International news — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 66% 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.
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 1 other registered channel. 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 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 26 comparable posts for this entry, running 31 July 2026 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 2, the earliest publisher we hold is @kavoshmedia — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 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 1 other registered channel, 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.
32 measurements spanning 43 days, net -237. 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 73,380–73,728 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
17 Sept 2026, 19:40
73,444
+21
15 Sept 2026, 19:36
73,423
-7
14 Sept 2026, 05:57
73,430
+6
12 Sept 2026, 16:58
73,424
-6
10 Sept 2026, 15:16
73,430
-5
7 Sept 2026, 10:17
73,435
-2
4 Sept 2026, 13:58
73,437
-4
3 Sept 2026, 00:18
73,441
+21
31 Aug 2026, 01:37
73,420
-28
30 Aug 2026, 03:53
73,448
-22
29 Aug 2026, 00:27
73,470
-11
27 Aug 2026, 21:46
73,481
-18
27 Aug 2026, 00:29
73,499
-6
26 Aug 2026, 00:33
73,505
-9
25 Aug 2026, 00:57
73,514
-38
23 Aug 2026, 10:57
73,552
-15
22 Aug 2026, 00:28
73,567
+4
20 Aug 2026, 22:03
73,563
-22
19 Aug 2026, 23:48
73,585
-10
18 Aug 2026, 21:02
73,595
first reading
Engagement
212 posts held, back to 31 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 97 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
14.6%
avg views ÷ 73,444 subscribers
Avg views / post
10,700
121 posts measured
Reaction rate
3.52%
reactions ÷ views · ER floor
Posts in window
121
of 212 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 22 September 2026
Posts held
212 (31 July 2026 – 22 September 2026)
Views total
1,300,300
Reactions total
45,794
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 00:50 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.
What this channel posts
Photos
≈223
Videos
≈4,150
Links
≈74
Lifetime counters from Telegram’s own channel header, read 23 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
12h 37m
Average length
3m 41s
Measured directly from 206 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.
Reaction mix
76,632 reactions across 206 posts, in 4 distinct kinds. The most used accounts for 75.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
57,575
75.1%
❤
18,800
24.5%
🤯
133
0.174%
😢
124
0.162%
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 212 of the 212 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 79,112 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 212 most recent posts we hold, published 31 July 2026 to 22 September 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
2
across the posts below
Posts paid on
2
of 212 we hold a reading for · 0.9%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @kavoshmedia. 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 212 most recent posts we hold for this entry, published 31 July 2026 to 22 September 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.
✅ روزنامهنگار آمریکایی:
📍فکر میکردند ظرف چهار روز کار تمام میشود و یک «دلسی رودریگز ایرانی» پیدا میکنند، اما محاسباتشان کاملاً غلط از آب درآمد...
🔻آمریکا به عنوان یک قدرت دریایی دارد مثل یک ببر کاغذی رسوا میشود، غذای ملوانهای آمریکایی جیرهبندی شد چون پایگاههای پشتیبانی با موشکهای ایران از کار افتادند...
🆔 @Kavoshmedia
✅ تحلیلگر ارشد و نماینده پیشین پارلمان کره جنوبی:
📍میدانید علت درخواست عاجل واشنگتن از کره جنوبی برای اعزام شناورهای رزمی چه بود؟ تمام پایگاههای نظامی آمریکا در ۸ کشور منطقه خلیج فارس ویران شدهاند؛ مقر فرماندهی ناوگان پنجم در بحرین غیرقابل بازسازی است...
🔻اسناد افشا شده نشان میدهد نیروهای آمریکایی در منطقه خلیج فارس با شدیدترین بحران لجستیکی و پشتیبانی تاریخ معاصر خود مواجه شدهاند...
#کرهای
🆔 @Kavoshmedia
✅ استاد ممتاز دانشگاههای ژاپن:
📍فرماندهان ایرانی تجربه جنگ دهه ۱۹۸۰ را دارند و با فشار و ترور دچار دستپاچگی نمیشوند. سیستم جانشینی دقیق، پراکندگی نیروها در تاسیسات زیرزمینی و راهبرد "دفاع موزائیکی"، ایران را به یک شبکه فرماندهی غیرمتمرکز و انعطافپذیر تبدیل کرده...
#ژاپنی
🆔 @Kavoshmedia
✅ جواب قاطع تحلیلگر ایرانی به کارشناس کویتی:
📍ادعا میکنی تنگه هرمز آمریکایی خواهد شد، بدان همچین چیزی را مگر در خواب و رویا ببینی، تنگه را تسخیر کردیم و یک لیوان آب هم روی آن خوردیم...
#عربی
🆔 @Kavoshmedia
✅ تحلیلگر ارشد و افسر بازنشسته ارتش چین:
📍با هدف قرار گرفتن نفتکشهای ایرانی و تشدید محاصره اقتصادی توسط آمریکا، گسترش حوزه درگیری به دریای سرخ، تدبیر متقابل تهران برای خنثیسازی تهدیدات واشنگتن بود...
🔻بازی همزمان در دو تنگه همافزایی بیسابقهای است که تحریمهای اقتصادی آمریکا را بیاثر و شوکهای سنگینی به بازار جهانی انرژی وارد کرد...
#چینی
🆔 @Kavoshmedia
✅ دیپلمات بازنشسته آمریکایی:
📍ایستادگی ایران در برابر هژمونی مشترک واشنگتن و تلآویو، یک رویداد بنیادین، عصرساز و نقطه پایانی بر 500 سال سیطره محور آتلانتیک بر غرب آسیا است...
🆔 @Kavoshmedia
✅ طنزپرداز آمریکایی از خجالت ترامپ درآمد!
📍الان دو تا تنگه داریم که نفت ازشون رد میشه و جفتشون هم بستهان؟! اصلاً چطور به این وضع رسیدیم؟!
🔻مهمتر از همه، کل این ماجرا نشون میده فرمانده کل قوامون چه شاهکاری تو مدیریت این جنگ به خرج داده! یعنی فقط یه نگاه به این گندکاری او بندازید...
🔻تنها خودرویی که الان راه میرود، ماشینی است که سوختش وعدههای دروغین رئیسجمهور است...
🆔 @Kavoshmedia
✅ کارشناس عرب:
📍ایالات متحده با توان آتشباری و محاصره شدید اقتصادی به دنبال تسلیم ایران است، اما تهران با یک «استراتژی معکوس» اهرمهای فشار واشنگتن را به ابزاری علیه اقتصاد جهانی و آمریکا تبدیل کرده است...
🔻گشودن جبهههای جدید مانند بابالمندب، ترامپ را سردرگم ساخته و او را میان تماشای تهدید کشتیرانی یا ورود به باتلاق یمن معلق گذاشته است...
#عربی
🆔 @Kavoshmedia
✅ تحلیلگر ارشد نظامی و معاون سابق نیروی هوایی تایوان:
📍خواست ایران بسیار روشن و ساده است؛ آنها میگویند همانگونه که از ما میخواهید دست به توسعه و ساخت تسلیحات هستهای نزنیم، باید همین الزام را برای اسرائیل نیز ایجاد کنید...
🔻ایران محق است که بگوید: «چرا مرا بازرسی میکنید اما کاری با اسرائیل ندارید؟ مگر هر دو در منطقه خاورمیانه نیستیم؟ چرا دو استاندارد متفاوت وجود دارد؟»
🆔 @Kavoshmedia
✅ ژنرال بازنشسته آمریکایی:
📍من به راهبرد امنیت ملی فکر میکنم که صریحاً گفته بود تمرکز ما قرار است روی امنیت داخلی و چین باشد. پس ما اساسا در ایران چه غلطی میکنیم؟!
🔻چرا درباره خسارتهایی که در جنگ با ایران وارد شده، با مردم آمریکا صادق نیستیم؟ احتمالاً صدها میلیارد دلار به داراییهای ما در آنجا خسارت وارد شده و مردم آمریکا اصلاً از آن خبر ندارند...
🆔 @Kavoshmedia
✅ استاد علوم سیاسی و مدیر مطالعات خاورمیانه دانشگاه سانفرانسیسکو:
📍ترامپ سادهلوحانه تصور میکرد حملات اولیه آمریکا و اسرائیل باعث سرنگونی حکومت ایران میشود/سیاستهای او مبتنی بر شتابزدگی، رفتارهای تکانهای و غرور است و اکنون در یک بنبست بزرگ گرفتار شده و هیچ راهکاری برای خروج از این نبرد ندارد...
🔻پاسخهای ایران اقتصاد جهانی را متزلزل کرده؛ ادامه تجاوزات آمریکا و عدم پذیرش خطا از سوی ترامپ، پیامدهای سنگین و وح…
✅ متخصص مسائل ژئوپلیتیک خاورمیانه:
📍کنترل انصارالله بر بابالمندب، اهرم چانهزنی بیسابقهای به ایران و متحدانش داده و منطقه را از ساختار تکقطبی آمریکا به سمت الگوی چندقطبی سوق داده است...
🔻بیتوجهی واشنگتن به نیازهای امنیتی متحدانش نشاندهنده فرسایش اعتبار تعهدات آمریکا و درک تغییر موازنه قوا در منطقه است...
#چینی
🆔 @Kavoshmedia
👍248❤25
Showing the 12 most recent of 212 posts we hold for @kavoshmedia. 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
@kavoshmedia edited 2 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
9 September 2026
Most recent edit
12 September 2026
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 29 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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 19 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.
تحلیلگر سیاسی (محمد ندیمی) @tahlilgar_siasi · 35,534 Telegram ranks this channel #2 of 88 here — alongside 87 others — read 2 September 2026
خط انرژی @khate_energy · 38,374 Telegram ranks this channel #2 of 91 here — alongside 90 others — read 31 August 2026
جدال- علی عليزاده @jedaal · 57,028 Telegram ranks this channel #2 of 92 here — alongside 91 others — read 23 August 2026
اخبار سوریه @syriankhabar · 89,201 Telegram ranks this channel #2 of 95 here — alongside 94 others — read 17 August 2026
آموزش سواد سایبری @Cyber_Literacy · 27,902 Telegram ranks this channel #4 of 86 here — alongside 85 others — read 10 September 2026
آقای تحلیلگر 🇮🇷✌️ @mrtahlilgar · 91,296 Telegram ranks this channel #5 of 91 here — alongside 90 others — read 17 August 2026
دفاع مدیا @defa_lr · 21,760 Telegram ranks this channel #6 of 85 here — alongside 84 others — read 22 September 2026
ایران،شهر خورشید @iran_cityofsun · 24,062 Telegram ranks this channel #9 of 89 here — alongside 88 others — read 17 September 2026
فرزند ایران @farzandeiran_ir · 26,090 Telegram ranks this channel #9 of 89 here — alongside 88 others — read 13 September 2026
طنز سیاسی دکترسلام @drsalaam · 34,093 Telegram ranks this channel #9 of 95 here — alongside 94 others — read 3 September 2026
جنگ پژوهی🪖 @updateworlddnews · 48,040 Telegram ranks this channel #9 of 87 here — alongside 86 others — read 26 August 2026
Masaf | مؤسسه مصاف @masaf · 188,915 Telegram ranks this channel #9 of 94 here — alongside 93 others — read 11 August 2026
مسلمان تی وی | Mosalman Tv @mosalman_tv · 22,425 Telegram ranks this channel #10 of 75 here — alongside 74 others — read 20 September 2026
تفسیرگر | علیرضا تقوی نیا @taghaviniaa · 23,779 Telegram ranks this channel #10 of 91 here — alongside 90 others — read 17 September 2026
جواد موگویی|حرف بیحساب @javadmogoei · 35,536 Telegram ranks this channel #11 of 93 here — alongside 92 others — read 2 September 2026
اخبار ارتش جمهوری اسلامی ایران @artesh · 60,206 Telegram ranks this channel #11 of 87 here — alongside 86 others — read 22 August 2026
رائفے پور (غیر رسمی) @ostadaliakbarraefipour · 36,307 Telegram ranks this channel #12 of 86 here — alongside 85 others — read 1 September 2026
چریکهای جنگ نرم @chrik_ir · 29,222 Telegram ranks this channel #13 of 83 here — alongside 82 others — read 8 September 2026
أخٌفيالله @mhrezaa2 · 39,365 Telegram ranks this channel #13 of 89 here — alongside 88 others — read 30 August 2026
مقاومت اسلامی انصارالله یمن @Ansaroollah · 26,503 Telegram ranks this channel #17 of 85 here — alongside 84 others — read 12 September 2026
آرشیو سخنرانیهای استاد رائفیپور @Masafbox · 79,341 Telegram ranks this channel #17 of 93 here — alongside 92 others — read 19 August 2026
بیداری ملت @bidariymelat_ir · 22,611 Telegram ranks this channel #19 of 76 here — alongside 75 others — read 20 September 2026
RaefipourFans @raefipourfans · 64,483 Telegram ranks this channel #19 of 94 here — alongside 93 others — read 21 August 2026
🎬 بیسیمچی مدیا @bisimchimedia · 1,012,215 Telegram ranks this channel #20 of 91 here — alongside 90 others — read 8 August 2026
This channel appears in 103 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.
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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“کاوش مدیا” (@kavoshmedia), 73,444 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/kavoshmedia.
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.