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Channel

Кириченко SEO | ex-Staurus

@skirichenko_seo

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

124subscribers

+24 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002778597197
TypeChannel
Username@skirichenko_seo
CreatedBetween 1 June 2025 and 30 September 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded9 August 2026
Last confirmed live14 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/skirichenko_seo

Growth

1001241127 August 2026 — 100 subscribers9 August 2026 — 100 subscribers14 August 2026 — 124 subscribers7 August 202614 August 2026
3 measurements spanning 7 days, net +24. 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 96–128 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 20:26124+24
9 Aug 2026, 10:48100no change
7 Aug 2026, 19:25100first reading

Engagement

20 posts held, back to 17 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
81.9%
avg views ÷ 124 subscribers
Avg views / post
102
5 posts measured
Reaction rate
3.34%
reactions ÷ views · ER floor
Posts in window
5
of 20 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. It is computed over the 4 of 5 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 9 August 2026
Posts held20 (17 June 20269 August 2026)
Views total508
Reactions total16
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Aug 2026, 10:48 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.

Reaction mix

57 reactions across 18 posts, in 6 distinct kinds. The most used accounts for 63.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍3663.2%
🔥1119.3%
610.5%
😁23.51%
😱11.75%
🤔11.75%

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 18 of the 20 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 57reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 17 June 2026 to 9 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.

Recent posts

9 Aug 2026, 09:20 UTC29 viewsread 9 August 2026

Я убрал из текста звёздочки, которыми размечают жирный шрифт. Ни одной буквы не тронул, проверил побайтово: 14 485 знаков до и столько же после. Все шесть моделей, минуту назад звавших текст машинным, сказали «человек». Это кусок моего исследования: 1882 текста, четыре независимых измерителя машинности, дизайн зарегистрирован до сбора данных. Препринт с DOI лежит на Zenodo. Оценку тянет оформление. Заголовки, спис

23 Jul 2026, 11:07 UTC104 views4 reactionsread 9 August 2026
Photo

Когда GA сертификаты не актуальны, приходиться вертеться. А вы уже обновили свои сертификаты?

🔥3😁1

20 Jul 2026, 20:40 UTC132 views4 reactionsread 9 August 2026
Photo

Одиночный замер видимости в нейросетях невоспроизводим. Проверил на себе. Прогнал восемь запросов через нейросеть пять раз подряд за десять минут. Выдача за это время меняться не могла. Половина цитируемых источников не пережила пять повторов. По медицинскому запросу первое место чередовалось через прогон: sostav, medesk, sostav, medesk, sostav. Дальше — хуже. Взял одну потребность, задал её пятью формулировками. У

🔥31

17 Jul 2026, 11:34 UTC130 views1 reactionsread 9 August 2026
Forwarded from @goburzhseoPhoto

Один хороший человек, которого зовут Карим, полностью систематизировал инфу о том, как продвигаться с помощью AI. Он отбросил все мифы, добавил чистой практики и создал мощный курс по GEO. 🚀 Ну и я просто не смог пройти мимо, чтобы не поделиться полезным контентом. https://geo-course.ru/ Специально для котанов из Go Бурж SEO держите промик GO GEO на -25% из цены курса 🐈‍⬛🔥

👍1

14 Jul 2026, 13:18 UTC114 views1 reactionsread 9 August 2026

Какая нейросеть пишет по-человечески, а какая просто аккуратно размазывает ИИ-слоп? Я дал 18 ИИ-сервисам два одинаковых задания и разобрал 36 текстов: повторы, ритм, пустые усилители, уклонение от конкретики, языковые сбои и следы генерации, которые модели оставили прямо в ответах. По ходу эксперимента пришлось выбросить первый рейтинг: детектор начал штрафовать нейросети за точное выполнение моего же ТЗ. Поэтому в

👍1

10 Jul 2026, 21:06 UTCviews —

Кириченко SEO | ex-Staurus pinned «Все новости переехали в канал https://t.me/seoptichka Канал полностью автоматизированный. Раз в сутки (в 20:00) делает дайджест новостей, кейсов и постов из телеграмм каналов по SEO, GEO, AEO. Источников больше 300 штук со всего мира и отбираются по внутреннему…»

10 Jul 2026, 11:32 UTC206 views2 reactionsread 9 August 2026

Списки «200 факторов ранжирования Google» — это SEO-фольклор. Их переписывают годами, добавляют туда слухи, патенты, утечки, старые заявления сотрудников Google и личные догадки. Потом называют всё это «факторами» и продают как экспертизу. Проблема простая: у большинства таких списков нет главного — уровня доказанности. Патент ≠ работающий алгоритм. Поле из утечки ≠ фактор ранжирования. Внутренний слайд ≠ показание

🔥2

9 Jul 2026, 12:10 UTC87 views2 reactionsread 9 August 2026
Forwarded from @drmaxseo

🔥 56%: Математический потолок поисковых систем Существует фундаментальный предел того, насколько "идеальной" может быть поисковая выдача или ответ LLM. Математически доказано: этот предел составляет 55,84% от теоретического максимума. Это не значит, что Google работает "на полсилы". Это значит, что при попытке одновременно выбрать самые полезные (g(S)) и самые разные (div(S)) источники, алгоритм неизбежно сталкивае

👍2

5 Jul 2026, 15:58 UTC130 views3 reactionsread 9 August 2026

Написал большой разбор о том, что происходит с брендом внутри ИИ-ответа: https://sk-seo.ru/blog/kak-ii-vidit-brend.html Позиция в выдаче больше не гарантирует участия в выборе. ChatGPT, AI Overviews и Алиса читают сайт за пользователя, пересобирают и отвечают сами. «Ваш сайт прочитали» и «ваш бренд использовали в ответе» — разные события, и между ними семь участков, где бренд теряет видимость. Веду один бренд по вс

2🤔1

28 Jun 2026, 20:49 UTC151 views5 reactionsread 9 August 2026

С мая часть популярных GEO-тактик официально стала спамом. По тексту правил Google, не метафорически. 15 мая Google переписал определение спама и прямо вписал туда попытки манипулировать AI-ответами. Июньский апдейт начал это применять. Год можно было пролезать в AI-ответы в обход топа — мусорными страницами, паразитными публикациями, накруткой цитирований. Теперь за это прилетает там же. Только не перепутайте: под

👍5

28 Jun 2026, 13:13 UTC144 views3 reactionsread 9 August 2026
Photo

Выкатил на Хабр большую статью-кейс про ContentCombine — мой мультинишевый контент-комбайн. Коротко: я устал вручную читать сотню SEO-источников и собрал систему, которая делает это за меня. Сейчас машина собирает материалы из 235 источников: RSS, Telegram-каналы, сайты, Bluesky. Дальше она считает важность, склеивает повторы в сюжеты, отделяет кейсы от проходных анонсов, чистит старьё, следит за сломанными источни

👍3

Showing the 12 most recent of 20 posts we hold for @skirichenko_seo. 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 — 86,835 of 1,481,217entries 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

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 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.

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.

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.

“Кириченко SEO | ex-Staurus” (@skirichenko_seo), 124 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/skirichenko_seo.

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.