2 measurements taken within a single day, net -1. 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 1,553–1,554 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 07:32
1,553
-1
7 Aug 2026, 07:32
1,554
first reading
Engagement
21 posts held, back to 2 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 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
65.6%
avg views ÷ 1,553 subscribers
Avg views / post
1,020
7 posts measured
Reaction rate
1.78%
reactions ÷ views · ER floor
Posts in window
7
of 21 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 7 August 2026
Posts held
21 (2 April 2026 – 7 August 2026)
Views total
7,133
Reactions total
127
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 18:07 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
423 reactions across 21 posts, in 8 distinct kinds. The most used accounts for 62.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
266
62.9%
👍
73
17.3%
❤
42
9.93%
🎉
28
6.62%
⚡
6
1.42%
💯
4
0.946%
🆒
3
0.709%
🤩
1
0.236%
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 21 of the 21 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 423reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 2 April 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.
🎓 Онлайн курс Bim-менеджер: Специализация «Линейные объекты»
📌 24 августа стартует специализация «Линейные объекты» в рамках курса «BIM-менеджер» от наших партнеров, компании ПСС. Можно записаться без прохождения общей базы. Если вы уже работаете в инфраструктурных проектах и хотите углубиться именно в BIM для линейных объектов — этот курс для вас.
🔘 Программный комплекс Топоматик Robur — основной инструмент курса.…
📀⚪️Менеджер BCF — работа с комментариями в Топоматик 360
📍В данном видео продемонстрирован полный цикл работы с замечаниями в формате BCF в Топоматик 360 — от импорта присланного файла до выгрузки собственных комментариев.
Возможности плагина:
🔘добавлять комментарии к сборочным проектам в формате IFC и SMDX;
🔘экспортировать комментарии в Excel;
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👥 Плагин разработан …
ℹ️ Обновление онлайн-документации
📌Продолжается перенос онлайн-документации по продуктам и сервисам Топоматик на новую платформу:
🔘Добавлены новые разделы;
🔘Добавлена возможность скачивания документации:
📄 в формате PDF;
📑 в виде файлов Markdown для использования во внутренних базах знаний организаций.
➡️ Ознакомиться с документацией.
🟪 Топоматик в MAX
#Топоматик_robur #обновление
📂 Наши партнеры из компании «Цифровые Технологии 1520» объявили начало бета-тестирования плагина для анализа и обмена данными между проектами «Топоматик Robur»
📌Предлагаем присоединиться, для этого пришлите запрос, указав ФИО, e-mail и наименование организации на адрес: info@dt1520.ru
➡️Ознакомиться с плагином «Альбатроc: Модуль обмена данными»
💬Плагин также доступен на нашем сайте.
#Топоматик_robur #плагины
🔘 💻 Robur MCP — плагин для подключения ИИ-моделей
📌Компания «Топоматик» разработала плагин, который позволяет подключать ИИ-модели и агенты при работе напрямую в проекте Robur. Разработка носит некоммерческий характер и является второй частью нашего исследовательского проекта по внедрению полноценного ИИ-ассистента для специалистов в рамках программного комплекса Топоматик Robur.
Разработка размещена в открытом дос…
📂 Новые плагины на сайте Топоматик
📍На официальном сайте обновлена страница с плагинами для программного комплекса Топоматик Robur.
Добавлены новые модули, которые разработали эксперты сообщества Robur Community:
🔘Ярослав Абрамов, канал: https://t.me/yabramove;
🔘Борис Фатеев, канал: https://t.me/RoburFan.
💬Плагины являются некоммерческими и предоставляются для свободного использования.
➡️Ознакомиться с плагинам…
🛤️ 🚇 Обновлен дистрибутив программного продукта «Топоматик Robur — Железные дороги», модуль Метро.
Сборка 16.0.64.2
📍Что нового?
🔘 Реализован блок инструментов по созданию и редактированию элементов верхнего строения пути;
🔘 Сделан ряд других функциональных дополнений.
Скачать дистрибутив программы и ознакомиться с полным списком изменений можно на странице продукта.
➡️ Перейти на страницу продукта.
🟪 Топоматик …
🎓 Дистанционное обучение по программным продуктам НПФ «Топоматик»
📍В сентябре-октябре 2026 года НПФ «Топоматик» проводит обучение по продуктам программного комплекса «Топоматик Robur».
🔘Обучение будет проходить дистанционно, на платформе ЯндексТелемост с 10:00. до 18:00 по МСК.
🔘Стоимость обучения одного человека в группе составляет 28800,00 руб. с учетом НДС 5%.
🔘Запись осуществляется путем направления заявки на …
🔘💻 TLCAssistant — Cвод правил для создания TLC
📌 Компания «Топоматик» разработала свод правил для автоматизированной генерации скриптов TLC при помощи ИИ-моделей под наименованием TLCAssistant.
🔘 Разработка носит некоммерческий характер и предназначена для упрощения создания параметрических TLC-объектов, а также их проверки и предоставления справочной информации.
🔘 Свод правил может быть применен в любой подходяще…
🔵🧮Интеграция сметного ПО в Топоматик 360
📌Компания АВС — разработчик отечественной сметной экосистемы, подготовила специализированный плагин, обеспечивающий прямую интеграцию между BIM-моделями транспортных инженерных сооружений и сметным ПО в Топоматик 360.
Разработанный плагин выступает в роли «бесшовного моста» между BIM-средой и сметной системой. Интеграция позволяет:
🔘Назначать сметные свойства прямо в модели:…
📂 Новый плагин для Топоматик Robur — Автомобильные дороги
📍Эксперт сообщества Robur Community Ярослав Абрамов разработал расширение для Топоматик Robur, предназначенное для управления конфигурациями слоев и настройками автомобильных дорог. Плагин является некоммерческим и предоставляется для свободного использования.
➡️Скачать плагин
➡️Канал Ярослава
💬Напоминаем, что плагины наших пользователей мы размещаем на наш…
🔘📁 Маппинг-файлы Топоматик Robur опубликованы на сайте Мособлгосэкспертизы
📌На официальном сайте ГАУ МО «Мособлгосэкспертиза» размещены файлы-маппинга Топоматик Robur в соответствии с актуальными требованиями к цифровым информационным моделям.
Файлы опубликованы в составе документов:
🔘 «Требования к цифровым информационным моделям наружных инженерных сетей, представляемым для проведения экспертизы. Редакция 3.3»;
🔘…
🔥12❤6👍5
Showing the 12 most recent of 21 posts we hold for @topomatic_official. 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 — 283,307 of 1,169,250entries 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 3 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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@topomatic_official named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@yabramov22 named in 1 post, 8 August 2026 – 8 August 2026
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.
“Топоматик” (@topomatic_official), 1,553 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/topomatic_official.
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.