Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 28% 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.
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.
Views per post sit far above this size band
6,930 average views per post against 8,320 subscribers — an engagement rate of 83.3%. Across the 31,022 registered channels in the same cohort — 3,163–9,999 subscribers, posting mainly in Russian — the middle half sit between 5.92% and 21.7%, with a median of 11.6%.
What this was computed from
Window
30 days (31 July 2026 – 30 August 2026)
Posts measured
28 of 28 published in the window (0 exact, 28 rounded by Telegram)
Views totalled
194,090
Mature posts only
83.3% over 28 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 30 August 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.
Growth
8 measurements spanning 22 days, net -58. 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 8,208–8,400 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
29 Aug 2026, 22:33
8,320
+31
26 Aug 2026, 22:12
8,289
+29
24 Aug 2026, 07:23
8,260
+30
20 Aug 2026, 09:36
8,230
-35
17 Aug 2026, 18:47
8,265
-20
14 Aug 2026, 21:16
8,285
-92
8 Aug 2026, 06:42
8,377
-1
7 Aug 2026, 14:16
8,378
first reading
Engagement
43 posts held, back to 27 March 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 21 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
83.3%
avg views ÷ 8,320 subscribers
Avg views / post
6,930
28 posts measured
Reaction rate
2.38%
reactions ÷ views · ER floor
Posts in window
28
of 43 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 22 August 2026
Posts held
43 (27 March 2026 – 22 August 2026)
Views total
194,090
Reactions total
4,617
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
28 Aug 2026, 17:58 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
6m 09s
Average length
1m 32s
Measured directly from 4 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
8,268 reactions across 43 posts, in 57 distinct kinds. The most used accounts for 23.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,974
23.9%
😁
1,463
17.7%
🤣
1,281
15.5%
👍
997
12.1%
🔥
742
8.97%
🤬
410
4.96%
🤡
399
4.83%
💯
211
2.55%
😢
87
1.05%
🤝
85
1.03%
🫡
71
0.859%
💊
56
0.677%
❤🔥
45
0.544%
😨
33
0.399%
😱
33
0.399%
✍
31
0.375%
👎
30
0.363%
😭
30
0.363%
💩
27
0.327%
🤪
27
0.327%
37 further kinds
236
2.85%
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 43 of the 43 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 8,268reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 43 most recent posts we hold, published 27 March 2026 to 22 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.
📱 Apple решила сократить более 200 сотрудников, работающих над Siri и Vision Pro. Компания подтвердила, что проводит перестройку работы некоторых подразделений.
Ну вы поняли? Даже работая в одной из крупнейших компаний мира, работая в одном из основных направлений, вы в любой момент можете быть просто уволены по причине "перестройка подразделений". Вас даже не перенаправят в другие команды, вас просто нахуй уволят 🚬…
Чуточку откровенный пост ☔️
Знаете гайз, за несколько месяцев релокации как-то эмоции подутихли, хотя всё ещё остаётся некоторая злость на все эти обстоятельства. Злость от собственного небезразличия к России. Я люблю Россию, мне очень нравится моя страна, в ней бесконечное количество прекрасных вещей. И когда ты планировал всю жизнь прожить в своей стране, но тебя буквально выдавливают из неё — от этого начинаешь з…
Забавное наблюдение: никто из тех, кому не интересны новости, не пишет просто "мне не интересно читать новости".
Они пишут:
- "у всех релокантов такой синдром дауна поливать родную страну гавном"
- "ты трясёшься с каждой новости, хотя на самом деле у тебя просто брызжет слюна и ненависть к стране"
- "канал скатился в хуйню, автор скатился"
То есть абсолютно потребительское отношение. Мол либо давай нам качественный…
Ну что, мои маленькие любители качественного айти контента? Вы готовы? 🥰
Делаю полный гайд на создание и продвижение LinkedIn профиля — основного инструмента для поиска удалённой работы с зарплатой в валюте. Покажу как регистрировать аккаунт, как наполнять, как вести, чтобы не ловить баны и получать приглашения на собеседования 📕
У нас в приватном сообществе первый запуск хакатона 😎
В чём суть? Можно попасть в команду таких же новичков как ты, вместе и сообща реализовать программный продукт, получить опыт работы в команде, в конце лучшим проектам даём денежные призы и бесплатные подписки на сообщество. Также можно поучаствовать как зритель, посмотреть на разработку со стороны 😊
Уникальная возможность получить опыт. Успевайте присоединиться!…
Россияне заплатят 136 млрд 🔍 рублей технологического сбора — вся электроника в стране сильно подорожает, считают аналитики.
С 1 декабря производители и импортёры смартфонов, ноутбуков, ПК и другой электроники начнут платить технологический сбор. Размер технологического сбора никак не регулируется, государство само вольно выбирать сколько брать дани с желающих купить технику.
Что-то мне автомобильный утильсбор вспом…
Тем временем на суверенном VK Видео просмотры на некоторых моих роликах пробивают астрономические 50 единиц. В то время как на вонючем западэнском богохульном YouTube это десятки тысяч просмотров.
Я не понимаю, в чём такая великая проблема в VK Видео сделать адекватную рекомендательную систему. Экспертиза в стране вполне имеется — в том же Авито система рекомендаций в рот даёт множеству зарубежных аналогов.
В 2025-…
За перемещением КАЖДОГО россиянина могут начать следить в реальном времени — Минтранс планирует ввести систему по сбору данных о поездках граждан. Эти меры направлены на повышение безопасности передвижений.
А на небе только и разговоров, что о безопастности.
😁67🤡31😭5🤬3🤯3❤1👍1🥱1
Showing the 12 most recent of 43 posts we hold for @nilchanpub. 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.
Handles this channel named that no longer answer
Dead references
3
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
3
vacant every time we have ever looked
@nilchanpub named 3 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@andreyvictoroff named in 4 posts, 8 August 2026 – 11 August 2026
@elena_lazarevvay named in 4 posts, 8 August 2026 – 11 August 2026
@msk_yuri named in 4 posts, 8 August 2026 – 11 August 2026
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 29 August 2026 — this
entry's latest reading, not the date you are reading this.
“nilchan pub” (@nilchanpub), 8,320 subscribers as measured 29 August 2026. Telegram Register, tgregister.com/channel/nilchanpub.
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.