Channel
@natali_vetdoc
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
17,877subscribers
+2 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001388410805 |
|---|---|
| Type | Channel |
| Username | @natali_vetdoc |
| Description | Здесь все для владельцев домашних животных 🐈🐕🦺 А+: Включена Роскомнадзором в перечень персональных страниц: https://gosuslugi.ru/snet/679b22c9e7235e5c9e385c5e |
| Created | 24 February 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 7 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 14 August 2026 |
| On Telegram | t.me/natali_vetdoc |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 23:04 | 17,877 | +1 |
| 13 Aug 2026, 11:26 | 17,876 | +1 |
| 10 Aug 2026, 12:41 | 17,875 | -5 |
| 8 Aug 2026, 14:24 | 17,880 | +4 |
| 7 Aug 2026, 12:55 | 17,876 | +1 |
| 7 Aug 2026, 04:17 | 17,875 | first reading |
19 posts held, back to 24 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 21 pagesof 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 29 July 2026 |
|---|---|
| Posts held | 19 (24 July 2026 – 29 July 2026) |
| Views total | 32,610 |
| Reactions total | 1,420 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Aug 2026, 10:34 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 15 August 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 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.
1,420 reactions across 19 posts, in 11 distinct kinds. The most used accounts for 71.6% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1,017 | 71.6% | |
| 🙏 | 138 | 9.72% | |
| 👍 | 72 | 5.07% | |
| 🔥 | 65 | 4.58% | |
| 💯 | 47 | 3.31% | |
| 😍 | 28 | 1.97% | |
| 🤗 | 25 | 1.76% | |
| 🥰 | 11 | 0.775% | |
| 😁 | 9 | 0.634% | |
| 😭 | 7 | 0.493% | |
| 💔 | 1 | 0.07% |
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 19 of the 19 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 1,420reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 24 July 2026 to 29 July 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.
А здесь я улыбнулась: 😀 Не проплаченный отзыв. Хозяйка, которая прошла обучения, теперь от всего сердца хочет донести другим, что с помощью моих обучений можно решить проблемы здесь и сейчас – самостоятельно, сэкономив деньги, нервы и время. Спасибо вам! Так приятно мне было читать обратную связь 🫶 И самое приятное – я ничего не просила. Люди сами хотят делиться и сами пишут благодарности!
❤33😍28💯4
Здесь были годы лечения, походы по клиникам… Хочу сказать спасибо за доверие 💞 Я очень счастлива читать отзывы и понимать, что моё обучение наконец-то помогло вашему питомцу и вам.
❤37
На обновление сегодня тоже последний день действует скидка. И в этом месяце мы обновляем данное обучение в последний раз. ➡️ Обновить сейчас https://natalivetdoc.ru/
👍22❤1😁1
🟢 Почему вам стоит пройти обучение «Глаза, кожа, уши всегда здоровы»? 👇 Разберем, что вы получите: 🔴 БЛОК ГЛАЗА: Перестанете гадать, норма это или патология. Вы наконец разберетесь, почему текут глаза и когда это повод бить тревогу. ✔️ Разберетесь с синдромом «сухого глаза» — и поймете, чем реально помочь до визита к врачу. ✔️ Узнаете, как «прочитать» выделения из глаз и почему большинство лосьонов из зоомагазина в…
❤25👍5
🔥 ПОСЛЕДНИЙ ДЕНЬ СКИДКИ на обучение «Глаза, кожа, уши всегда здоровы»! Одним обучением вы сейчас можете закрыть вопросы, которые копятся годами: от банальной гигиены до сложных диагнозов. Сделайте это прямо сейчас!
❤24
💎 ВМЕСТО ПОТРАЧЕННЫХ ТЫСЯЧ РУБЛЕЙ НА БЕСПОЛЕЗНЫЕ АНАЛИЗЫ И НА ОЧЕРЕДНУЮ СМЕНУ КОРМА Потратьте лучше их на знания. ✅ Чтобы самостоятельно разобраться в теме аллергий. ✅ Чтобы по чёткому плану исключить каждую аллергию. ✅ Чтобы добраться до истины — почему питомец чешется, разлизывает лапы или страдает от постоянного отита. ✅ Чтобы самостоятельно знать, как бороться с этой аллергией. Обучающее руководство «Глаза, ко…
❤45
МИФ №3 «Анализ крови на пищевую аллергию поможет подобрать правильный корм» ❌ НЕТ. НЕТ. НЕТ. 📢 Ещё раз повторю: Анализ крови на пищевую аллергию не является достоверным. Он ничем не поможет вам и вашему питомцу. Ваше время и деньги будут потрачены впустую. Чтобы вы понимали, эти анализы в среднем выходят на 10–15 тысяч рублей.
❤41👍9💔1
Хозяйка сама разобралась с аллергией после обучения. И здесь аллергия была не на курицу, а на молочные продукты. Владельцы потом говорят «СПАСИБО», потому что даже не могли представить, что всё так просто.
❤44
❌ ЭТО НЕ ТАК. Абсолютно любой источник белка может давать аллергическую реакцию. 📊 По статистическим данным, самый аллергенный белок — говядина, вопреки общему мнению. Потом идут молочные продукты, и только потом — курица и рыба.
💯23❤20
МИФ №2 «Курица — самый сильный аллерген»
❤39
⚠️ В ТАКИХ СЛУЧАЯХ ТОЧНО НЕ НАДО МЕНЯТЬ КОРМ. Надо начинать с борьбы с блошиным дерматитом. В руководстве «Глаза, кожа, уши всегда здоровы» раздел «Аллергии» начинается именно с исключения блошиного дерматита, а не со смены корма. Потому что существует поэтапный план исключения каждой из аллергий. И на первом месте — аллергия на блох!
❤35👍9
Хозяйка больше года пыталась лечить пищевую аллергию. Она многократно меняла питание, но ничего не помогло. Когда мы сказали: «У вашего питомца блошиный дерматит», она не поверила. Как мы это поняли? У животного НЕ БЫЛО ОБРАБОТОК. «Он же домашний, какие блохи?» 🙈 После двух лечебных обработок от блох все симптомы аллергии ушли. Всё. Просто. Обработки. Не корма. Не таблетки. Не диета.
❤51👍12
Showing the 12 most recent of 19 posts we hold for @natali_vetdoc. 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 — 388,788 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.
Named by 2 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.
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.
“Ветеринарный врач Наталья Федосеева” (@natali_vetdoc), 17,877 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/natali_vetdoc.
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.