Job listings — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 14 September 2026 and assigned it the closest of 31 fixed categories, at 37% 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.
Growth
16 measurements spanning 65 days, net -1. 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 3,423–3,457 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
11 Oct 2026, 04:41
3,427
-11
5 Oct 2026, 07:56
3,438
+1
26 Sept 2026, 16:36
3,437
-4
13 Sept 2026, 03:18
3,441
-6
9 Sept 2026, 03:59
3,447
-6
4 Sept 2026, 00:15
3,453
+2
31 Aug 2026, 19:35
3,451
+3
28 Aug 2026, 16:17
3,448
+3
25 Aug 2026, 05:43
3,445
+7
22 Aug 2026, 13:02
3,438
+2
19 Aug 2026, 06:46
3,436
+2
16 Aug 2026, 04:52
3,434
+1
12 Aug 2026, 17:22
3,433
+3
10 Aug 2026, 00:29
3,430
+2
7 Aug 2026, 09:46
3,428
no change
7 Aug 2026, 09:33
3,428
first reading
Engagement
20 posts held, back to 16 March 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 3 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 16 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
26s
Average length
13s
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
771 reactions across 20 posts, in 16 distinct kinds. The most used accounts for 41.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
320
41.5%
🔥
156
20.2%
😁
144
18.7%
👍
67
8.69%
❤🔥
42
5.45%
🤡
12
1.56%
👀
6
0.778%
🍓
5
0.649%
👌
4
0.519%
🤣
4
0.519%
🤯
4
0.519%
💯
2
0.259%
🤩
2
0.259%
🙏
1
0.13%
🥰
1
0.13%
🦄
1
0.13%
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 20 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 771 reactions 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 16 March 2026 to 16 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.
Telegram Stars
Stars received
75
across the posts below
Posts paid on
19
of 20 we hold a reading for · 95%
Most on one post
6
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @linkedinwithsofia. 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 20 most recent posts we hold for this entry, published 16 March 2026 to 16 July 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.
Всем привет! Такой вопрос.
📌Может быть здесь есть кто-то, кто хотел бы себя попробовать в ведении профилей в LinkedIn?
Под моим руководством)
В идеале, если вы, конечно, уже знакомы с этой площадкой.
Есть отличный проект, которому подойдут начинающие специалисты 🪴
Сегодня обсуждала с коллегами интересный момент.
Имеем: LinkedIn-инфлюенсер с аудиторией в несколько сотен тысяч опубликовал пост.
Через 3 минуты - 50 комментариев
Через 20 минут - 300+ комментариев
По стечению обстоятельств мы с этим инфлюенсером в этот момент общаемся в личке, и я решила спросить как так))) состоит ли он в каких-то подах или в чем секрет?
Ответ вы видите на скрине.
Ну а потом птичка донесла, ч…
Эксперимент «Open for dating» официально закончен!😂
Конверсия: 0.000%
Знаете, я за эти полтора месяца получила столько положительных эмоций, что эксперимент точно себя оправдал!😂
Во-первых, я не ожидала, что ТАКОЕ количество женщин откликнется и станет поддерживать меня. Многие писали, что это очень смело и круто, что они хотели бы так же. Было конечно же приятно)
Со многими познакомились, было даже пара предложе…
Внезапно в ночи обнаружила новый раздел в LinkedIn - Connected Apps.
Полезла смотреть в интернетах - новости десять дней!)
Что нового?
Теперь можно подключать рабочие инструменты прямо к профилю, и они будут автоматически показывать, что именно ты реально умеешь.
Пишут, что если ты один из самых активных пользователей, LinkedIn даже может дать бейдж Top User.
Ну и для рекрутеров это тоже будет знак!
PS они не д…
Небольшое, но интересное обновление!
Теперь можно прикреплять GIFs в комментариях!
Знаете, иногда одна картинка заменяет тысячи слов 😂
@linkedinwithsofia
Я консультирую в основном по вопросам личного бренда, brand awareness и лидогенерации через LinkedIn, но иногда мы касаемся вопроса и поиска работы.
Помимо стандартного выхода к рекрутерам, я всегда советую писать вашим потенциальным коллегам. Часто в компаниях есть реферальные программы + с интро от текущего сотрудника явно легче попасть :)
Здесь я всегда привожу свой любимый пример, как один мой знакомый нашел кл…
Очень люблю такие посты :)
Называется «как из ничего сделать виральный пост» 😁
Инфоповод топ!
Это кстати будет полезно увидеть тем, кто считает, что каждая публикация должна быть супер экспертной и мега полезной 🫣
@linkedinwithsofia
Слушайте, первый раз в этом году выбираюсь на профильное мероприятие, и очень-очень этому рада!
19 июня еду на CPC.Forum - международный форум про перформанс-маркетинг.
Посмотрела фотки как было в 2025 году - кажется, это прямо супер что-то интересное!
В этом году обещают аж Ксению Собчак, ну посмотрим 👩🦰
По другим спикерам я буду ждать:
- Олега Егорова, CMO Flowwow
- Анастасию Девятых, CMO Lapochka (сколько я э…
Среди целей, почему я заводила этот канал, - ставить разные эксперименты в LinkedIn и смотреть что будет :)
Следующий эксперимент дался мне непросто, и продлится он 2 месяца 😂
До 14 июля у меня будет плашка - Open for dating.
Да, вот так тоже можно 🙂
Я как-то писала про эту плашку в развлекательном ключе….
Вот тебе хи хи да ха ха
Делюсь классной идеей для поста в LinkedIn на завтра.
Завтра отмечается международный день семьи!
Супер-комбо:
🌺 личная тематика
🌺 дети / жены / мужья - триггер в соц сетях —> потенциал на виральность
🌺 инфоповод, привязанный к празднику
Если будете делать пост, отмечайте меня, мне будет приятно 🫶🏻
Всем хорошего четверга!
@linkedinwithsofia
❤15🔥9😁3
Showing the 12 most recent of 20 posts we hold for @linkedinwithsofia. 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.
Mentions
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.
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.
Саша пишет про Берлин @sasha_pishet_pro_berlin · 20,559 Telegram ranks this channel #76 of 98 here — alongside 97 others — read 26 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 11 October 2026 — this
entry's latest reading, not the date you are reading this.
“LinkedIn with Sofia” (@linkedinwithsofia), 3,427 subscribers as measured 11 October 2026. Telegram Register, tgregister.com/channel/linkedinwithsofia.
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.