногда получается неплохо. Но настоящая польза начинается совсем в другом месте. Когда нейросеть перестает быть генератором текстов и становится помощнико

27 Jul 2026, 12:50 UTC534 viewsread 12 August 2026

Через час начинаем практикум «Люди сами пишут». Сегодня на первой встрече выберем тему и начнём создавать публикацию для вашего проекта. Дальше разместим её, посмотрим на реакцию аудитории и разберём, как превращать отклики в живые диалоги без давления и навязывания. Не нужно заранее уметь писать сильные тексты. Не нужно разбираться в сложных инструментах искусственного интеллекта. Будем делать всё вместе, шаг з

27 Jul 2026, 08:09 UTC463 viewsread 12 August 2026

Сегодня начинаем. В 17:00 мск состоится первая встреча практикума «Люди сами пишут». Мне нравится формат небольших практикумов по одной причине. Здесь сложно спрятаться за словами: «Я обязательно сделаю это потом». Сегодня каждый участник возьмёт свой настоящий проект, выберет тему и начнёт создавать публикацию. Не абстрактный учебный текст. Не заготовку, которая останется лежать в папке. Материал, который мы

Showing the 12 most recent of 20 posts we hold for @mlmforum1. 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 — 388,231 of 1,620,105entries 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

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.

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

“МЛМ РЕВОЛЮЦИЯ 11.05-15.05” (@mlmforum1), 6,112 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/mlmforum1.

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.