Art & design — 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 41% 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 word for word on 2 other registered channels. They sit inside a group of 377 channels that share the same post bodies with each other. 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)
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. None of the 2 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 2,250 comparable posts for this entry, running 3 September 2025 to 7 August 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).
Across the whole group of 377, the earliest publisher we hold is @mash. That is a statement about our reading window, not a claim of authorship.
Views and reactions moved apart
On 29 of the 270 posts we watched over 30 days, the view counter climbed while the reaction counter stayed where it was — by more than this channel’s own reactions-per-view rate can account for. That rate, measured on this entry, is 0.0032 reactions per view.
Each interval, as we read it — views and reactions before and after
Expected is the view gain multiplied by this channel’s own prior reactions-per-view rate over the same post — not a corpus average, so a channel whose audience never reacts is compared only against itself. Every interval is credited in the direction that makes the observation harder to record, never easier: t.me renders views and reactions to three significant figures above ~1,000, so a raw delta can be a rendering step. Every delta below is at least 4 x the coarser reading's step, the view gain is discounted by a full step and the reaction gain credited with one. Measured by tgregister velocity.py (our own t.me/s/ readings).
What this does and does not say. It says the two counters moved apart, by more than rounding and more than this channel’s own history predicts. It asserts no cause. Views arriving from outside Telegram, an embedded or forwarded copy of the post, and a burst of readers who simply do not react all produce this shape. This detector has recorded very few observations across the whole register, and its precision has not been measured; treat it as an anomaly worth looking at, not as a finding.
Recorded under the keys clone_mutual · clone_source · view_reaction_decoupling, last confirmed 6 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 376 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
326 more channels are in this same group but not listed individually here.
Growth
60 measurements spanning 92 days, net +630,740. 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 2,676,626–3,498,850 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
6 Nov 2026, 08:36
3,402,238
-1,740
5 Nov 2026, 06:10
3,403,978
+16
4 Nov 2026, 05:45
3,403,962
+2,458
3 Nov 2026, 06:27
3,401,504
+1,174
2 Nov 2026, 02:40
3,400,330
+25,580
1 Nov 2026, 05:26
3,374,750
+7,112
31 Oct 2026, 08:44
3,367,638
+6,016
30 Oct 2026, 06:58
3,361,622
-3,222
29 Oct 2026, 04:41
3,364,844
+88
27 Oct 2026, 23:56
3,364,756
+2,650
26 Oct 2026, 21:56
3,362,106
+2,860
25 Oct 2026, 18:55
3,359,246
+13,259
24 Oct 2026, 18:56
3,345,987
+9,363
23 Oct 2026, 16:36
3,336,624
+8,338
22 Oct 2026, 14:48
3,328,286
-9,121
21 Oct 2026, 05:57
3,337,407
+7,960
20 Oct 2026, 03:47
3,329,447
+17,865
19 Oct 2026, 02:16
3,311,582
-2,553
18 Oct 2026, 01:26
3,314,135
+4,372
17 Oct 2026, 02:56
3,309,763
first reading
Engagement
3,908 posts held, back to 3 September 2025 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 4,574 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
1.54%
avg views ÷ 3,402,238 subscribers
Avg views / post
52,400
272 posts measured
Reaction rate
0.321%
reactions ÷ views · ER floor
Posts in window
272
of 3,908 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 November 2026
Posts held
3,908 (3 September 2025 – 6 November 2026)
Views total
14,265,440
Reactions total
45,776
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 12:26 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 272 of this channel’s own posts over the last 30 days (1 of the 24-hour readings behind this are interpolated, not measured directly): across 262 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 3.7 hours of being posted; a typical post has already reached 25.6% of its 24-hour view count within the first hour, and 74.1% within the first six; the median 24-hour reach across those posts is 38,550 views — 1.13% of this channel’s own subscriber count (90th percentile 75,970).
8 most recently posted, with a view-velocity reading
2.3 hoursprovisional — final view count still climbing
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.
Recent posts
Telegram’s own ‘edited’ marker: 7 of 272 posts held from the last 30 days (2.57%) 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).
Гжель со СПОРТСМЕНАМИ вместо привычных цветов — Гжельский фарфоровый завод и художница Дарья Фетисова выпустили коллекцию «Синее на белом» с гимнастами, боксёрами и всадниками. Каждый предмет расписан вручную и существует в единственном экземпляре.
Спорт — это жизнь 🌟
В Казахстане лес больше ста лет стоит под водой. В 1️⃣9️⃣1️⃣1️⃣ году землетрясение вызвало оползень, который перекрыл реку. Вода затопила еловый лес — так появилось озеро Каинды.
Над бирюзовой гладью до сих пор торчат голые стволы, а под водой сохранились ветви деревьев. Холодная вода замедлила разложение, превратив лес в подводный памятник землетрясению.
Казахстан опять могает в природном плане 🔫
Шарф в виде огромной РОЗОВОЙ ПАНТЕРЫ придумала дизайнер Ming — необычный аксессуар с головой, лапами и хвостом животного можно носить на плечах или оборачивать вокруг шеи.
У вас же тоже в голове заиграла та самая мелодия? 😱
В Копенгагене открывают общественные бани из 3️⃣0️⃣0️⃣ тысяч кирпичей ручной работы. Архитектор Кэнго Кума спроектировал пять башен с десятью бассейнами, тремя саунами и парной.
Между башнями расположился бассейн под открытым небом, рядом — тёплый онсэн с видом на гавань. Открытие — 5️⃣ декабря, а в начале 2️⃣0️⃣2️⃣7️⃣ года добавят зоны для купания прямо в гавани.
Сейчас бы в баньку 🌹
Британский бренд HADES выпустил кардиган С СИГАРЕТАМИ вместо пуговиц — ярко-зелёную модель украшают имитации окурков с пеплом на кончиках.
Курение вредит вашему здоровью, но никто не сказал, что если не курить, можно сойти с ума 😮💨
Прокофьев был настоящим троллем ещё до появления интернета. Уже в 1️⃣3️⃣ лет он пародировал директора консерватории, подкладывая подушку под пальто, а в 1930-х рассекал по Москве в жёлтых ботинках, клетчатом костюме и красно-оранжевом галстуке.
Композитор не боялся выделяться и нарушать правила. Больше историй о его выходках и творчестве вы можете узнать в проекте «Три жизни Сергея Прокофьева».
Дизайнер Пол Харди обжигает стулья, чтобы огонь сам оставил на них рисунок. Его USTIO CHAIR сделан из стали, раскроенной плазмой: после нагрева на металле появляются цветные разводы, которые невозможно повторить в точности.
Следы обжига не шлифуют и не исправляют — они и становятся финальной отделкой. Каждый стул получается со своим узором 🌟
В Москве придумали оберег от М*ДАКОВ в виде обычной английской булавки. Необычное украшение выпускает московский ювелирный бренд «По кругу». Булавку можно приколоть к одежде, повесить на цепочку или просто носить с собой в качестве талисмана.
Аксессуар делают из серебра 9️⃣2️⃣5️⃣ пробы, в том числе с покрытием золотом 9️⃣9️⃣9️⃣ пробы. На выбор три размера — S, M и King-size. А надпись «От м*даков» можно заменить соб…
❤86👎21😁9👍7
Showing the 12 most recent of 3,908 posts we hold for @TRND_X. 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.
Posts edited after publishing
@TRND_X edited 13 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
17 August 2026
Most recent edit
3 November 2026
Posts recorded as deleted after publishing
We recorded 1 post on @TRND_X as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
12 September 2026
Most recent seen missing
12 September 2026
Median time before seen missing
6.2 hours
Seen missing in the last 30 days
0
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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
Named by 9 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.
Domains linked from posts
54 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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“TRNDX.” (@TRND_X), 3,402,238 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/TRND_X.
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.
