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 8 August 2026 and assigned it the closest of 31 fixed categories, at 55% 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
9 measurements spanning 7 days, net +121. 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 503,704–503,885 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 17:43
503,849
-15
11 Aug 2026, 18:03
503,864
+46
10 Aug 2026, 15:02
503,818
+52
9 Aug 2026, 14:15
503,766
+8
8 Aug 2026, 16:37
503,758
+5
7 Aug 2026, 20:11
503,753
+28
6 Aug 2026, 22:31
503,725
-3
6 Aug 2026, 00:42
503,728
no change
5 Aug 2026, 22:18
503,728
first reading
Engagement
69 posts held, back to 5 August 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 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
4.91%
avg views ÷ 503,849 subscribers
Avg views / post
24,700
69 posts measured
Reaction rate
1.42%
reactions ÷ views · ER floor
Posts in window
69
of 69 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 12 August 2026
Posts held
69 (5 August 2026 – 12 August 2026)
Views total
1,707,660
Reactions total
24,324
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 17:38 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
18m 11s
Average length
50s
Measured directly from 22 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
23,165 reactions across 63 posts, in 12 distinct kinds. The most used accounts for 28.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
6,636
28.6%
🤮
4,816
20.8%
❤
3,995
17.2%
👍
3,196
13.8%
🔥
1,857
8.02%
😱
1,468
6.34%
🤷♀
710
3.06%
🤬
154
0.665%
😢
145
0.626%
🎉
117
0.505%
🫡
39
0.168%
🙏
32
0.138%
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 69 of the 69 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 24,324reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 69 most recent posts we hold, published 5 August 2026 to 12 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.
Telegram Stars
Stars received
6
across the posts below
Posts paid on
5
of 69 we hold a reading for · 7%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @imnotbozhena. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 69 most recent posts we hold for this entry, published 5 August 2026 to 12 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Познакомилась тут с очень интересной девушкой. Ее зовут Наташа. Комсомолка, спортсменка, красавица. Еще хорошо поёт! Наташа заканчивает магистратуру во ВШЭ, работает в рекламном агентстве, много читает всяких умных книжек. И делится своими мыслями в канале.
А еще у нее можно прочесть о том, как попадать на крутые мероприятия и строить связи, о любимых и необычных местах в Москве, о том, что из себя представляют совр…
Уже читали новости про автогражданку? Рассказываю.
На днях Эльвира Набиуллина ясно дала понять, что пора ускорить внедрение автоматического контроля за ОСАГО через камеры на дорогах. Президент Владимир Путин согласился с этим.
Штрафы за нарушения смогут направлять на развитие общественного транспорта в регионах. Процесс идет, уже даже убедились в чистоте базы страховых данных, подконтрольной ЦБ.
Я, как добросовестн…
Плюс одна фобия. Из-за пилота, употреблявшего наркотики, в Индии чуть не разбился самолёт, сообщает The Times of India
Тест подтвердил, что командир экипажа во время полёта 4 августа был под воздействием марихуаны и утратил самоконтроль. В результате лайнер начал резкое снижение, из-за чего пострадали 24 человека. Избежать авиакатастрофы помог второй пилот.
Я в МАХ — по ссылке.
Кинотеатру в Канаде пришлось повесить нарисованный от руки постер «Человека-паука: Новый день». Из-за проблем с доставкой им не привезли ни одной оригинальной афиши, поэтому руководство попросило сотрудника нарисовать постер самостоятельно — его шедевр повесили вместо оригинала.
Я в МАХ — по ссылке.
Оказывается, рестораны Москвы теперь конкурируют не только шефскими амбициями, но и винными картами
Simple Wine News и ресторанный гид GreatList запустили Great Wine List от SWN — рейтинг винных карт, устроенный по всем правилам индустрии: 100-балльная шкала, больше полусотни критериев и оценки независимых экспертов
Судили, что характерно, вслепую: сначала карты разбирали без названных ресторанов, чтобы никто не см…
В Китае подружки невесты провели целую тактическую операцию, чтобы бабка не украла счастье молодожёнов.
В некоторых регионах Китая существует суеверие: если пожилая женщина первой пересечёт порог при входе невесты, она может «украсть» удачу и здоровье новобрачных.
Бабка на свадьбе рванула к двери, как только её приоткрыли, чтобы перехватить благословение. Но подружки невесты оказались хитрее — выманили её, захлопну…
Российские миллионеры нашли способ сэкономить на греческом ВНЖ. Через фиктивные однополые браки. Схема простая: один покупает недвижимость в Греции, второй становится его супругом, после чего оба получают ВНЖ. В итоге вместо €250 тыс. каждый тратит по €125 тыс.
Я в МАХ — по ссылке.
В Швеции можно встретить говорящие урны. Если выкинуть в них мусор, они поблагодарят, рыгнут или аппетитно почавкают. Эксперимент запустили еще в 2017 году, чтобы за счет «прикола» мотивировать не оставлять мусор и доносить его до урны. Сейчас такие есть в Стокгольме, Мальмё, Хельсингборге и не только.
Я в МАХ — по ссылке.
Новый гипотетический проект для Москва-Сити. Две башни, вырастающие из общего основания. Хотят поставить на участке рядом с будущим НЦ Россия, недалеко от Дома Дау и Capital Towers.
Я небоскребы не люблю, не понимаю, зачем они нужны в самой большой стране мира.
Я в МАХ — по ссылке.
Самый известный биохакер (шиз) Брайан Джонсон ни разу не спал ночью со своей девушкой — они даже живут в разных домах. Миллиардер поделился главными исследованиями по этому поводу. В одном из них установили, что у девушек качество сна ниже, когда они спят вместе со своим партнером, а не в одиночку. У мужчин ситуация противоположная: их сон был крепче и лучше, когда они засыпали вместе со второй половинкой. Независимо…
😁201🤮58❤37👍24🔥6🫡5😱3🤷♀2
Showing the 12 most recent of 69 posts we hold for @imnotbozhena. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Citation-graph rank
Citation-graph rank — 3,161 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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 58 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s.When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 9 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
Коза кричала @kozakrichala · 181,010 Telegram ranks this channel #1 of 88 here — alongside 87 others — read 12 August 2026
Лера Кудрявцева @lerakudryavtseva · 239,831 Telegram ranks this channel #1 of 89 here — alongside 88 others — read 11 August 2026
Кристина Потупчик @krispotupchik · 151,370 Telegram ranks this channel #2 of 94 here — alongside 93 others — read 12 August 2026
Вероника Степанова @veronikastepanova20011 · 472,958 Telegram ranks this channel #2 of 84 here — alongside 83 others — read 10 August 2026
Только никому... @spletni_tg · 188,787 Telegram ranks this channel #3 of 90 here — alongside 89 others — read 11 August 2026
Кровавая барыня @bloodysx · 1,151,837 Telegram ranks this channel #3 of 92 here — alongside 91 others — read 8 August 2026
Алёна, Блин! @neopra_blin · 156,375 Telegram ranks this channel #5 of 90 here — alongside 89 others — read 12 August 2026
ДОКТОР МЯСНИКОВ @drmyasnikov · 181,107 Telegram ranks this channel #5 of 91 here — alongside 90 others — read 12 August 2026
москоутиндер @moscowtinderr · 722,101 Telegram ranks this channel #5 of 80 here — alongside 79 others — read 8 August 2026
Super.ru @SuperRu · 198,429 Telegram ranks this channel #7 of 89 here — alongside 88 others — read 11 August 2026
СОБЧАК @ksbchk · 373,766 Telegram ranks this channel #7 of 92 here — alongside 91 others — read 10 August 2026
Микерина. Роды? Зови акушера! @mikeryna_sashaa · 191,609 Telegram ranks this channel #10 of 77 here — alongside 76 others — read 11 August 2026
История человечества @historic_ru · 240,033 Telegram ranks this channel #10 of 88 here — alongside 87 others — read 11 August 2026
Виктория Боня @bonyaviktorya · 626,029 Telegram ranks this channel #11 of 78 here — alongside 77 others — read 8 August 2026
Доктор Садовская @doctor_sadovskaya · 159,046 Telegram ranks this channel #12 of 84 here — alongside 83 others — read 12 August 2026
Лука Ебков @luka_ebkov · 429,384 Telegram ranks this channel #12 of 90 here — alongside 89 others — read 10 August 2026
СИГНАЛ @ssigny · 451,362 Telegram ranks this channel #12 of 88 here — alongside 87 others — read 10 August 2026
YOBAJUR @yobajur · 189,840 Telegram ranks this channel #14 of 84 here — alongside 83 others — read 11 August 2026
Ещё главу и спать | Литература @knigi_literatura · 263,675 Telegram ranks this channel #14 of 92 here — alongside 91 others — read 10 August 2026
Ирина Хакамада @chillosophy · 149,454 Telegram ranks this channel #15 of 93 here — alongside 92 others — read 12 August 2026
Тина Канделаки @tikandelaki · 313,575 Telegram ranks this channel #15 of 95 here — alongside 94 others — read 10 August 2026
ЮЛИЯ МЕНЬШОВА @JuliaMenshovaJulia · 361,530 Telegram ranks this channel #15 of 91 here — alongside 90 others — read 10 August 2026
Дорогая Хурма @expensive_hurma · 151,923 Telegram ranks this channel #17 of 89 here — alongside 88 others — read 12 August 2026
Беспощадный пиарщик @prbezposhady · 152,041 Telegram ranks this channel #17 of 92 here — alongside 91 others — read 12 August 2026
This channel appears in 218 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
One domainthis channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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.
Волохов, Михаил Игоревич(ru.wikipedia.org) “…|archive-date=2023-11-10 |url-status=live }}{{Cite web|url=https://t.me/imnotbozhena/51363|title=НЕБОЖЕНА|website=Telegram|description=Особенно следует…” read 9 August 2026
Игра в жмурики(ru.wikipedia.org) “…|archive-date=2023-11-10 |url-status=live }}{{Cite web|url=https://t.me/imnotbozhena/51363|title=НЕБОЖЕНА|website=Telegram|description=Особенно следует…” read 9 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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“НЕБОЖЕНА” (@imnotbozhena), 503,849 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/imnotbozhena.
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.