Crypto & trading — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 59% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 4 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 1 of the 18 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 1,802 comparable posts for this entry, running 21 June 2024 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
65 measurements spanning 98 days, net -368,675. 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 1,598,271–2,077,548 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)
Subscribers
Change
11 Nov 2026, 16:20
1,653,572
-5,002
9 Nov 2026, 18:40
1,658,574
-6,046
8 Nov 2026, 07:54
1,664,620
-5,288
6 Nov 2026, 23:48
1,669,908
-3,417
5 Nov 2026, 21:38
1,673,325
-3,943
4 Nov 2026, 21:10
1,677,268
-3,550
3 Nov 2026, 21:09
1,680,818
-3,608
2 Nov 2026, 17:27
1,684,426
-3,841
1 Nov 2026, 14:26
1,688,267
-4,739
31 Oct 2026, 14:28
1,693,006
-2,719
30 Oct 2026, 15:59
1,695,725
-5,356
29 Oct 2026, 14:44
1,701,081
-3,702
28 Oct 2026, 15:40
1,704,783
-3,015
27 Oct 2026, 17:26
1,707,798
-5,088
26 Oct 2026, 17:21
1,712,886
-1,622
25 Oct 2026, 15:59
1,714,508
-2,620
24 Oct 2026, 18:31
1,717,128
-2,678
23 Oct 2026, 21:26
1,719,806
-3,393
22 Oct 2026, 20:00
1,723,199
-6,191
21 Oct 2026, 13:11
1,729,390
first reading
Engagement
2,293 posts held, back to 20 June 2024 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 4,236 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.069%
avg views ÷ 1,653,572 subscribers
Avg views / post
1,130
172 posts measured
Reaction rate
0.274%
reactions ÷ views · ER floor
Posts in window
172
of 2,293 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. It is computed over the 139 of 172 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 11 November 2026
Posts held
2,293 (20 June 2024 – 11 November 2026)
Views total
195,183
Reactions total
433
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 20:25 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
Computed from 172 of this channel’s own posts over the last 30 days: across 168 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 13 hours of being posted; a typical post has already reached 21.4% of its 24-hour view count within the first hour, and 54.1% within the first six; the median 24-hour reach across those posts is 710 views — 0.043% of this channel’s own subscriber count (90th percentile 870).
8 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed views is the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
2,421 reactions across 659 posts, in 11 distinct kinds. The most used accounts for 39.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
947
39.1%
👍
665
27.5%
🔥
350
14.5%
🤯
259
10.7%
👏
53
2.19%
🤔
34
1.40%
😱
27
1.12%
🤬
25
1.03%
😁
23
0.95%
🥰
20
0.826%
👎
18
0.743%
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 824 of the 1,000 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 3,003 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 19 July 2026 to 11 November 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
30
across the posts below
Posts paid on
28
of 1,000 we hold a reading for · 3%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @learn2earnings. 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 1,000 most recent posts we hold for this entry (the sample is capped at 1,000), published 19 July 2026 to 11 November 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
Telegram’s own ‘edited’ marker: 0 of 172 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
📚 AI for Normal People · Lesson 4 of 12
Image gen — Midjourney, Flux, Nano Banana
What each one is actually good at, real examples
In short: Midjourney, Flux, and Nano Banana are all AI image generators, but each excels at different tasks. Knowing which tool fits your need saves time and gives sharper results than relying on just one.
How it works
• Midjourney shines for stylized, artistic visuals like posters, log…
📈 Why this is worth your time
$55 million is what Jane Street partners earn.
That's not your target—but here's what matters: people who can code, who understand crypto, who build things—they still get paid when others don't. Right now, US software engineer hiring fell to 47% of its 2022 peak. The market is smaller, tighter, more selective.
So yes. Your evenings matter.
Spend an hour tonight setting up a free codi…
📚 Crypto from Zero · Lesson 4 of 12
Stablecoins — the boring ones that matter
USDC vs USDT vs DAI — what's actually behind each one
In short: Stablecoins are crypto designed to hold steady value, usually $1. But 'stable' depends on what backs it: real dollars, other crypto, or just code and math.
How it works
• Fiat-backed (USDC, USDT): a company holds real dollars or similar safe assets in reserve for every coin i…
📈 Why this is worth your time
$684M went into African tech startups in the first nine months of this year alone.
That money isn't sitting in banks. It's funding real companies that need people who can actually build things—designers, developers, product people. The skills gap is the only thing keeping those seats empty.
Start tonight by picking one small project you'd actually use. Build it badly. Learn from break…
💡 Satoshi built Bitcoin to remove the middleman. But here's what nobody tells you: a pre-loaded hardware wallet from an online marketplace might already be compromised.
30-second breakdown — plain English, Nigerian examples, no hype.
▶️ Watch: https://youtube.com/shorts/CginJmR2Umw
#crypto #learncrypto #nigeria #shorts
News | TimeFarm | 𝕏 takes
💡 You've started learning crypto three times and stopped because it felt like everyone else already understood it. That's not a personal thing.
30-second breakdown — plain English, Nigerian examples, no hype.
▶️ Watch: https://youtube.com/shorts/quhpAJPCiOo
#crypto #learncrypto #nigeria #shorts
News | TimeFarm | 𝕏 takes
📚 Financial Literacy 101 · Lesson 4 of 12
Retirement accounts, decoded
RSA, PFA, 401k, TFSA — African systems first
In short: A retirement account is a protected savings pot that grows while you work and pays you later. In Nigeria, your RSA (Retirement Savings Account) is managed by a PFA (Pension Fund Administrator) you choose.
How it works
• Nigeria's Contributory Pension Scheme: you and your employer each contri…
📈 Why this is worth your time
$90,000
That's what Remote Strategic Partnerships Officer roles pay at the high end. Real positions, real money, open to people building skills from home right now.
You don't need to be in Silicon Valley or New York. You need to know how to talk to people, understand business problems, and learn the tools as you go. Evening study compounds fast when you're working toward something con…
🤬2👍1
Showing the 12 most recent of 2,293 posts we hold for @learn2earnings. 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.
Polls
The 6 most recent of 191 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
What is the main reason to choose a specific budgeting system?
It guarantees you save more money automatically28%
It matches your personality so you'll actually stick with it59%
It removes the need to track spending at all7%
It is required by banks for account opening7%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 1,000 most recent posts we hold (the sample is capped at 1,000), published 19 July 2026 to 11 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Mentions
Named by 6 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 7 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
Tap to Earn Insider @taptoearninsider · 929,496 Telegram ranks this channel #1 of 89 here — alongside 88 others — read 8 August 2026
Crypto Life @cryptolifebro · 972,202 Telegram ranks this channel #2 of 89 here — alongside 88 others — read 8 August 2026
Crypto News @currentcryptonewsdaily · 936,894 Telegram ranks this channel #3 of 91 here — alongside 90 others — read 8 August 2026
Crypto Meme Foundation @CryptoMemeFoundation · 1,647,958 Telegram ranks this channel #3 of 90 here — alongside 89 others — read 7 August 2026
Chrono.tech NEWS @ChronotechNEWS · 934,219 Telegram ranks this channel #4 of 91 here — alongside 90 others — read 8 August 2026
Falcon Gambling @falcongambling · 89,324 Telegram ranks this channel #5 of 89 here — alongside 88 others — read 16 August 2026
Amazing World and Travel @amazingworldtravel · 947,626 Telegram ranks this channel #5 of 90 here — alongside 89 others — read 8 August 2026
Crypto AI/AGI/ASI @cryptoAIAGI · 968,180 Telegram ranks this channel #5 of 89 here — alongside 88 others — read 8 August 2026
PAXGold Channel @PAXGold_Channel · 51,433 Telegram ranks this channel #6 of 85 here — alongside 84 others — read 23 August 2026
DeFi Dive: TON & Beyond @defi_dive · 93,918 Telegram ranks this channel #6 of 90 here — alongside 89 others — read 13 August 2026
LaborX - Web3 Jobs l Crypto & Blockchain Jobs @laborx · 940,931 Telegram ranks this channel #6 of 91 here — alongside 90 others — read 8 August 2026
Crypto Games and Telegram mini Apps @NewsPlayToEarn · 2,070,710 Telegram ranks this channel #8 of 88 here — alongside 87 others — read 7 August 2026
CryptoSniper @cryptosniper_signals · 210,085 Telegram ranks this channel #12 of 85 here — alongside 84 others — read 11 August 2026
Naija Profit Zone @Naija_free · 936,053 Telegram ranks this channel #15 of 90 here — alongside 89 others — read 8 August 2026
Crypto Era | Trading, News, Airdrops @CryptoEraEng · 164,406 Telegram ranks this channel #17 of 88 here — alongside 87 others — read 12 August 2026
Coin Post – Money, Investments, Bitcoin @coinpost · 223,973 Telegram ranks this channel #17 of 86 here — alongside 85 others — read 10 August 2026
Crypto Mason 👁 Bitcoin News @thecrypto_mason · 153,796 Telegram ranks this channel #19 of 90 here — alongside 89 others — read 12 August 2026
Nairaland Pulse | News @Nigerii_News · 809,820 Telegram ranks this channel #19 of 90 here — alongside 89 others — read 8 August 2026
Pictographs.io | ENG News @pictographs_official · 84,054 Telegram ranks this channel #20 of 84 here — alongside 83 others — read 25 August 2026
NEVERSOL @never_sol · 572,973 Telegram ranks this channel #20 of 88 here — alongside 87 others — read 8 August 2026
Crypto Drop Club @drop_cryptogo · 1,327,326 Telegram ranks this channel #21 of 90 here — alongside 89 others — read 8 August 2026
Still Early @whalehunter_eng · 127,045 Telegram ranks this channel #22 of 90 here — alongside 89 others — read 13 August 2026
bookmaker.XYZ Announcements @xyzbookxyz · 146,375 Telegram ranks this channel #22 of 85 here — alongside 84 others — read 12 August 2026
Memecoin daily @memecoin_daily · 783,358 Telegram ranks this channel #22 of 90 here — alongside 89 others — read 8 August 2026
This channel appears in 66 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
16 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 November 2026 — this
entry's latest reading, not the date you are reading this.
“Learn to Earn” (@learn2earnings), 1,653,572 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/learn2earnings.
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.