Education — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 53% 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
30 measurements spanning 36 days, net -662. 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 22,504–23,364 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)
Subscribers
Change
12 Sept 2026, 08:56
22,603
-32
10 Sept 2026, 03:41
22,635
-62
6 Sept 2026, 18:39
22,697
-47
4 Sept 2026, 06:38
22,744
-33
2 Sept 2026, 17:37
22,777
-30
1 Sept 2026, 19:15
22,807
-29
31 Aug 2026, 17:07
22,836
-10
30 Aug 2026, 18:24
22,846
-6
29 Aug 2026, 20:43
22,852
-9
28 Aug 2026, 22:26
22,861
-21
28 Aug 2026, 00:34
22,882
-21
27 Aug 2026, 01:12
22,903
-23
26 Aug 2026, 04:33
22,926
-22
25 Aug 2026, 05:34
22,948
-28
24 Aug 2026, 06:16
22,976
-31
22 Aug 2026, 17:26
23,007
-15
21 Aug 2026, 11:06
23,022
-12
20 Aug 2026, 09:06
23,034
-16
19 Aug 2026, 07:17
23,050
-20
18 Aug 2026, 07:03
23,070
first reading
Engagement
24 posts held, back to 23 July 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 62 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
1.82%
avg views ÷ 22,603 subscribers
Avg views / post
411
1 post measured
Reaction rate
2.68%
reactions ÷ views · ER floor
Posts in window
1
of 24 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 30 August 2026
Posts held
24 (23 July 2025 – 30 August 2026)
Views total
411
Reactions total
11
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 13:09 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
704 reactions across 24 posts, in 17 distinct kinds. The most used accounts for 54.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
381
54.1%
👍
140
19.9%
🔥
49
6.96%
💯
48
6.82%
🙏
20
2.84%
🥰
15
2.13%
😇
12
1.70%
❤🔥
10
1.42%
💔
9
1.28%
😍
7
0.994%
🤗
3
0.426%
🆒
2
0.284%
🕊
2
0.284%
🦄
2
0.284%
🫡
2
0.284%
😘
1
0.142%
🤯
1
0.142%
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 24 of the 24 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 704 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 24 most recent posts we hold, published 23 July 2025 to 30 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.
Self-Perception & Biases
The Dunning-Kruger effect: People with low skill in a domain often overestimate their ability (because they lack the knowledge to recognize their shortcomings). Highly skilled people sometimes underestimate theirs, assuming what’s easy for them is easy for everyone.
Spotlight effect: We overestimate how much other people notice our appearance, mistakes, or awkward moments. Others are usuall…
Love Psychology
1. When someone truly loves you, they notice the smallest changes no one else sees.
2. Late replies hurt more when they come from the person care about.
Try to understand people more.
♡ ㅤ ❍ㅤ ⌲ 🔔
ˡᶦᵏᵉ ᶜᵒᵐᵐᵉⁿᵗ ˢʰᵃʳᵉ Turn on
━━━━━━━━━━━━━━━
Psychology says:
— if a person laughs too much, even at stupid things, they are lonely deep inside.
— if a person sleeps a lot, they are sad.
— if a person speaks less, but speaks fast, he keeps secrets.
— if someone can't cry, they are weak.
— if someone eats in an abnormal manner, they are tense.
— if someone cries on little things, they are innocent and soft-hearted.
--Most women are attracted to men who possess …
Mind blowing psychology tricks to dominate any situation:
1. Leverage the Foot-in-the-Door technique:
Start with a small request before a larger one. People are more likely to agree to bigger asks one they've already said yes to small one.
2. Employ the Scarcity principle: Highlight how rare or limited something is. This makes people value it more and act quickly.
3. Establish Authority: subtly display your expe…
Match body language
If you are looking to impress, get attention, or gain respect, observe the body language of the person you are talking to and try to imitate it. Research proves that this behavior will show comfort, reinforce trust, and help build a rapport between you and the person you are talking to.
Calling by name
Want to build reliable connections with others?
Remember the person’s name, and when you meet them again, greet them by their name, say “Hi Peter” instead of just saying “Hi.” And don’t stop there, remember little details which they mentioned in the earlier meeting and ask about it.
People feel important and respected when you remember details about them. And they will automatically feel connected …
❤23💯7🔥5😍1
Showing the 12 most recent of 24 posts we hold for @psycho_tricks_TM. 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.
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
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 12 September 2026 — this
entry's latest reading, not the date you are reading this.
“PSYCHOLOGY TRICKS” (@psycho_tricks_TM), 22,603 subscribers as measured 12 September 2026. Telegram Register, tgregister.com/channel/psycho_tricks_TM.
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.