Local community — 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 27 September 2026 and assigned it the closest of 31 fixed categories, at 76% 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 why it has no browse page of its own yet.
Growth
4 measurements spanning 55 days, net +2. 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 101–103 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
1 Oct 2026, 11:02
103
+1
12 Sept 2026, 06:17
102
+1
9 Aug 2026, 10:30
101
no change
7 Aug 2026, 10:55
101
first reading
Engagement
8 posts held, back to 11 May 2023 — 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 8 posts for this entry, the most recent from 31 October 2024. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
17s
Average length
17s
Measured directly from 1 video 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
40 reactions across 8 posts, in 10 distinct kinds. The most used accounts for 27.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🤬
11
27.5%
😱
8
20.0%
🤡
6
15.0%
👍
5
12.5%
🍾
4
10.0%
👌
2
5.00%
❤
1
2.50%
🎉
1
2.50%
😢
1
2.50%
🤔
1
2.50%
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 8 of the 8 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 40 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 11 May 2023 to 31 October 2024, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
🆘‼️ОСТОРОЖНО МОШЕННИК!!!!!!!!!!
Станислав Перетяткин, живёт в Торревьехе.Предлагает инвестировать в недвижимость, работает с банками и фондами, обещает хороший доход и не возвращает деньги. Пользуется тем, что нерезиденты не могут положить деньги на счёт. Рассказывает грустную историю, что болеет раком. Работал с Натальей Халиной. Очень хорошо втирается в доверие. В процессе мошенничества делает поддельные документы,…
Внимание! МОШЕННИКИ! Предоставляю вашему внимание двух "помощниц", которые "помогли" с ситой. Сегодня мы приехали в Аликанте , а нас в списке нет. Две эти красавицы кинули наши все номера в блок. Схема стандартная, может и сами виноваты, поверили землякам! Помогите распространить, что бы предупредить всех о очень непорядочных людях!
🤷♂️Один из специалистов в Аликанте
Отзыв:
Хочу рассказать о своем неблагоприятном опыте от контактирования с некоторыми так называемыми специалистами! Так вот, крайне не рекомендую обращаться к данному товарищу.
Гоша Парикмахер. Активно продвигает свои услуги по
окрашиванию в Аликанте, заявляет себя опытным мастером с кучей довольных клиентов. По факту, отвечает крайне выборочно и долго. Пишет сначала, что не берет …
❗️Развод❗️
👉 АРЕНДА МАШИН
Запомните голос этого человека, просит предоплату 200 долларов и обещает что машина будет через 10 минут) аккаунты созданы 2 недели назад..
https://t.me/xxxcarsx
_____
👮♂️Если вы столкнулись с обманом, напишите нам!
_____
👉 @botmorra
👍1
Showing the 8 most recent of 8 posts we hold for @chernyyspisokispaniya. 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 1 October 2026 — this
entry's latest reading, not the date you are reading this.
“🌴Чёрный список АЛИКАНТЕ и Испания🌴” (@chernyyspisokispaniya), 103 subscribers as measured 1 October 2026. Telegram Register, tgregister.com/channel/chernyyspisokispaniya.
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.