Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 78% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Growth
62 measurements spanning 97 days, net +172. 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 19,346–19,760 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
11 Nov 2026, 23:15
19,712
+3
10 Nov 2026, 02:21
19,709
+33
8 Nov 2026, 16:56
19,676
+31
7 Nov 2026, 13:08
19,645
+38
6 Nov 2026, 15:56
19,607
+136
5 Nov 2026, 16:09
19,471
+77
4 Nov 2026, 17:45
19,394
-3
3 Nov 2026, 20:30
19,397
-5
2 Nov 2026, 21:34
19,402
-4
1 Nov 2026, 18:48
19,406
-3
31 Oct 2026, 19:58
19,409
-6
30 Oct 2026, 20:50
19,415
+2
29 Oct 2026, 23:48
19,413
+4
29 Oct 2026, 00:30
19,409
-4
28 Oct 2026, 02:50
19,413
-2
27 Oct 2026, 00:29
19,415
-1
26 Oct 2026, 03:56
19,416
-3
25 Oct 2026, 04:06
19,419
-3
24 Oct 2026, 04:16
19,422
-3
23 Oct 2026, 00:59
19,425
first reading
Engagement
28 posts held, back to 20 July 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 75 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
21.2%
avg views ÷ 19,712 subscribers
Avg views / post
4,190
8 posts measured
Reaction rate
2.40%
reactions ÷ views · ER floor
Posts in window
8
of 28 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 6 November 2026
Posts held
28 (20 July 2026 – 6 November 2026)
Views total
33,480
Reactions total
805
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 15:59 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
11m 42s
Average length
59s
Measured directly from 12 videos 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
2,097 reactions across 28 posts, in 19 distinct kinds. The most used accounts for 48.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,026
48.9%
🔥
527
25.1%
👍
178
8.49%
🍾
113
5.39%
💯
60
2.86%
😱
40
1.91%
❤🔥
31
1.48%
😍
31
1.48%
🎉
25
1.19%
😁
16
0.763%
🥰
14
0.668%
🙈
13
0.62%
👏
7
0.334%
🤩
5
0.238%
⚡
4
0.191%
👌
3
0.143%
🤔
2
0.095%
💔
1
0.048%
🤝
1
0.048%
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 28 of the 28 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 2,097 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 28 most recent posts we hold, published 20 July 2026 to 6 November 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
Telegram’s own ‘edited’ marker: 1 of 8 posts held from the last 30 days (12.5%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Сколько всего я наслушалась, какой я «поросенок» 🤭
С кем не бывает)) Но почему-то на себя все внимание перетянула именно стеклянная витрина, много было рекомендаций заклеить пленкой. Скрыть с глаз и все…
По такой же логике многие закупаются одинаковыми органайзерами от пола до потолка. Но прятать лишнее нет никакого смысла.
Тут мы в итоге вынесли несколько пакетов выбросить/отдать. Это ключевое!
Перевесили всю пл…
Ставьте дату в календари и ничего не планируйте на 9.11 ❤️🔥
Мы с Аидой запланировали офлайн встречу с читателями в магазине «Читай-город», ТЦ Европейский.
Кого ждать? :-)
Регистрация по ссылке: https://www.chitai-gorod.ru/events/event/a-u-vas-vse-v-poryadke
Для всех у кого уже есть моя книга «Порядочные люди», я дополнила страничку с QR кодом внутри книги визуальным рядом ❤️🔥
Теперь суть текста будет значительно понятнее:
⚡️добавился ваш любимый формат до/после для некоторых тезисов;
⚡️легкие задания для расхламления в виде рандомных карточек каждый день;
⚡️ возможность задать вопрос
Кстати, на электронную версию сейчас действует специальное предложение, QR код там т…
Мне сегодня 42 🦩
По моей стойке в детстве говорили, что точно стану директором. Стала :-)
Меня окружают невероятно классные люди, друзья и команда. Очень вас люблю ❤️🔥
В этом году вышла моя книга, а проекты взлетели на новый уровень, я как никогда близка к своей мечте которую вынашиваю уже больше 6 лет 🚀 Заходите позалипать: https://lentamethodproject.ru/anketa/garderob
Проколола уши. Даже дважды. Тоже детская м…
В последнее время я очень много работаю с нейросетями. И чем глубже погружаюсь в эту тему, тем чаще встречаю громкие обещания. Скоро ИИ сам будет проектировать шкафы, интерьеры, планировки и даже здания. Быстро, красиво и практически без участия человека.
Но меня смущает один момент. Нейросети обучаются на огромных массивах информации, среди которой немало красивых, эффектных, но совершенно непродуманных дизайнерски…
Всем привет, моя подруга делает один интересный городской проект, для которого нужен небольшой опрос. Команда изучает, как семьи проводят свободное время: куда ходят с детьми, как выбирают и кто в семье на самом деле решает.
Опрос анонимный, занимает около 20 минут. Правильных ответов нет, нужен ваш реальный опыт.
Ссылка: https://yandex.ru/poll/FndF7miVLnN5rm76ejqpe3
Буду очень признательна за помощь!)
Профессия организатор хранения — бесплатный прямой эфир 15 октября
Думаете о профессии, уже решили её освоить или работаете организатором и хотите больше заказов? Приходите на открытый эфир.
Мы с Катей Карауловой работаем по-разному: я почти сразу ушла в проектирование мебели и люблю дистанционную работу, а Катя активно практикует выездные организации и делает замеры сама. Покажем оба пути, чтобы вы выбрали свой.
…
Подписчица поделилась магазином, который возит русские книги в Европейские страны:
Вот прямая ссылка на мою
А на Озон сейчас самая лучшая стоимость https://ozon.ru/t/gmLPR4s
Когда мне будут говорить о вреде пластиковых емкостей для сыпучки и выделении микро пластика в пищу…
А вы выбрали свои самые идеальные баночки? Какие они? Стекло/пластик? Какой формы? Поделитесь фото :-)
Showing the 12 most recent of 28 posts we hold for @Lt_recommend. 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.
Posts recorded as deleted after publishing
We recorded 1 post on @Lt_recommend as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
19 August 2026
Most recent seen missing
19 August 2026
Median time before seen missing
5 days
Seen missing in the last 30 days
0
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 1 October 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Порядок Тайм. Алина Ныркова @poryadoktime · 28,375 Telegram ranks this channel #2 of 79 here — alongside 78 others — read 13 September 2026
Лёгкий быт с Аидой Prodom @aidaprodom · 317,667 Telegram ranks this channel #3 of 77 here — alongside 76 others — read 10 August 2026
УБОРКА с Аленой. Дом будет чистый @uborka_alena · 52,929 Telegram ranks this channel #17 of 64 here — alongside 63 others — read 9 September 2026
ЛЕТНЕЕ УТРО | Letneeutro @Letneeutro_channel · 47,705 Telegram ranks this channel #25 of 68 here — alongside 67 others — read 26 August 2026
Шелуша Фуд | @shelusha_food | Маша Шелушенко @shelusha_food · 319,233 Telegram ranks this channel #26 of 82 here — alongside 81 others — read 10 August 2026
Готовь, как Глыва @ya_glyva · 20,517 Telegram ranks this channel #33 of 81 here — alongside 80 others — read 26 September 2026
Заготовки с Шелушей @zagotovki_welldone · 31,080 Telegram ranks this channel #47 of 86 here — alongside 85 others — read 6 September 2026
Канал «Дом быта» @dmbt_media · 45,797 Telegram ranks this channel #55 of 77 here — alongside 76 others — read 28 August 2026
Екатерина Шрейнер | SchreinerKate | Психолог @schreinerkate_life · 64,262 Telegram ranks this channel #58 of 80 here — alongside 79 others — read 21 August 2026
КАК ЖИВУТ ДРУГИЕ. Оля Качанова @kakzhivutdrugie · 66,542 Telegram ranks this channel #60 of 75 here — alongside 74 others — read 21 August 2026
Дарья Черненко | Меню недели 🍏 | Кулинарная школа @Dasha_Chernenko · 91,835 Telegram ranks this channel #63 of 90 here — alongside 89 others — read 17 August 2026
doctor_annamama @doctor_annamama · 82,264 Telegram ranks this channel #87 of 90 here — alongside 89 others — read 18 August 2026
This channel appears in 12 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“Лентаметод: хранение и мебель” (@Lt_recommend), 19,712 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/Lt_recommend.
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.