https://youtu.be/XpoJLxy83Mw?si=28ATH6sfcn7epO8U
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Channel
@NazarenkoHistory
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Cite this entry
17,221subscribers
+1,973 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1002273088575 |
|---|---|
| Type | Channel |
| Username | @NazarenkoHistory |
| Description | Это канал историка, который рассказывает истории об истории. Доктор исторических наук, профессор, заведующий кафедрой источниковедения истории России Института истории СПбГУ, член-корреспондент Академии военных наук. Для личных обращений @Istkirbornaz |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 6 November 2026 |
| Measurements held | 63 |
| Confirmed unchanged | 1 time, most recently 6 November 2026 |
| On Telegram | t.me/NazarenkoHistory |
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 10 September 2026 and assigned it the closest of 31 fixed categories, at 96% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Nov 2026, 01:19 | 17,221 | +7 |
| 5 Nov 2026, 03:16 | 17,214 | +17 |
| 3 Nov 2026, 23:45 | 17,197 | +61 |
| 3 Nov 2026, 02:17 | 17,136 | +23 |
| 2 Nov 2026, 05:18 | 17,113 | +14 |
| 1 Nov 2026, 08:28 | 17,099 | +10 |
| 31 Oct 2026, 05:01 | 17,089 | +9 |
| 30 Oct 2026, 05:48 | 17,080 | +9 |
| 29 Oct 2026, 03:58 | 17,071 | +4 |
| 28 Oct 2026, 01:45 | 17,067 | +16 |
| 27 Oct 2026, 01:16 | 17,051 | +2 |
| 26 Oct 2026, 00:54 | 17,049 | +15 |
| 24 Oct 2026, 21:50 | 17,034 | +2 |
| 23 Oct 2026, 19:27 | 17,032 | +10 |
| 22 Oct 2026, 22:45 | 17,022 | +24 |
| 21 Oct 2026, 19:09 | 16,998 | +17 |
| 20 Oct 2026, 14:34 | 16,981 | +15 |
| 19 Oct 2026, 16:47 | 16,966 | +35 |
| 18 Oct 2026, 17:20 | 16,931 | +36 |
| 17 Oct 2026, 14:07 | 16,895 | first reading |
85 posts held, back to 2 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 62 pages of Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 6 November 2026 |
|---|---|
| Posts held | 85 (2 August 2026 – 6 November 2026) |
| Views total | 99,500 |
| Reactions total | 5,345 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 16:13 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.
Lifetime counters from Telegram’s own channel header, read 6 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
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.
22,825 reactions across 83 posts, in 31 distinct kinds. The most used accounts for 59.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 13,617 | 59.7% | |
| 🔥 | 3,528 | 15.5% | |
| ❤ | 2,504 | 11.0% | |
| 💯 | 769 | 3.37% | |
| 😁 | 694 | 3.04% | |
| 🤔 | 289 | 1.27% | |
| ✍ | 225 | 0.986% | |
| 😢 | 216 | 0.946% | |
| custom 5305732620129149365 | 202 | 0.885% | |
| 🤣 | 177 | 0.775% | |
| custom 5389070537748130784 | 135 | 0.591% | |
| 👏 | 114 | 0.499% | |
| ❤🔥 | 70 | 0.307% | |
| 🖕 | 49 | 0.215% | |
| 🫡 | 41 | 0.18% | |
| 🥴 | 36 | 0.158% | |
| 🥱 | 35 | 0.153% | |
| 😱 | 21 | 0.092% | |
| 🤩 | 14 | 0.061% | |
| 🤯 | 14 | 0.061% | |
| 11 further kinds | 75 | 0.329% |
Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 85 of the 85 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 23,416 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 85 most recent posts we hold, published 2 August 2026 to 6 November 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @NazarenkoHistory. 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 85 most recent posts we hold for this entry, published 2 August 2026 to 6 November 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.
Telegram’s own ‘edited’ marker: 4 of 19 posts held from the last 30 days (21.1%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
https://youtu.be/XpoJLxy83Mw?si=28ATH6sfcn7epO8U
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Posted without readable text
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Золото за рану: пиратский кодекс в действии 12 июля 1717 года в Нью-Йорке допрашивали Джеремию Хиггинса, бывшего боцмана того самого пиратского шлюпа «Мэри Энн», который месяцем раньше стоял у Сэнди-Хука (подробнее см. в предыдущем посте рубрики). Взяли его в Нью-Йорке, в доме, где он остановился, и при нём нашлось целое состояние: «14 пистолей золотом, 7½ унций золотого песка, 81 или 82 пиастра серебром и кусок сер…
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Последнее восстание крепостных. Почему русские солдаты и матросы восстали против своих офицеров? Вышла интересная книга Дмитрия Кочетова «Последнее восстание крепостных». Название провокационное, но за ним стоит вполне серьёзная историческая проблема: почему в феврале 1917 г. русская армия, которая должна была быть опорой монархии, стала одной из главных сил, её уничтоживших? Мне близок вопрос о том, откуда взялась…
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Ну, ещё раз с праздником, соотечественники!
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Очередная моя лекция, прошу - https://www.youtube.com/watch?v=tLqbTFSNBLA
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Продолжим о прапорщиках (часть 1). Кроме чина прапорщика существовали также звания подпрапорщика , портупей-прапорщика и зауряд-прапорщика. Отмечу, что до революции чин - это категория Табели о рангах, а звание - категория нижних чинов, не входившее в Табель. В XVIII в. подпрапорщик - старший унтер-офицер, помощник прапорщика, про которого в Уставе воинском 1716 г. сказано только то, что он носит ротное знамя в пох…
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Вот уж не думал, что доберусь до Бизерты. Для меня, как историка флота в основе, это сильное впечатление. Центр памяти о русской эскадре - дом-музей Анастасии Александровны Манштейн-Ширинской и русская церковь. Удивительно интеллигентная женщина - Лариса Богданова - вела экскурсию. Я было подумал, что она из "тех" эмигрантов. Но нет. Однако 30 лет общения с Манштейн-Ширинской не прошли даром. Несмотря на мою отрицате…
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Вот уж не думал, что доберусь до Бизерты. Для меня, как историка флота в основе, это сильное впечатление. Центр памяти о русской эскадре - дом-музей Анастасии Александровны Манштейн-Ширинской и русская церковь.
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СВО. Как мы дошли до 2022 года и куда мы двигаемся сейчас. Часть 3. Часть 1. Часть 2. В комментариях к предыдущим постам постоянно возникает один и тот же вопрос: как можно говорить о борьбе России за независимость, если в России капитализм, есть олигархи, социальное неравенство, а значительная часть экономики встроена в мировой рынок? На мой взгляд, здесь смешиваются два совершенно разных вопроса. Первый - каков о…
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Часть 51. Развал СССР и современный мир / Кирилл Назаренко и Егор Яковлев Четыре года и 51 выпуск спустя цикл «История России — главное» подошёл к концу. В финальной части Кирилл Назаренко и Егор Яковлев говорят о перестройке, распаде СССР и о том, куда движется мир дальше — от дефицита и «конвергенции» до приватизации 1990-х, роли личности в истории и будущего социализма. В этом видео: — Почему поворот не туда слу…
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Софья и Голицын: альтернатива петровским реформам? Обычно царевну Софью Алексеевну (1682–1689) вспоминают как неудачливую соперницу Петра I, а её фаворита князя Василия Васильевича Голицына - как полководца, провалившего два Крымских похода. Между тем при Софье не только продолжались преобразования, начатые её предшественниками, но и обсуждались весьма радикальные проекты. Историк А. С. Лавров посвятил специальное …
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Showing the 12 most recent of 85 posts we hold for @NazarenkoHistory. 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.
@NazarenkoHistory edited 4 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 26 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.
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.
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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“Историк Кирилл Назаренко” (@NazarenkoHistory), 17,221 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/NazarenkoHistory.
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.