Film & TV — 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 20 September 2026 and assigned it the closest of 31 fixed categories, at 83% 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
11 measurements spanning 87 days, net +8. 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 572–609 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
2 Nov 2026, 10:36
584
-2
27 Oct 2026, 09:54
586
-8
20 Oct 2026, 12:19
594
-8
12 Oct 2026, 23:39
602
-1
3 Oct 2026, 05:56
603
-2
18 Sept 2026, 04:36
605
+1
30 Aug 2026, 13:13
604
+12
23 Aug 2026, 06:47
592
+12
15 Aug 2026, 18:56
580
+4
8 Aug 2026, 03:30
576
no change
7 Aug 2026, 19:12
576
first reading
Engagement
6 posts held, back to 23 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 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 6 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
45s
Average length
15s
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
48 reactions across 6 posts, in 3 distinct kinds. The most used accounts for 58.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
28
58.3%
custom 5242351426964830850
10
20.8%
custom 5244962573807270294
10
20.8%
Custom emoji. 2 of the rows above are 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 counts beside them are 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 6 of the 6 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 48 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 23 July 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.
«ЭЙНШТЕЙН И МАРГАРИТА» 🎭
Полтора часа пронзительной драмы, тайной страсти и рокового выбора на фоне уходящей эпохи. Смогут ли два сильных человека отпустить друг друга, когда весь мир рушится на части? В этой трагической неизбежности и кроется главная загадка любви. Прикоснуться к великой тайне 1945 года, прожить этот вечер вместе с героями и прочувствовать каждую секунду.
Звездный состав:
Алексей Серебряков, Алён…
Трейлер спектакля «Эйнштейн и Маргарита» 🎬✨
1945 год. Принстон. Последний вечер перед расставанием навсегда. Великий гений и его единственная любовь. Роковая тайна, неизбежность разлуки и чувство, которое оказалось сильнее времени.
🎭 В главных ролях: Алексей Серебряков и Алёна Хмельницкая.
🎟️ Смотрите трейлер и забирайте лучшие места [ПО ССЫЛКЕ]
Почувствуйте атмосферу: трейлер спектакля «Буду сниматься в кино» 🎭
«Буду сниматься в кино» — это трогательная, невероятно смешная и глубокая история о семье, прощении и попытке собрать разбитые отношения заново.
Голливудский сценарист, переживающий кризис, и 19-летняя дочь, которую он не видел более десяти лет. Она приехала «сниматься в кино», но на самом деле — чтобы просто посмотреть отцу в глаза и найти ответов…
«Я хочу сниматься в кино. Но дело совсем не в Голливуде…» 🎭
Когда за легким юмором скрывается пронзительная история о любви, застрявших эмоциях и попытке найти путь друг к другу.
Лирическая комедия «Буду сниматься в кино» — это 2 часа чистого удовольствия, смеха и легкой грусти.
На сцене — невероятный актерский состав: Андрей Смоляков, Евгения Дмитриева и Мария Мацель.
Если вы искали повод сходить в театр на что-т…
Собрали постановки, которые станут главными точками вашего культурного маршрута.
Каждое событие - отдельный мир: от искренней поэзии до голливудской иронии.
🎭 Психопаты | 24.08 и 25.08
➡️ [Выбрать места]
🎭 Ищу мужа | 26.08
➡️ [Выбрать места]
🎭 Папа | 24.07 и 28.08
➡️ [Выбрать места]
🎭 Одни во вселенной | 30.08
➡️ [Выбрать места]
🎭 Буду сниматься в кино | 02.09
➡️ [Выбрать места]
🎭 Поединок | 03.09
➡️ [Выбрать м…
Showing the 6 most recent of 6 posts we hold for @TicketToShow. 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.
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.
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 2 November 2026 — this
entry's latest reading, not the date you are reading this.
“TTS | БИЛЕТЫ И АФИША” (@TicketToShow), 584 subscribers as measured 2 November 2026. Telegram Register, tgregister.com/channel/TicketToShow.
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.