СМИ Энергодара и Запорожской области. Главные новости региона
Наш новый чат области: t.me/zaporozhskaya_obl_chat
Обратная связь @glavnoe_v_melitopole
https://gosuslugi.ru/snet/6882257bccc45029e57c976c
Created
7 March 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel)
National news — 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 10 August 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 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.
Content that also appears on other registered channels
Posts published here appear word for word on 4 other registered channels. They sit inside a group of 9 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 32 of the 56 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 48 comparable posts for this entry, running 4 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 9, the earliest publisher we hold is @berdyansk_ru. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_source, last confirmed 8 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 8 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.
35 measurements spanning 43 days, net +1,137. 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 34,585–36,692 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)
Subscribers
Change
18 Sept 2026, 13:01
36,138
-307
16 Sept 2026, 05:39
36,445
+1,514
14 Sept 2026, 08:54
34,931
+103
12 Sept 2026, 19:20
34,828
-111
10 Sept 2026, 22:41
34,939
-610
7 Sept 2026, 23:01
35,549
-868
5 Sept 2026, 00:01
36,417
-32
3 Sept 2026, 06:45
36,449
+25
2 Sept 2026, 02:22
36,424
+36
1 Sept 2026, 03:18
36,388
+44
31 Aug 2026, 01:55
36,344
+61
30 Aug 2026, 04:08
36,283
-21
29 Aug 2026, 04:44
36,304
+483
28 Aug 2026, 07:53
35,821
+148
27 Aug 2026, 07:04
35,673
-35
26 Aug 2026, 03:43
35,708
-52
25 Aug 2026, 01:58
35,760
-55
23 Aug 2026, 15:45
35,815
-256
22 Aug 2026, 02:36
36,071
-51
20 Aug 2026, 19:17
36,122
first reading
Engagement
652 posts held, back to 4 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 80 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
20.6%
avg views ÷ 36,138 subscribers
Avg views / post
7,450
356 posts measured
Reaction rate
1.99%
reactions ÷ views · ER floor
Posts in window
356
of 652 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 September 2026
Posts held
652 (4 August 2026 – 22 September 2026)
Views total
2,653,537
Reactions total
52,891
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 02:02 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
≈14,200
Videos
≈4,240
Links
≈4,780
Lifetime counters from Telegram’s own channel header, read 23 September 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.
Video runtime
31m 50s
Average length
10m 37s
Measured directly from 3 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
94,025 reactions across 632 posts, in 11 distinct kinds. The most used accounts for 61.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
57,911
61.6%
❤
16,266
17.3%
👏
6,844
7.28%
🙏
4,880
5.19%
😐
3,893
4.14%
🔥
2,352
2.50%
🤬
1,613
1.72%
😢
227
0.241%
😨
15
0.016%
🤯
15
0.016%
😱
9
0.01%
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 652 of the 652 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 96,883 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 652 most recent posts we hold, published 4 August 2026 to 22 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.
Собака из Запорожской области собрала вокруг себя все свои игрушки
Подписчица из Запорожской области поделилась забавным снимком своего питомца. Собака расположилась в окружении множества игрушек и с увлечением играет с ними. По словам хозяйки, получился настоящий детский сад.
У вас тоже есть возможность прислать нам фотографии, которые мы опубликуем. Вы можете отправить их на нашу обратную связь.
Подписывайтесь н…
В ИК-1 УФСИН Запорожской области прошла встреча осужденных со священнослужителем
В исправительной колонии № 1 УФСИН России по Запорожской области в рамках духовно-нравственного воспитания осужденных состоялась встреча со священнослужителем. В ходе беседы были затронуты вопросы традиционных духовных ценностей, важности законопослушного поведения и недопустимости совершения повторных преступлений.
Особое внимание уде…
Сотрудники ГИМС МЧС провели урок безопасности для школьников
Инспекторы Центра Государственной инспекции по маломерным судам МЧС России по Запорожской области посетили среднюю общеобразовательную школу в Бердянске. Специалисты рассказали школьникам о правилах поведения на воде и сезонных рисках, среди которых снижение температуры воды, ухудшение видимости и изменение погодных условий.
В ходе занятия работники ГИМС …
В Мелитопольском индустриальном колледже прошел семинар по работе с молодежью
В Мелитополе состоялся семинар для специалистов, работающих в сфере молодежной политики. Участниками встречи стали педагоги Мелитопольского индустриального колледжа. В ходе обсуждения рассмотрели темы выстраивания доверительных отношений с молодежной аудиторией, работы с молодежными инициативами и проектами.
Отдельным блоком стало обсужде…
📢В ДНР, ЛНР и Запорожской области сварят борщ из херсонских овощей
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Агрегатор закупает у фермеров небольшие партии, сортирует, упаковывает, оформляет документы и отправляет оптовикам и в торговые сети внутри региона и за ег…
Сотрудники Минкультуры Запорожской области приняли участие во всероссийском совещании
Сотрудники Министерства культуры Запорожской области совместно с директорами детских школ искусств региона подключились к Всероссийскому совещанию в формате видеоконференции. В ходе мероприятия обсуждались вопросы государственной поддержки детских школ искусств.
Также участники рассмотрели вопросы проведения общероссийских конкурс…
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Ребята узнали, чем занимается Молодежка, какие направления работы существуют и как можно присоединиться к команде.
Кроме того, школа передала Молодежке гуманитарную помощь для военнослужащих — еще одно подтверждение того, что вместе можно сделать много полезного.
Активисты поблагодарили учеников и педагогов за поддержку и отметили, …
❗️Бойцы группировок войск «Днепр» и «Восток» за сутки ликвидировали более 310 военнослужащих ВСУ
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📢В Запорожской области опровергли данные о заниженных зарплатах медиков
Специалисты регионального Центра скорой помощи пояснили, что опубликованный расчетный лист отражает только базовый оклад, тогда как фактический доход медработников складывается из множества надбавок: за квалификационную категорию, выслугу лет, работу в особых условиях и участие в оказании помощи пострадавшим в ходе СВО.
С сентября для сотрудник…
Министр культуры встретилась с членами Союза художников Запорожской области
Министр культуры Светлана Назина посетила художественную галерею и здание, где располагается Союз художников региона. Помещение вновь передано творческому объединению, что открывает возможности для развития его деятельности и создания условий для работы художников.
В ходе встречи обсудили дальнейшие шаги по организации работы Союза, перспек…
За сутки в Запорожской области родились шесть малышей
В Запорожской области за последние сутки на свет появились шесть малышей. Из них один мальчик и пять девочек, сообщили в региональном минздраве.
Подписывайтесь на нас в MAX
❗️ВСУ нанесли удар по скорой помощи в Запорожской области
Киевские террористы атаковали автомобиль скорой помощи в селе Малая Белозерка Каменско-Днепровского округа.
Погиб водитель, еще три человека получили ранения и получают необходимую медицинскую помощь.
Подписывайтесь на нас в MAX
👍102❤29🤬16😢10😐8
Showing the 12 most recent of 652 posts we hold for @energodar_ru. 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
@energodar_ru edited 1 post 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
22 August 2026
Most recent edit
22 August 2026
Forward network
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.
Mentions
Named by 11 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.
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 1 September 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.
Триколор над Запорожьем @tricolourzaporogye · 50,798 Telegram ranks this channel #2 of 94 here — alongside 93 others — read 26 August 2026
Главное в Бердянске @berdyansk_ru · 37,136 Telegram ranks this channel #9 of 85 here — alongside 84 others — read 1 September 2026
Триколор над Херсоном @tricolourkherson · 45,728 Telegram ranks this channel #11 of 95 here — alongside 94 others — read 29 August 2026
Главное в Каховке и Новой Каховке @newkahovka_ru · 34,262 Telegram ranks this channel #28 of 96 here — alongside 95 others — read 2 September 2026
Главное в Мелитополе @melitopol_ru · 102,370 Telegram ranks this channel #36 of 73 here — alongside 72 others — read 15 August 2026
Главное в Скадовске @skadovsk_rus · 39,114 Telegram ranks this channel #50 of 86 here — alongside 85 others — read 31 August 2026
ЭНЕРГОДАР СЕГОДНЯ @energodartime · 26,752 Telegram ranks this channel #56 of 78 here — alongside 77 others — read 12 September 2026
Никополь/Марганец/Энергодар/Обстрелы @other_nikopol · 21,888 Telegram ranks this channel #59 of 86 here — alongside 85 others — read 22 September 2026
Главное в Геническе @Genichesk_ru · 51,450 Telegram ranks this channel #61 of 88 here — alongside 87 others — read 24 August 2026
This channel appears in 9 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Главное в Энергодаре” (@energodar_ru), 36,138 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/energodar_ru.
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.
