Politics & activism — 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 11 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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 1 other registered channel. This entry also sits inside a group of 4 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts 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 (1 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. None of the 0 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 18 comparable posts for this entry, running 10 March 2019 to 9 June 2020. 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).
Of the group of 4 channels, the one whose matching posts we hold earliest is @campe85 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
Channels linked by matching posts
This channel is in a group of 4 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
24 measurements spanning 101 days, net -51. 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 2,892–2,959 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)
Subscribers
Change
15 Nov 2026, 01:06
2,900
-4
9 Nov 2026, 19:58
2,904
-2
6 Nov 2026, 05:51
2,906
-5
3 Nov 2026, 00:21
2,911
-1
31 Oct 2026, 10:07
2,912
-2
28 Oct 2026, 13:46
2,914
-2
25 Oct 2026, 22:41
2,916
-1
20 Oct 2026, 02:30
2,917
-2
16 Oct 2026, 18:47
2,919
-3
13 Oct 2026, 21:20
2,922
-3
8 Oct 2026, 12:15
2,925
-2
2 Oct 2026, 01:55
2,927
-4
12 Sept 2026, 18:19
2,931
-1
8 Sept 2026, 20:40
2,932
-4
3 Sept 2026, 14:16
2,936
-2
27 Aug 2026, 22:56
2,938
-1
24 Aug 2026, 22:14
2,939
-3
21 Aug 2026, 13:58
2,942
-2
18 Aug 2026, 15:48
2,944
-1
15 Aug 2026, 07:08
2,945
first reading
Engagement
20 posts held, back to 10 March 2019 — 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 17 July 2022. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
5m 06s
Average length
1m 42s
Measured directly from 3 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.
نظام جمهوری اسلامی چقدر مظلوم واقع شده !
کسانی مانند محمد رضا حیاتی که بر سر سفره میلیاردی انقلاب آنهم نه میلیارد الان میلیارد سال ۱۳۸۰ می خوردند حالا که سرمایه ای ادر آن سوی آبها فراهم کرده اند میخواهند خودشان را اپوزوسیون کنند بعید نیست #محمد_رضا_حیاتی سر از #من_و _تو و ایران اینترنشنال درآورد
دقیقا به همین دلیل وقتی زن ابی به محسن چاووشی توهین کرد تا خبر ها داغ بود طرف ابی و در واقع عربستان سعودی را گرفت
منتظر …
گفتم شاید این ویدیو قدیمی رو شما ندیده باشید...
مهدی هاشمی رفسنجانی تو آمبولانس حمل جنازه آیة الله هاشمی:
از اونجا یه عكس از من بگیر
#آقازاده_نیوز
بلندگوی افشاگری و مبارزه با فساد و رانت
⚖️ @aghazadeh24
#آقازاده_نیوز
🔻منبع محرمانه ترین اخبار بدون سانسور رسانه های ایران
👈 روابط آقازادگی
👈 رانت
👈 فساد
❌ کافیه اسم یه #آقازاده رو توی کانال سرچ کنی❌
⚖️ https://t.me/joinchat/AAAAAFEyg3KkWzQWjUvaUQ
💢تجارت 13هزار میلیاردی با استفاده از جیب مردم
🔹به تازگی برخی شرکت های خدمات ارزش افزوده به دنبال برخی مقررات موجود، نامه ای به سران قوا ارسال کردن و از هجمه های مکرر به این صنعت شکایت کردند!
در حالی که این شرکت های خدمات بر ارزش افزوده مالیات زیادی از مردم دریافت می کنند و خدمات بسیار ضعیفی ارائه می کنند، از افزایش رضایت مشتری و ایجاد 30 هزار شغل در کشور سخن می گویند.(دروغ که حناق نمیشه از گلو مسئولین دروغگو در بیا…
اینم وضعیت نوه عسکراولادی و سرنوشت پول های مرحوم
بهادر خان علاقه زیادی به فاحشه ها و سایت های شرط بندی دارد...
#آقازاده_نیوز
بلندگوی افشاگری و مبارزه با فساد و رانت
توئیتر:
⚖️ https://twitter.com/meysam_yousefy
تلگرام:
⚖️ https://t.me/joinchat/AAAAAFEyg3KkWzQWjUvaUQ
مجالس حسینی باید ظلم ستیز و ضد فساد باشه ، نه محفل تخدیر جامعه توسط ابن زیاد ها و معرفی حسینی که یزید معرفی کرد!
وگر نه شمر و کوفیان هم عاشورا گریه کردند.
#کاسبان_محرم
🔗 یـــפּــωــ؋
#آقازاده_نیوز
بلندگوی افشاگری و مبارزه با فساد و رانت
⚖️ https://t.me/joinchat/AAAAAFEyg3KkWzQWjUvaUQ
🔴 حجت الاسلام والمسلمین #مقتدایی عضو شورایعالی حوزه و عضو جامعه مدرسین و صاحب نظریه مخالفت با #روحانی، مخالفت با امام زمان(عج) است، در افتتاحیه حوزه اشرافی امام حسن مجتبی(ع) لواسان متعلق به حجت الاسلام #ناطق_نوری حضور یافت!
🔗 یـــפּــωــ؋
#آقازاده_نیوز
بلندگوی افشاگری و مبارزه با فساد و رانت
⚖️ https://t.me/joinchat/AAAAAFEyg3KkWzQWjUvaUQ
⭕️با «بهروز ریختهگران» بیشتر آشنا شوید /خرید بانک بدون پول!
▪️بهروز ریختهگران را شاهمهره پرونده فساد در بانک سرمایه میدانند؛ با این حال، او در جلسات دادگاه بانک سرمایه غایب بود و تازه همین هفته پیش در ارتباط با این پرونده بازداشت شد!
▪️اوج داستان ریختهگران از خرید بخش قابل توجهی از سهام بانک سرمایه شروع میشود. او در اسفند سال ۸۶، یعنی زمانی که محمدباقر قالبیاف شهردار تهران بود، برای خرید بانک سرمایه اقدام می…
۵۰ شخصیت حقیقی که بیشترین ارز نیمایی را دریافت کردهاند.
#آقازاده_نیوز
قرارگاه افشاگری و مبارزه با فساد و رانت
⚖️ https://t.me/joinchat/AAAAAFEyg3KkWzQWjUvaUQ
🔹با توجه به ترور نا جوانمردانه طلبه همدانی و رشته توئیت های مهناز افشار که از علت های ترور فوق بوده به کمپین #محاکمه_مهناز_افشار بپیوندید و برای دوستان و گروه های خود ارسال کنید:
https://t.me/joinchat/E6Bn91VExHibl3ORR7XnaQ
🔹مطالبه گر حق باشیم ...
#لطفا_انتشار_دهید
کانال سپاه سایبری ایران
🇮🇷 @sepah_cyberi_iran
Showing the 12 most recent of 20 posts we hold for @campe85. 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.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
2
vacant every time we have ever looked
@campe85 named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@aghazadeh2 named in 1 post, 8 August 2026 – 8 August 2026
@gharargahe_admin named in 1 post, 8 August 2026 – 8 August 2026
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 15 November 2026 — this
entry's latest reading, not the date you are reading this.
“کمپ ترک هنرهای تجسمی” (@campe85), 2,900 subscribers as measured 15 November 2026. Telegram Register, tgregister.com/channel/campe85.
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.
