This channel’s posts match, word for word or near enough, posts on 3 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word 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.
8 measurements spanning 7 days, net +14. 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 22,860–22,895 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 09:57
22,891
+21
13 Aug 2026, 03:53
22,870
+6
12 Aug 2026, 03:33
22,864
-12
11 Aug 2026, 06:27
22,876
+8
10 Aug 2026, 09:01
22,868
-17
9 Aug 2026, 05:21
22,885
-1
8 Aug 2026, 07:46
22,886
+9
7 Aug 2026, 14:15
22,877
first reading
Engagement
32 posts held, back to 9 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 20 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
26.5%
avg views ÷ 22,891 subscribers
Avg views / post
6,060
29 posts measured
Reaction rate
1.04%
reactions ÷ views · ER floor
Posts in window
29
of 32 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 14 August 2026
Posts held
32 (9 July 2026 – 14 August 2026)
Views total
175,620
Reactions total
1,832
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
15 Aug 2026, 05:12 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
Photos
195
Videos
8
Links
336
Lifetime counters from Telegram’s own channel header, read 15 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
1m 36s
Average length
48s
Measured directly from 2 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
2,006 reactions across 31 posts, in 35 distinct kinds. The most used accounts for 23.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🤡
468
23.3%
👍
432
21.5%
❤
234
11.7%
🔥
143
7.13%
🤬
114
5.68%
🥴
98
4.89%
🤣
97
4.84%
😁
90
4.49%
😱
66
3.29%
✍
50
2.49%
🙉
30
1.50%
😢
20
0.997%
🤯
19
0.947%
🍌
18
0.897%
🤝
17
0.847%
💩
16
0.798%
🌭
15
0.748%
🤔
15
0.748%
👎
14
0.698%
😭
10
0.499%
15 further kinds
40
1.99%
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 32 of the 32 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 2,006reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 32 most recent posts we hold, published 9 July 2026 to 14 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.
#postgres_professional
Часть вторая. Реструктуризация.
И я бы даже не стал писать этот отзыв: ну да, компания с плохеньким менеджментом, но в хорошей струе корпоративных заказов. Однако настала она - реструктуризация. Вдруг внезапно в середине лета меняется гендир. Новый объявляет, что рынок изменился, поэтому будут "перетрахивать" буквально каждый отдел. Далее на Cnews выходит новость, что сократят до 30% персонал…
#postgres_professional
Postgres Professional
Привет всем! Решил оставить отзыв о компании, в которой работал и из которой ушёл. Да, это та самая, в которой Бартунов. Многие мои знакомые, когда я туда устроился, слали мне одобрительные реакции: мол, ну круто ты устроился, с самим Олегом будешь работать, это же топ!
Мой отзыв нацелен на то, чтобы развеять некоторые иллюзии насчёт работы в этой организации. А ещё я с…
#м_видео #м_тех
М.Видео вызывает айтишников в офис в одностороннем порядке?
Мне написал разработчик из М Тех ака М.Видео, рассказал, что сотрудникам на удаленке отменяют дистанционку и вызывают в офис, в Одинцово. Мой подписчик кстати живет в 700 км от Одинцово, сплошной кайф, согласны?
«Антон, добрый день! Посоветуй пожалуйста, что можно сделать в сложившейся ситуации. Компания М Тех(М.Видео) в пятницу 31 июля вс…
Разбираемся с текущими проблема айтишников, предъявляем Антону Гладкову и Владу Тену, решаем ваши проблемы из донатов
Бонусом разыграю 15% скидос на профсоюзную
https://youtube.com/live/ivS2rSlA8Qo?feature=share
Закрываю все боли айтишников / Возрождение полезных IT-конференций
https://youtu.be/q5rMPaI13EU
https://youtu.be/q5rMPaI13EU
https://youtu.be/q5rMPaI13EU
Зачем делать конференцию в ноль, вкладывая более десятка миллионов из своего кармана? Все ради борьбы с лицемерием. Объясняю, как делалась конфа и для кого она предназначена, какие цели преследует и боли закрывает.
Даже если вы в другом городе и не сможете приеха…
#МТС_Финтех
Компания: #МТС , а точнее #МТС_Финтех
Ставка: Продуктовый дизайнер. Но история даст размышления для любого сотрудника.
Проработал почти год.
Поначалу всё было прекрасно, я не мог поверить, что пробился сюда. Мне нравился офис и я был вдохнавлен на работу.
Через несколько месяцев начал замечать некоторые проблемы, но не сразу среагировал на это:
Нет планирования, груминга и ретро. Задачи падают в любой м…
#hdcart_pte
Проходила отбор в компанию HDCart PTE на позицию e-com дизайнер. После всех этапов мне направили официальный оффер, который я приняла. Я считала, что конкурс завершён и решение о найме уже принято (весьма логично, не так ли?).
Однако позднее компания отозвала оффер, объяснив это тем, что уже после его отправки завершила рассмотрение еще одного кандидата, чей опыт оказался якобы более подходящим. В итоге …
Смотрим статистику по увольнениям, как не попасть под сокращение, разбираем кейсы подписчиков уволенных
https://youtube.com/live/m1nbQLSpr-Q?feature=share
Как пройти собес с нулевым IQ / Все способы списать с AI
https://youtu.be/eBjsDWm4C3g
https://youtu.be/eBjsDWm4C3g
https://youtu.be/eBjsDWm4C3g
Постоянно стреляет новый способ всех жеска наебать и пройти собес без подготовки. Я собрал и протестировал их все. Вот что из них работает на самом деле, можете забирать себе на вооружение.
Не спешите негодовать и обвинять меня в читерстве, по факту почти ничего не работае…
#трансстройбанк
Пост скорее не о самой компании, сколько об опыте прохождения полиграфа.
Чуть предыстории. Ищу работу с начала лета на начальную позицию, в идеале SysAdmin. По факту сотрудник тех поддержки и что то в таком духе, набраться опыта. Никогда в жизни не проходил полиграф.
Вначале было предупреждено о 3 этапах. Я согласился. Первый собес, меня встретила эйчар, и пару начальников. Отсобеседовали меня дост…
🥴97👍18😁13😭9🤯7🤡5❤4👀4
Showing the 12 most recent of 32 posts we hold for @nazarov_interviews. 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.
Citation-graph rank
Citation-graph rank — 396,484 of 1,350,102entries 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 1 registered channel — 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.
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“Отзывы об IT Компаниях” (@nazarov_interviews), 22,891 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/nazarov_interviews.
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.