Education — 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 15 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 19 comparable posts for this entry, running 22 July 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @ispanki — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
25 measurements spanning 95 days, net +105. 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 2,577–2,748 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
9 Nov 2026, 17:09
2,702
-1
6 Nov 2026, 19:58
2,703
-6
3 Nov 2026, 20:56
2,709
-7
31 Oct 2026, 18:20
2,716
-5
28 Oct 2026, 19:31
2,721
-3
25 Oct 2026, 16:44
2,724
-4
22 Oct 2026, 20:08
2,728
+7
19 Oct 2026, 13:40
2,721
-4
16 Oct 2026, 23:50
2,725
+6
13 Oct 2026, 21:17
2,719
-3
8 Oct 2026, 13:00
2,722
-6
1 Oct 2026, 20:38
2,728
+42
16 Sept 2026, 06:56
2,686
-2
12 Sept 2026, 19:21
2,688
+66
8 Sept 2026, 10:58
2,622
+11
3 Sept 2026, 05:49
2,611
-9
31 Aug 2026, 03:27
2,620
-5
28 Aug 2026, 03:42
2,625
+8
24 Aug 2026, 23:43
2,617
-1
21 Aug 2026, 17:45
2,618
first reading
Engagement
24 posts held, back to 22 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 2 pages 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 24 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
157 reactions across 20 posts, in 7 distinct kinds. The most used accounts for 56.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
88
56.1%
❤
37
23.6%
❤🔥
10
6.37%
🥰
9
5.73%
🔥
8
5.10%
⚡
3
1.91%
🍓
2
1.27%
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 24 of the 24 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 208 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 24 most recent posts we hold, published 22 July 2026 to 7 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.
Advertising
Ad load
4.17%
1 of 24 posts carry an ad marker
Regulatory tokens
1
posts carrying an erid · 1 distinct token
Median views · ads
308
over 1 measured post
Median views · rest
237
over 23 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
5jtCeReNx12oajzfzmihJ27
1
26 July 2026
26 July 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 24 most recent posts we hold, published 22 July 2026 to 7 August 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
😍😍😍😍😍
Ты мне нравишься - me gustas, me agradas. - ме густас, ме аградас.
Я тебе нравлюсь - Te gusto - Те густо
Пожелание сладких снов - te deseo dulces sueños. - те десео дульсес суэньос.
Я по тебе скучаю - te echo de menos, te extraño. - те эчо де менос, те экстраньо.
Думаю о тебе - pienso en ti - пьенсо эн ти
Ты великолепен - eres magnifico - эрес магнифико
Я чувствую себя чужим (потерянным) без тебя - soy un extr…
🇪🇸🇪🇸🇪🇸
В испанском языке достаточно слов, кототорые, вроде очень похожи, только род у них разный. А от рода-то в данном случае и зависит значение.
la cólera – ярость y el cólera – холера
el capital – капитал la capital – столица
el frente – фронт la frente – лоб
el orden – порядок la orden – приказ
el guardia – сторож la guardia – гвардия
el calavera – гуляка la calavera – череп
el cólera – холера la cólera – яро…
🇪🇸 Испания становится ближе!
В этой подборке собраны Telegram-каналы о жизни в Испании, испанском языке, культуре, путешествиях, переезде и многом другом.
🔗 Ссылка на папку:
https://t.me/addlist/myFxsIzR9_s3NGZi
Приятного знакомства с подборкой!
📱 Ведёте канал? Присоединяйтесь к следующим подборкам.
🇪🇸🇪🇸🇪🇸🇪🇸🇪🇸🇪🇸🇪🇸
УНИВЕРСАЛЬНЫЕ ФРАЗЫ ДЛЯ ЛЮБОГО РАЗГОВОРА
de verdad дэ бэрдАд - на самом деле
tal o cual таль о куАль - такой-то такой-то
lo que necesitas ло кэ нэсэсИтас - то, что тебе нужно
en vista de эн бИста кэ - ввиду того, что
aparte de апАртэ дэ - не считая
en todo sentido de la palabra эн тодо сэнтИдо дэ ла палАбра - в полном смысле этого слова
por todas partes пор тОдас пАртэс - повсюду
eso es todo Эсо эс т…
Изучаем испанский язык и погружаемся в культуру Испании! 🇪🇸
🇪🇸 Испанские истории на каждый день
Не знаешь, что почитать на испанском? Тебе сюда 👉Здесьтебя ждёт серия коротких, живых и простых историй, идеально подходящих для начинающих — с разбором на русском. Подписывайся и читай без стресса!
🇪🇸 Испанский с Алисой💋
Испанский язык для общения с носителями НА РАВНЫХ. Хватит тратить время на скобочки.
Здесь вход в бе…
🇪🇸🇪🇸🇪🇸🇪🇸🇪🇸
estar en casa - быть дома
estar sano – быть здоровым
estar enfermo – быть больным
estar resfriado — быть простуженным
estar bien/mal - чувствовать себя хорошо/плохо
estar libre – быть свободным
estar ocupado – быть занятым
estar triste/alegre (как временное состояние) - быть грустным/веселым
estar contento – быть довольным
estar feliz — быть счастливым
estar casado/a – быть женатым (замужем)
estar cansado…
Preposiciones de lugar
detrás дэтрАс - сзади
delante дэлАнте - перед
debajo дэбАхо - под
arriba арИба - над
entre Энтрэ - между
a la izquierda а ла искиЭрда - слева
a la derecha а ла дэрЭча – справа
🇪🇸🇪🇸🇪🇸
Buenos días буЭнос дИяс - Доброе утро
Buenаs tardes буЭнас тАрдэс - Добрый день
Buenas noches буЭнас нОчес - Спокойной ночи
Adios адьЁс - Досвидания
Hasta luego Аста луЭго - До встречи
Hasta mañana Аста маньЯна - До завтра
¿Cómo estás? кОмо эстАс - Как твои дела?
Muy bien - ¿Y tú? мУи бьен и ту - Очень хорошо, а у тебя?
Perdoname пердОнаме - Извини меня
¿Hablas ruso? Аблас рУсо - Ты говоришь по-русски?
¿Habl…
🇪🇸🇪🇸🇪🇸
Футбольные термины на испанском
¿Cual es el resultado?- Какой счёт?
el penal- пенальти
Corre!-Беги!
el arquero(Латинская Америка)- вратарь
el portero - вратарь
el arco- ворота
el equipo contrario-команда противников
Defender-защищать
atajar-ловить
el foul-фол
la falta-фол
atacar-атаковать
una patada inicial-введение мяча в игру
el aplauso- аплодисменты
una tarjeta roja-красная карточка
una tarjeta amarill…
Showing the 12 most recent of 24 posts we hold for @ispanki. 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
Named by 3 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.
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.
Испанский язык! @espanol_spanish_castellano · 43,668 Telegram ranks this channel #37 of 97 here — alongside 96 others — read 28 August 2026
Мой Испанский! @miespanol · 18,759 Telegram ranks this channel #44 of 95 here — alongside 94 others — read 5 October 2026
Аудиокурсы Langme @langme_ru · 38,237 Telegram ranks this channel #60 of 97 here — alongside 96 others — read 31 August 2026
Esparusski | Испанский язык @esparusski · 19,278 Telegram ranks this channel #63 of 97 here — alongside 96 others — read 3 October 2026
Настя про испанский 🪭 ESPALINGO® @espalingo_castellano · 19,160 Telegram ranks this channel #81 of 96 here — alongside 95 others — read 30 September 2026
This channel appears in 5 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 9 November 2026 — this
entry's latest reading, not the date you are reading this.
“🇪🇸 Испанский язык español @ispanki” (@ispanki), 2,702 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/ispanki.
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.