3 measurements taken within a single day, 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 494–495 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 07:03
495
+1
8 Aug 2026, 04:20
494
no change
7 Aug 2026, 10:16
494
first reading
Engagement
15 posts held, back to 26 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
19.1%
avg views ÷ 495 subscribers
Avg views / post
94.7
15 posts measured
Reaction rate
7.96%
reactions ÷ views · ER floor
Posts in window
15
of 15 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 6 August 2026
Posts held
15 (26 July 2026 – 6 August 2026)
Views total
1,420
Reactions total
113
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 04:20 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
113 reactions across 15 posts, in 7 distinct kinds. The most used accounts for 32.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
37
32.7%
custom 5388727223832294197
28
24.8%
🥰
13
11.5%
👍
12
10.6%
👏
11
9.73%
🔥
11
9.73%
🤣
1
0.885%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 15 of the 15 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 113reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 26 July 2026 to 6 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.
Ч/б-мышление в мультфильме...
... мы с вами уже находили ранее в рубрике #мультилогия. Мне нравится смотреть мультики и находить в их сюжетах что-то терапевтичное
Сегодня собрала вам такую мульти-подборку:
🦜 Сепарация от мамы в "Рио"
❤️🩹 Принятие помощи и исцеление в "Твитсах"
📖 Прокрастинация и перфекционизм у "Повелительницы сказок"
🫂 Уязвимость ради близости в "Эллио"
🎁 Проживание горя в "Клаусе"
💫 Отве…
IKEA довольно психологична 🛋
В её честь даже назвали когнитивное искажение. Продолжаем рубрику о них, и давайте разбирать_ся, в чём суть:
Оправдание усилий (оно же эффект Икеи) — это когда наш мозг говорит: "Если я вложил/а в это много труда — значит, оно очень ценное"
🪑 Главный пример — мебель из Икеи. Вы покупаете обычный бюджетный стол, но проводите 3 часа, собирая его по непонятной инструкции. В итоге этот сто…
Собрала техники самопомощи ❤️🩹
На этой неделе я в отпуске, но без поддержки вас не оставлю. Забирайте себе:
Техники на случай, когда эмоции "накрывают"
👉 Разные способы подышать
👉 Техника 1-2-3-4-5
👉 Навык ТРУД
👉 Навык СТОП
👉 Прогрессивная мышечная релаксация
Упражнения, чтобы "отделиться" от навязчивых мыслей
💭 "Облака"
💭 "Белая комната"
💭 "Бумажный самолётик"
Способы почувствовать и принять своё тело
…
Иногда мы как базилик в конце недели 🥴
Тот, который на первой картинке. Сегодня вот такая подборка psy-мемов для настроения получилась
А у вас какой мем дня? Или всей недели? Покажите 👇
#депрессия #тревога #усталость
🙅♀️🙅 Дружба НЕ получится...
... если речь о психотерапии. Хотя иногда очень хочется найти родственную душу. Но почему психолог/иня не сможет стать другом или подругой?
Давайте обсудим 👆
#еленашварц #психологиня #кпт
☢️ Токсины в дружбе обнаружены ☢️
Для многих из нас дружба — это что-то важное в жизни. В ней мы ценим открытость, взаимность и готовность помогать. Но бывает и наоборот
Токсичная дружба — это не всегда что-то про злых людей. Часто это про дисбаланс и неуважение. А ещё про поведение разрушает вас
На какие "токсины" обратить внимание в дружбе? Можно начать с честного ответа на несколько вопросов:
❓️ После встречи …
Что вы цените в друзьях и подругах? 🫂
Такой вопрос захотелось вам задать в День дружбы. Расскажите, какие черты цените в друзьях? На что точно обратите внимание? 👇
🥰4❤3🔥1
Showing the 12 most recent of 15 posts we hold for @psyho_login. 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 — 1,089,348 of 1,183,361entries 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 8 August 2026 — this
entry's latest reading, not the date you are reading this.
“Психо логин | Елена Шварц” (@psyho_login), 495 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/psyho_login.
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.
