Telegram RegisterThe public register of Telegram

Channel

1С:Лекторий

@lector_1c

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

12,354subscribers

-21 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001871756457
TypeChannel
Username@lector_1c
Description1С:Лекторий – это еженедельные лекции фирмы «1С» по законодательству и его отражению в программах «1С» Подробнее its.1c.ru/lector #9OBJC
CreatedBetween 1 October 2022 and 30 September 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held6
Confirmed unchanged2 times, most recently 13 August 2026
On Telegramt.me/lector_1c

Growth

12,35412,37512,364.57 August 2026 — 12,375 subscribers8 August 2026 — 12,372 subscribers9 August 2026 — 12,366 subscribers9 August 2026 — 12,362 subscribers10 August 2026 — 12,355 subscribers12 August 2026 — 12,354 subscribers7 August 202612 August 2026
6 measurements spanning 5 days, net -21. 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 12,351–12,378 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 00:0812,354-1
10 Aug 2026, 21:1112,355-7
9 Aug 2026, 23:3212,362-4
9 Aug 2026, 01:1112,366-6
8 Aug 2026, 00:0212,372-3
7 Aug 2026, 06:4612,375first reading

Engagement

31 posts held, back to 29 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 16 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
8.07%
avg views ÷ 12,354 subscribers
Avg views / post
997
30 posts measured
Reaction rate
0.176%
reactions ÷ views · ER floor
Posts in window
31
of 31 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 11 of 30 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 12 August 2026
Posts held31 (29 July 202612 August 2026)
Views total29,905
Reactions total21
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 03:28 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
961
Videos
55
Links
2,160

Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

21 reactions across 11 posts, in 3 distinct kinds. The most used accounts for 76.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1676.2%
👍419.0%
🔥14.76%

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 11 of the 31 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 21reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 31 most recent posts we hold, published 29 July 2026 to 12 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

12 Aug 2026, 12:59 UTC427 viewsread 13 August 2026

🔥 Смотрите видеозапись лекции Статистическая отчетность - каких изменений ожидать с отчетности за 2026 год В связи с запуском с января 2027 года ГИС «Цифровая аналитическая платформа предоставления статистических данных» (ГИС ЦАП) у предприятий возникают вопросы, как изменится статистическая отчетность. В ходе лекции Денис Евгеньевич Тимофеев, начальник управления координации и развития статистического учета Росстат

12 Aug 2026, 08:59 UTC508 viewsread 13 August 2026

📖 Маркировка в 1С: загружаемый классификатор товарных категорий 🤓

12 Aug 2026, 05:59 UTC600 viewsread 13 August 2026

🔴Рекомендуем к просмотру серию лекций об Электронных перевозочных документах (ЭПД): ▫️01.07.2026. Обязательное использование электронных перевозочных документов, возможности сервиса ▫️09.07.2026. Работа с ЭПД в мобильном приложении 1С ▫️15.07.2026. ЭПД на практике: особенности заполнения и подписание перевозочных документов с телефона ▫️22.07.2026. ЭТрН: как подготовиться к обязательному использованию с 1 сентября 2

11 Aug 2026, 12:59 UTC767 viewsread 13 August 2026

‼️Про ЭТрН с опциональными титулами (основную схему перевозки, как ее видит Минтранс) подробно рассказал Антон Бушмелев, эксперт ГК "Астрал" в лекции на тему Работа с ЭПД в мобильном приложении 1С Дополнительно рекомендуем: ▫️Презентация лектора ▫️Получить индивидуальную консультацию ▫️Сервис 1С-ЭПД ▫️Мобильное приложение 1С-ЭПД 👉 Смотрите бесплатно полную видеозапись лекции 📲 1С:Лекторий в МАХ 💙 1С:Лекторий Вко

11 Aug 2026, 05:59 UTC728 viewsread 13 August 2026

🤓 В июле в 1С:Лектории прошло 14 интересных лекций и даже 1 в августе. Проверьте, не пропустили ли вы что-то интересное для себя❗️ 🔝06.08.2026. 1С-ЭПД: как подключиться и начать работать уже сейчас. Практика и опыт пользователей 🔝30.07.2026. ЭПД с 01 сентября 2026 года: экспедиторские документы 29.07.2026. Новое в программах 1С:ERP и 1С:КА версии 2.6.1 и 1С:УТ версии 11.6.1 🔝28.07.2026. Сохранить себя в хаосе: пс

10 Aug 2026, 12:59 UTC714 viewsread 13 August 2026

❓У сотрудника (инвалид) два остатка по основному отпуску разными столбцами: 8,67, +18,67. Как правильно скорректировать остатки? Как оставить только один вид основного отпуска? на этот и другие вопросы ответила Анастасия Гурьева, эксперт 1С, в лекции на тему Отпуска в «1С:ЗУП 8», ред. 3: алгоритмы расчета, учет остатков, доли РК и СН 👉 Смотрите бесплатно полную видеозапись лекции Дополнительно рекомендуем: ▫️През

10 Aug 2026, 08:59 UTC722 viewsread 13 August 2026

🔥 Смотрите видеозапись лекции 1С:Гид по кадровому учету: От кадровых решений до выплат: 5 процессов под контролем в 1С:ЗУП и 1С:ЗКГУ В этом выпуске мы собрали пять процессов, которые связывают кадровые решения, развитие и поощрение сотрудников с расчетом выплат и контролем взаиморасчетов. Покажем, какие настройки, документы и отчеты используются на каждом этапе и что важно проверить, чтобы процесс оставался управляем

10 Aug 2026, 06:01 UTC739 viewsread 13 August 2026

🤓 Лекции, которые вы могли пропустить в июне 🎁 25.06.2026. Кадровое планирование в 1С:ЗУП КОРП — инструмент для управления штатом и кадровыми ресурсами 🔝23.06.2026. Учет иностранных работников на примере программы 1С:ЗУП, ред.3 🔝18.06.2026. СПОТ: поддержка изменений в программе 1С:Бухгалтерия 8 11.06.2026. Отпуска в «1С:ЗУП 8», ред. 3: алгоритмы расчета, учет остатков, доли РК и СН 09.06.2026. Дополнительные вых

7 Aug 2026, 12:59 UTC950 views4 reactionsread 13 August 2026

‼️В каких кейсах без ЭПД не обойтись? рассказала Костюкова Ольга – консультант по внедрению сервиса 1С-ЭПД в лекции на тему ЭПД на практике: особенности заполнения и подписание перевозочных документов с телефона 👉 Смотрите бесплатно полную видеозапись лекции 📲 1С:Лекторий в МАХ 💙 1С:Лекторий Вконтакте 🆗 1С:Лекторий в Одноклассниках

👍21🔥1

7 Aug 2026, 09:04 UTCviews —

1С:Лекторий pinned «🤓 Лекции, которые вы могли пропустить в мае 🎁 28.05.2026. Развитие учета внеоборотных активов в программах 1С:ERP и 1С:Комплексная автоматизация 27.05.2026. Бухгалтерский и налоговый учет в "1С: Бухгалтерия некоммерческий организации" 🔝26.05.2026. Доходы…»

7 Aug 2026, 08:59 UTC≈2,190 views1 reactionsread 13 August 2026

🔥 Смотрите видеозапись лекции на тему 1С-ЭПД: как подключиться и начать работать уже сейчас. Практика и опыт пользователей 01 сентября 2026 года вводится обязательное использование электронных перевозочных документов (ЭПД). Для того, чтобы переход к ЭПД был безболезненным и своевременным, следует позаботиться об этом прямо сейчас. Этой лекцией мы подведем итоги и поможем слушателям перейти от теории к действию: выбр

1

7 Aug 2026, 05:59 UTC822 views1 reactionsread 13 August 2026

🔴Рекомендуем к просмотру лекции по лизингу не утратившие актуальность на текущий момент: ▫️15.06.2023. Учет лизинговых операций у лизингополучателя в «1С:Бухгалтерии 8» (ред. 3.0) ▫️04.04.2023. Автоматизация учета лизинговой компании на платформе 1С:Предприятие ▫️12.04.2022. Новый порядок учета лизинговых операций с 2022 года в 1С:ERP и 1С:Комплексная автоматизация Дополнительно рекомендуем материалы 1С:ИТС: ▫️Лизи

1

Showing the 12 most recent of 31 posts we hold for @lector_1c. 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 — 114,539 of 1,160,990entries 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 2 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.

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.

“1С:Лекторий” (@lector_1c), 12,354 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/lector_1c.

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.