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Channel

Паволга видела

@olgapavolga

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Handles named that no longer answer · Cite this entry

7,194subscribers

-7 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001539006910
TypeChannel
Username@olgapavolga
Created25 February 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded7 August 2026
Last confirmed live27 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 27 August 2026
On Telegramt.me/olgapavolga

Growth

7,1947,2017,197.57 August 2026 — 7,201 subscribers7 August 2026 — 7,201 subscribers10 August 2026 — 7,200 subscribers13 August 2026 — 7,197 subscribers17 August 2026 — 7,199 subscribers20 August 2026 — 7,198 subscribers24 August 2026 — 7,195 subscribers27 August 2026 — 7,194 subscribers7 August 202627 August 2026
8 measurements spanning 19 days, net -7. 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 7,193–7,202 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
27 Aug 2026, 04:327,194-1
24 Aug 2026, 06:577,195-3
20 Aug 2026, 09:227,198-1
17 Aug 2026, 10:427,199+2
13 Aug 2026, 10:257,197-3
10 Aug 2026, 14:577,200-1
7 Aug 2026, 17:167,201no change
7 Aug 2026, 17:067,201first reading

Engagement

17 posts held, back to 29 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 12 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
18.6%
avg views ÷ 7,194 subscribers
Avg views / post
1,340
17 posts measured
Reaction rate
10.2%
reactions ÷ views · ER floor
Posts in window
17
of 17 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
WindowRolling 30 days · latest post in window 18 August 2026
Posts held17 (29 July 202618 August 2026)
Views total22,715
Reactions total2,311
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken20 Aug 2026, 11:55 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
50s
Average length
13s

Measured directly from 4 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

2,311 reactions across 17 posts, in 16 distinct kinds. The most used accounts for 38.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
87838.0%
🔥65228.2%
😁33814.6%
💔1375.93%
❤‍🔥1044.50%
🤩743.20%
👍441.90%
🥰301.30%
😭200.865%
😱100.433%
🌚70.303%
👏50.216%
👀40.173%
🤔40.173%
🙏20.087%
🤪20.087%

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 17 of the 17 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 2,311reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 29 July 2026 to 18 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
3
across the posts below
Posts paid on
3
of 17 we hold a reading for · 18%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @olgapavolga. 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 17 most recent posts we hold for this entry, published 29 July 2026 to 18 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.

Recent posts

18 Aug 2026, 12:17 UTC653 views77 reactionsread 20 August 2026
Photo

пре пре превращения 🪄 модель Александра образы, фото @pavolgafoto костюмы: моя костюмерная визажист Юля Сметанина ассистент Ирина Орлова видео Лера Трифонова ⠀ 🌿про сьемки на сайте pavolga.com или у координатора Ирины Орловой в тг @allthislight ⠀

🔥5027

17 Aug 2026, 12:08 UTC≈1,010 views173 reactionsread 20 August 2026

Пережила небольшую операцию (плановую, все хорошо), на осмотре доктора видела единственную книжку на полке: «Живые и мертвые» Симонова. Хороший доктор, бодрит.

86😁63🔥22🙏2

17 Aug 2026, 12:05 UTC986 views61 reactions1 Starread 20 August 2026
Photo

Создание животных, особенно мне нравится лицо петуха, хотя все хорошие! Master Bertram of Minden, 1379

51😁10

14 Aug 2026, 13:26 UTC≈1,420 views129 reactionsread 20 August 2026
Photo

Прекраснейшая Алена и ковер 🌚🩵 модель Алена образы, фото @pavolgafoto костюмы: моя костюмерная визажист Юля Сметанина парик Женя Филиппова ассистент @mycinephilia видео Лера Трифонова ⠀ 🌿про сьемки на сайте pavolga.com или у координатора Ирины Орловой в тг @allthislight ⠀

🔥10622🥰1

13 Aug 2026, 14:30 UTC≈1,550 views154 reactionsread 20 August 2026
Photo

нашла Божественную кошку, 1725, Ямагути Соке лицо у нее наше

🤩64🔥49😁2316🤪2

13 Aug 2026, 13:13 UTC≈1,400 views175 reactionsread 20 August 2026
Photo

Некоторые волшебные женщины этого лета 🖤🤍

111❤‍🔥31🔥24💔4🥰3👍2

13 Aug 2026, 07:18 UTC≈1,150 views99 reactionsread 18 August 2026
Photo

Была тут на УЗИ у приятного доктора, он мне объяснял, всё, что он делает, что он видит, что я сейчас буду чувствовать, показывал картинки и перед прикосновениями предупреждал. Вышла от него, как после терапии. На меня внимательно, безопасно и с интересом посмотрели, показали, что увидели и отпустили. ⠀ Потом думаю, так это я ж на сьемках! Надо только мне халат белый для закрепления эффекта завести. ⠀ Взяла на вооруж

84🔥15

9 Aug 2026, 17:12 UTC849 views66 reactionsread 12 August 2026
Photo

Я раньше у Леонида Шмелькова в инстаграме смотрела только коротенькие милые рилсы про синего волка Андрея. А сейчас у него вышел большой странный мультфильм прямо в киношный прокат. Какой-то сон, сюрреалистический мульт по всей стране в кинотеатрах. Онлайн есть на Окко. Сюжет - как смесь Твин Пикса, Извне и даже не знаю чего. Одновременно непонятного, тревожного и ироничного. Там пара приятелей попадает в отель, из

37😁17🌚7🔥5

9 Aug 2026, 16:04 UTC917 views213 reactionsread 12 August 2026

Есть у меня привычка, когда прихожу домой после особенно нагруженного дня, сразу иду на кухню пить и кричу Алисе «Включи фанфары и аплодисменты!». Так я себя хвалю за то, что я молодец и справилась. Вчера вхожу в кухню и тут же раздается громкий мужской голос: «Аплодисменты!» и уже не так громко, но слышно, как начинают хлопать, свистеть люди и звучит торжественная музыка. Ну, думаю, перетрудилась. Проверила колонк

🔥114😁4738❤‍🔥9👏5

7 Aug 2026, 11:52 UTC≈1,060 views158 reactionsread 12 August 2026
Photo

А вот результат поисков на авито чрезмерно красивой обуви для съемок, побочным эффектом которого были те ботфорты эрмитажной наружности.

🔥113🥰1916❤‍🔥10

5 Aug 2026, 15:29 UTC≈1,490 views110 reactionsread 12 August 2026
Photo

ну какой ангел у Пентуррикио, какой зеленый с розовым фреска 1500, Spello, Santa Maria Maggiore Capella bella

85🔥18🥰6❤‍🔥1

3 Aug 2026, 12:40 UTC≈1,690 views137 reactionsread 12 August 2026
Photo

Знаю, что не у всех Тредс такой, поделюсь своим хорошеньким, чтоб все порадовались, первые несколько постов в ленте. И это еще без комментов!

😁10619👍12

Showing the 12 most recent of 17 posts we hold for @olgapavolga. 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 — 1,172,015 of 1,621,754entries 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.

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 27 August 2026 — this entry's latest reading, not the date you are reading this.

“Паволга видела” (@olgapavolga), 7,194 subscribers as measured 27 August 2026. Telegram Register, tgregister.com/channel/olgapavolga.

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.