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 24 September 2026 and assigned it the closest of 31 fixed categories, at 79% 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
9 measurements spanning 84 days, net -11. 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 189–204 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
30 Oct 2026, 13:29
191
-2
23 Oct 2026, 06:35
193
-1
16 Oct 2026, 07:36
194
-1
8 Oct 2026, 12:54
195
-1
28 Sept 2026, 05:56
196
-4
14 Sept 2026, 04:39
200
-1
7 Sept 2026, 06:18
201
-1
8 Aug 2026, 11:20
202
no change
7 Aug 2026, 13:58
202
first reading
Engagement
7 posts held, back to 25 August 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 7 posts for this entry, the most recent from 5 September 2025. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
2m 28s
Average length
49s
Measured directly from 3 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
70 reactions across 7 posts, in 7 distinct kinds. The most used accounts for 48.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
34
48.6%
👍
15
21.4%
🔥
15
21.4%
👏
2
2.86%
💔
2
2.86%
custom 5219855165657477815
1
1.43%
💯
1
1.43%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
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 7 of the 7 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 70 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 7 most recent posts we hold, published 25 August 2025 to 5 September 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Вчера мир моды потерял титана. Ушел Джорджио Армани — человек, который переодел современность. Ему было 91.
Он построил целую империю на своем безупречном вкусе и показал, что настоящая сила не в брендах на показ, а в сдержанности и элегантности.
Сегодня про самую ходовую позицию в гардеробе - джинсы.
Какую форму выбрать, рассказала в видео.
Очень частая проблема — джинсы теряют форму и вытягиваются колени.
Почему так происходит ?
Идеальный состав для долговечных джинс выглядит так:
· 98-100% хлопок — это эталон. Такие джинсы (например, сырой деним или модели от японских брендов) практически не тянутся и держат форму. Но они требуют привыкания к жесткости…
Если вы подписаны на меня, значит у вас точно будут вещи в шкафу подходящие к 1 сентября )
Прилагаю несколько простых, но не скучных формул!
Но для начала, почему стоит приодеться формально для этого праздника ?
• Вы главная опора и фон в кадре своего школьника. Дети живут в жизни, где границы между буднями и праздниками размыты. Одеваясь особенно (формально) – вы буквально показываете «ты и твой старт важен, этот…
Девочки, нужно срочно поговорить о трендах. Опять. 👯♀️
Смотрю я на эти витрины, а там сплошные: «носи это, если не хочешь выглядеть как мамонт». И честно? У меня уже нервный тик начинается.
Каждый сезон нам пытаются впарить то бананы, то каре-боб, то джинсы с заниженной талией (привет, 2000-м, мы вас помним и не очень-то хотим обратно).
Так что ловите краткий разбор полётов от меня.
Следовать трендам – это как е…
Несколько позиций из Sela и Zarina к которым стоит присмотреться.
Особенно к этому пальто из искусственной кожи! Себе бы его забрала 🥺
Пальто, куртка, куртка кожзам, куртка с кулиской
Девочки! А что если не тренч?
Например, многие мнутся, не всегда нравятся модели, трудно найти подходящую или просто потому что эта позиция есть у всех?
5 вариантов верхней одежды на осень.
С чем носить Капри?
Кроме обтягивающих капри, есть еще варианты широких - мне нравятся и те, и те. Под настроение.
Но длина коварная, может украсть визуально немного роста, если кажется что вещь приземляет, играйте с длинами и надевайте каблук или танкетку, чуть приподнимая себя.
На фото актуальные варианты стилизации.
Берем на заметку 📝
Я буду носить осенью с тренчем длины до колено и балетками.
P.s. Очень класс…
❤3🔥2
Signed Валентина Егорова
Showing the 7 most recent of 7 posts we hold for @valentinas_day. 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.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
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 October 2026 — this
entry's latest reading, not the date you are reading this.
“Дьявол постит Pravdu” (@valentinas_day), 191 subscribers as measured 30 October 2026. Telegram Register, tgregister.com/channel/valentinas_day.
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.