Literature — 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 20 August 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 why it has no browse page of its own yet.
Growth
29 measurements spanning 32 days, net +258. 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 18,450–18,895 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 29
Measured (UTC)
Subscribers
Change
7 Sept 2026, 07:36
18,759
-72
4 Sept 2026, 12:40
18,831
+70
2 Sept 2026, 20:37
18,761
-28
1 Sept 2026, 18:14
18,789
-55
31 Aug 2026, 16:12
18,844
+116
30 Aug 2026, 16:55
18,728
+49
29 Aug 2026, 15:34
18,679
+60
28 Aug 2026, 14:32
18,619
+16
27 Aug 2026, 14:33
18,603
+21
26 Aug 2026, 10:58
18,582
+40
25 Aug 2026, 12:49
18,542
+20
24 Aug 2026, 14:07
18,522
-4
22 Aug 2026, 19:48
18,526
-5
21 Aug 2026, 06:38
18,531
+4
20 Aug 2026, 06:58
18,527
+2
19 Aug 2026, 07:32
18,525
+1
18 Aug 2026, 10:06
18,524
-8
17 Aug 2026, 11:37
18,532
+7
15 Aug 2026, 20:15
18,525
-1
14 Aug 2026, 07:37
18,526
first reading
Engagement
67 posts held, back to 28 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 55 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
14.8%
avg views ÷ 18,759 subscribers
Avg views / post
2,770
45 posts measured
Reaction rate
1.80%
reactions ÷ views · ER floor
Posts in window
47
of 67 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 2 September 2026
Posts held
67 (28 July 2026 – 2 September 2026)
Views total
124,644
Reactions total
2,242
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 02:11 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
5s
Average length
5s
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
2,790 reactions across 55 posts, in 9 distinct kinds. The most used accounts for 58.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,638
58.7%
🔥
432
15.5%
👍
329
11.8%
😢
323
11.6%
👏
46
1.65%
🤔
10
0.358%
👎
7
0.251%
😱
4
0.143%
🤬
1
0.036%
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 65 of the 67 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 3,258 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 67 most recent posts we hold, published 28 July 2026 to 2 September 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.
Лето прошло — встречаем осень приятными новостями!
С 4 по 6 сентября участвуем в фестивале «Книжный сад», который пройдёт в честь 100-летия «Подписных изданий».
Все три дня будем ждать вас в Итальянском саду: привезём наши новинки и любимые хиты.
Заглядывайте — будем рады встрече!
Показываем переиздание легендарной серии «История цвета» Мишеля Пастуро!
В новом оформлении уже вышли четыре книги серии — «Белый», «Зеленый», «Черный» и «Желтый». Их можно заказать на нашем сайте, купить в московской книжной лавке «НЛО», а до 6 сентября — найти на ММКЯ в Гостином Дворе.
Ищите наши новинки на ММКЯ — ярмарка начнется уже завтра!
В первый день осени у нас вышли книги о том, как складывалась русская кухня, как искусство связано с политическими идеями, как историки читают прошлое и почему Лос-Анджелес так часто оказывается городом катастроф. А еще — исследование о французском учителе пушкинской эпохи, который мог стать прототипом мосье Лаббе из «Евгения Онегина», и четвертый том собрани…
«НЛО» на Московской международной книжной ярмарке
Уже завтра начинается ММКЯ, и в этом году ярмарка пройдет в Гостином Дворе. Привезем наши новинки и бестселлеры, а еще на ярмарке впервые поступят в продажу долгожданные переиздания книг Мишеля Пастуро об истории цвета — ищите их на нашем стенде F43!
В воскресенье, 6 сентября, в 13:00, вместе с «Альпиной нон-фикшн» проведем паблик-ток «Символы и мифы Франции: Жанна …
Теория и практика звука. Анатолий Рясов
Как связаны философское исследование звука и работа звукорежиссера? Почему звукозапись нельзя считать простым воспроизведением реальности? И что меняется в музыкальном производстве с появлением нейросетей?
В новом выпуске подкаста «Искусствоведение как детектив» Евгений Былина разговаривает с писателем и исследователем Анатолием Рясовым, автором книги «Едва слышный гул. Введе…
Как попасть на нашу распродажу? Заходите на Винзавод, идете прямо и справа видите Зеленый ангар и счастливых охотников за «добычей». Ждем вас сегодня здесь до 20.00 и завтра с 12.00, а также на сайте nlobooks.ru, где на все, кроме предзаказа, действует скидка 20%!
ДАРИМ КНИГУ О ВИНЕ
🍷
Вместе с издательством «Новое литературное обозрение» разыгрываем книгу Стивена Биттнера «История вина в стране царей и комиссаров» о становлении российского виноградорства и виноделия.
Условия простые:
• подписаться на артель «Беседы» и издательство «Новое литературное обозрение»;
• нажать на кнопку «Участвовать».
Победителя выберем 4 сентября в 12:00.
Удачи!
Участников: 135
Призовых мест:…
Гаражная распродажа «НЛО» стартовала!
Ждём вас в Зелёном ангаре ЦСИ Винзавод и в магазине «НЛО» в Петербурге.
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👍37❤31🔥13😢3
Showing the 12 most recent of 67 posts we hold for @nlobooks. 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.
Posts edited after publishing
@nlobooks edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
8 August 2026
Most recent edit
1 September 2026
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.
Mentions
Named by 37 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Подосокорский @podosokorsky · 29,841 Telegram ranks this channel #1 of 97 here — alongside 96 others — read 8 September 2026
по краям @admarginem · 29,862 Telegram ranks this channel #1 of 87 here — alongside 86 others — read 8 September 2026
Армен и Фёдор @armenifedor · 41,903 Telegram ranks this channel #5 of 96 here — alongside 95 others — read 29 August 2026
Arzamas @ArzamasLive · 59,295 Telegram ranks this channel #25 of 97 here — alongside 96 others — read 22 August 2026
Книжный импорт @importknig · 35,281 Telegram ranks this channel #50 of 93 here — alongside 92 others — read 2 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.
Referenced elsewhere
This handle named by sources this register does not control and did not measure — each shown exactly as found, attributed by name, dated to when it was read.
Wikipedia
2 Wikipedia articles name this handle in its article text, found by searching for a t.me link inside the article source. A citation is a notability signal, not a verification: nobody here confirmed the cited post is genuine or still says what the article quotes. Article text is CC BY-SA 4.0, Wikipedia contributors; snippets below are short excerpts.
Вишневецкий, Игорь Георгиевич(ru.wikipedia.org) “…№ 3 (41).
* ''[[Давыдов, Данила Михайлович|Данила Давыдов]]''. [https://t.me/nlobooks/6568 Микрорецензия на: Игорь Вишневецкий. Пробуждение: поэма. —…” read 23 August 2026
Горнон, Александр Георгиевич(ru.wikipedia.org) “…Умер 4 декабря 2024 года в возрасте 78 лет{{Cite web|url=https://t.me/nlobooks/4510|title=Новое литературное обозрение|website=Telegram|access…” read 23 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 7 September 2026 — this
entry's latest reading, not the date you are reading this.
“Новое литературное обозрение” (@nlobooks), 18,759 subscribers as measured 7 September 2026. Telegram Register, tgregister.com/channel/nlobooks.
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.