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 10 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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 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)
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. 36 of the 36 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 37 comparable posts for this entry, running 5 August 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 5, the earliest publisher we hold is @americanislam. That is a statement about our reading window, not a claim of authorship.
Views per post sit far below this size band
7.6 average views per post against 16,543 subscribers — an engagement rate of 0.046%. Across the 7,490 registered channels in the same cohort — 10,001–31,611 subscribers, posting mainly in Persian — the middle half sit between 3.83% and 17.6%, with a median of 8.86%.
What this was computed from
Window
30 days (13 July 2026 – 12 August 2026)
Posts measured
109 of 109 published in the window (109 exact, 0 rounded by Telegram)
Views totalled
828
Mature posts only
0.062% over 40 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the keys clone_copy · err_low, last confirmed 12 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 4 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.
5 measurements spanning 6 days, net -65. 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 16,533–16,618 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 12:06
16,543
-22
9 Aug 2026, 07:53
16,565
-10
8 Aug 2026, 11:04
16,575
-19
7 Aug 2026, 11:20
16,594
-14
6 Aug 2026, 14:01
16,608
first reading
Engagement
109 posts held, back to 5 August 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 16 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
0.046%
avg views ÷ 16,543 subscribers
Avg views / post
7.6
109 posts measured
Reaction rate
8.11%
reactions ÷ views · ER floor
Posts in window
109
of 109 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 3 of 109 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 August 2026
Posts held
109 (5 August 2026 – 11 August 2026)
Views total
828
Reactions total
3
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 10:05 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
Video runtime
1h 06m
Average length
1m 29s
Measured directly from 45 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
3 reactions across 3 posts, in 1 kind.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
3
100.0%
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 3 of the 109 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 3reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 109 most recent posts we hold, published 5 August 2026 to 11 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.
📌پتروپالایشگاه ۱۲۰ هزار بشکهای «مهر خلیج فارس» مراحل پایانی ساخت خود را طی میکند.
📌فاز اول این پالایشگاه با تولید روزانه ۱۳.۵ میلیون لیتر بنزین در نیمه دوم سال جاری وارد مدار خواهد شد.
📌همچنین با راهاندازی فاز دوم در سال آینده، ۱۲ میلیون لیتر دیگر به ظرفیت تولید بنزین ایران افزوده میشود.
🔞 روایتی تکان دهنده از تاریخ
اگر این روزها از جنایات #پهلوی و سلطنتطلبان متعجب شدین، این کلیپ رو ببینید تا متوجه بشین این کارا برای #رضاشاه ، پز نیست؛ سبک زندگیه!!
بر سر مسافت دویدن اجساد بی سر، شرطبندی میکردند و بر سر تعداد قدمهایی که اجساد میتوانند بدوند، برد و باخت راه میانداختند..!
💢قرارگاه خاتمالانبیا با ستاد کل نیروهای مسلح ادغام شد
🔹قرارگاه مرکزی خاتمالانبیا(ص) و ستادکل نیروهای مسلح، دو رکن اصلی ساختار فرماندهی دفاعی کشور، در پی تحولات نظامی سالهای ۱۴۰۴ و ۱۴۰۵ و تجربه جنگهای تحمیلی دوم و سوم، در یک مجموعه واحد ادغام شدند.
🔹قرارگاه خاتم در ۳۰ بهمن ۱۳۶۲ و در آستانه عملیات خیبر برای ایجاد فرماندهی مشترک میان ارتش و سپاه شکل گرفت؛ ستاد فرماندهی کل قوا نیز در سال ۱۳۶۷ برای هماهنگی کلان نیرو…
🚨چند نکتۀ معنادار در احکام اخیر نصب فرماندهان نظامی از سوی فرماندۀ کل قوا
1️⃣حرف و حدیثها درمورد ادغام ستاد کل نیروهای مسلح و قرارگاه مرکزی خاتم الانبیاء(ص) که از زمان رهبر شهید مطرح بود رنگ واقعیت به خود گرفت.در حکم سرلشکر عبداللهی تکمیل روند ادغام از ماموریتهای رئیس ستادکل عنوان شده.
2️⃣ادغام قرارگاه مرکزی خاتمالانبیا(ص) و ستاد کل نیروهای مسلح در یکدیگر یعنی متمرکز شدن فعالیتهای جنگی، نظامی و تهاجمی کشور و همچن…
⭕️ صحبتهای ضدواکسن ترامپ سگ زرد:
برخی از گروهها تقریباً هیچ مشکلی با اوتیسم ندارند.
این گروهها، افرادی هستند که به شدت به دنیای واکسنها علاقهمندند.
هر سال، میزان ابتلا به اوتیسم افزایش مییابد، و این افزایش روز به روز بیشتر میشود.
واکسیناسیون برای بیماریهایی مانند هپاتیت B، کووید-19 و آنفولانزا، و سایر بیماریها، دیگر برای همه کودکان توصیه نمیشود.
🔴 محمد مرندی: ایران آگاه است که نیروهای رژیم ترامپ در کویت، امارات متحده عربی، قطر، عربستان سعودی، بحرین و اردن در حال بسیج برای یک حمله برقآسای بالقوه احتمالاً در کنار نیروهای اسرائیلی علیه مردم ایران هستند.
🔹جمهوری اسلامی با پاسخی سریع و کوبنده آماده است.
🔺سخنگوی سپاه: موشکهای ایران قابلیت تغییر مسیر دارند
موشکهای ما قابلیت هدایت دارند و حتی برخی موشکها میتوانند در برابر سامانههای پدافندی دشمن تغییر مسیر دهند.
حتی اگر برای موشکی یک هدف مشخص شده باشد، میتوانیم در میانۀ مسیر هدف ثانویهای برای آن تعیین کنیم.
🔺نظامی سابق آمریکا: روند خروج ما از منطقه آغاز شده
🔹اسکات ریتر، نظامی بازنشستۀ آمریکایی: ارتش آمریکا بخش قابلتوجهی از ذخایر موشکهای دورایستا و مهمات دقیق خود را مصرف کرده و ذخایر تاماهاوک نیز کاهش یافته.
🔹در نتیجه آمریکا برای حمله به اهداف عمیق در داخل ایران با کمبود سلاحهای دورایستا مواجه است.
🔹آمریکا عملاً در مسیر عقبنشینی تدریجی از غرب آسیا قرار گرفته؛ هرچند ترامپ احتمالاً حاضر نخواهد بود این روند را بهصور…
🎥 افسر بازنشستۀ آمریکا: ایران معادلات را از هستهای به تنگۀ هرمز تغییر داد
🔹ویلیام پاتنم: هدف آمریکا همیشه این بود که ایران به سلاح هستهای دست پیدا نکند اما امروز تمام تمرکز آمریکا روی بازکردن تنگۀ هرمز است.
🔹اقدامات نظامی آمریکا تاکنون نتوانسته به اهداف تعیینشده علیه ایران منتهی شود.
Showing the 12 most recent of 109 posts we hold for @Twitter_motalebe. 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
@Twitter_motalebe edited 1 post 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 August 2026
Most recent edit
9 August 2026
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 August 2026 — this
entry's latest reading, not the date you are reading this.
“توییتر مطالبه گری” (@Twitter_motalebe), 16,543 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/Twitter_motalebe.
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.
