کافهتدریس پلتفرم یادگیری و آموزش آنلاینه، توی این کانال با محتواهای اختصاصی، همراه با اساتید و مشاورهای باتجربه، رتبهبرترها و حرفهایهای بازار کار کنارتون هستیم.
https://cafetadris.com
شماره تیم پشتیبانی
021 - 91305040
Created
Between 1 May 2016 and 28 February 2017 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Education — 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 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 forms a group of 2 channels linked by matching posts. 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 27 comparable posts for this entry, running 2 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).
Of the group of 2 channels, the one whose matching posts we hold earliest is @konkoorMBA. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, 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.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. 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.
64 measurements spanning 97 days, net +592. 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 11,878–12,649 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)
Subscribers
Change
10 Nov 2026, 12:56
12,560
+9
8 Nov 2026, 23:59
12,551
+2
7 Nov 2026, 15:49
12,549
+7
6 Nov 2026, 12:01
12,542
+2
5 Nov 2026, 12:48
12,540
-2
4 Nov 2026, 09:51
12,542
+8
3 Nov 2026, 13:19
12,534
-2
2 Nov 2026, 13:10
12,536
-11
1 Nov 2026, 14:29
12,547
+7
31 Oct 2026, 16:06
12,540
+12
30 Oct 2026, 12:30
12,528
+5
29 Oct 2026, 10:09
12,523
-1
28 Oct 2026, 11:18
12,524
+10
27 Oct 2026, 13:16
12,514
-1
26 Oct 2026, 12:30
12,515
+6
25 Oct 2026, 13:15
12,509
-2
24 Oct 2026, 16:36
12,511
-2
23 Oct 2026, 16:39
12,513
+14
22 Oct 2026, 15:54
12,499
+1
21 Oct 2026, 11:06
12,498
first reading
Engagement
191 posts held, back to 2 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 64 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
6.60%
avg views ÷ 12,560 subscribers
Avg views / post
829
47 posts measured
Reaction rate
1.04%
reactions ÷ views · ER floor
Posts in window
47
of 191 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 10 November 2026
Posts held
191 (2 August 2026 – 10 November 2026)
Views total
38,940
Reactions total
405
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 19:49 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
≈7,330
Videos
≈511
Links
≈7,430
Lifetime counters from Telegram’s own channel header, read 10 November 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
6m 08s
Average length
1m 32s
Measured directly from 4 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
1,618 reactions across 183 posts, in 11 distinct kinds. The most used accounts for 55.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
898
55.5%
👍
344
21.3%
🔥
247
15.3%
🤩
43
2.66%
👏
22
1.36%
👌
20
1.24%
🫡
12
0.742%
🎃
10
0.618%
🤔
9
0.556%
🤯
8
0.494%
💯
5
0.309%
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 189 of the 191 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 1,659 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 191 most recent posts we hold, published 2 August 2026 to 10 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
10
across the posts below
Posts paid on
1
of 190 we hold a reading for · 0.5%
Most on one post
10
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Cafetadris. 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 191 most recent posts we hold for this entry, published 2 August 2026 to 10 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: 1 of 47 posts held from the last 30 days (2.13%) 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).
▪️ سلسله وبینارهای رایگان هوش مصنوعی برای همه
از ساخت AI Agents تا راهاندازی کسبوکار با هوش مصنوعی
➕ توی این وبینارها، از حل مسائل واقعی کسبوکار با ایجنتهای هوشمند تا ساخت محصولات AI و راهاندازی کسبوکارهای یکنفره، باهامون همراه شو!
📌 ایجنتسازی در کسبوکار؛ از مسئله واقعی تا راهکار هوشمند
🗓 شنبه، ۲۳ آبان | ساعت ۲۰
📌 طوفان محصولات هوش مصنوعی؛ اصولی برای کسبوکارهای تکنفره
🗓 دوشنبه، ۲ آذر | ساعت ۲۰
توی این …
🚀 گفتوگوی ویژه با رتبه ۹۷ کنکور ارشد MBA
🎓 توی این مصاحبه، مبین عصاری، رتبه ۹۷ کشوری کنکور ارشد MBA، از تجربهها، منابع و روشهای مطالعهش میگه و توضیح میده که چطور تونست توی این کنکور چالشبرانگیز به نتیجه برسه.
📣 برای دیدن ویدیوی کامل مصاحبه از لینکهای زیر استفاده کنید:
🔸 مشاهده ویدیو در آپارات
🎞 مشاهده ویدیو در یوتیوب
@konkoorMBA | دپارتمان MBA
🟡 پرسشوپاسخ تلگرامی ویژه کنکور ارشد مدیریت
اگه قصد داری برای یکی از رشتههای کنکور ارشد مدیریت امسال بخونی، این پرسش و پاسخ رو از دست نده. هر سوالی از مسیر آمادگی کنکور مدیریت داری، امشب ساعت ۲۰ سوالت رو توی گروه بپرس تا پاسخش رو از استاد محمدپور بگیری.
⏰ساعت ۲۰:۰۰
📌 برای شرکت توی پرسشوپاسخ عضو این گروه بشین:
👉🔗 https://t.me/konkoormodiriat_group
📍 کانال تخصصی کنکور ارشد و دکتری مدیریت:
@konkoormodiriat
🤩 استرس کنکور؛ چطور اضطراب رو کنترل کنیم و با تمرکز بیشتری درس بخونیم؟
هرچی به کنکور نزدیکتر میشیم، ممکنه نگرانی درباره نتیجه آزمون، حجم درسهای باقیمونده و مقایسه خودمون با بقیه بیشتر بشه. اما استرس زیاد میتونه تمرکز، کیفیت مطالعه و حتی عملکردمون سر جلسه آزمون رو تحت تأثیر قرار بده. توی این مقاله با دلایل استرس کنکور و راهکارهای کاربردی مدیریت اون آشنا میشیم؛ از برنامهریزی واقعبینانه و تنظیم خواب گرفته تا تک…
🚨 کمتر از ۱ روز تا شروع رویداد حضوری MBA 360!
یه فرصت ویژه برای داوطلبان کنکور MBA سال ۱۴۰۶!
توی رویداد حضوری MBA 360 کافهتدریس قراره از نزدیک با اساتید دپارتمان MBA همراه بشیم، توی کلاسهای آموزشی شرکت کنیم و برای مسیر کنکور مشاوره تخصصی بگیریم.
📌 برنامههای رویداد:
➕ کلاس حضوری ریاضی و GMAT
➕ آموزش زبان و رفع اشکال
➕ پنل مشاوره تخصصی با اساتید MBA
🗓 فردا، سهشنبه ۱۹ آبان | ساعت ۱۵
⚠️ ظرفیت محدوده! اگه هنوز ثبت…
▶️ ویدیو کامل مصاحبه با دریا واحد
تجربه داوطلبین سال پیش میتونه چراغی باشه که مسیر رو بهتر ببینیم. توی این ویدیو، دریا واحد از تجربه خودش کامل صحبت کرده.
✔️ رتبه ۶۷ کنکور ارشد مدیریت صنعتی
✔️ رتبه ۱۱۲ کنکور ارشد مدیریت بازرگانی
✔️ رتبه ۱۲۰ کنکور ارشد مدیریت فناوری اطلاعات
✔️ رتبه ۱۴۴ کنکور ارشد مدیریت فناوری
📌 ویدیو کامل در یوتیوب:
👉🔗 https://youtu.be/d2NsJ85ks8Y
📌 ویدیو کامل در آپارات:
👉🔗 https://aparat.com…
🚨 فقط ۱ ساعت تا شروع وبینار رایگان جبر خطی!
جبر خطی به کنکور ارشد کامپیوتر اضافه شده؛ چطور براش آماده بشیم؟
توی این وبینار همراه با رضا شکرزاد، مدرس جبر خطی، با سرفصلهای مهم، نمونه سؤالات کنکور و بهترین منابع و روش مطالعه این درس آشنا میشیم.
⏰ امشب، دوشنبه ۱۸ آبان | ساعت ۲۰
🎁 شرکت در وبینار کاملاً رایگانه!
🔴 فرصت رو از دست نده، همین حالا ثبتنام کن:
🔗 https://ctdrs.ir/cr18624
🔗 https://ctdrs.ir/cr18624
@cafet…
📌 توضیحات علیرضا مروج درباره رویداد حضوری MBA 360 | ویژه داوطلبان کنکور ۱۴۰۶
📚 در بخش GMAT این رویداد چه برنامههایی داریم؟
⦿ بررسی استراتژی صحیح و هدفمند مطالعه GMAT
⦿ شناخت مباحث و موضوعات مهم و اولویتبندی اونها در کنکور MBA
⦿ بررسی اشتباهات رایج در مطالعه و راهکارهای مدیریت زمان
⦿ حل سؤالات منتخب و بررسی تکنیکهای تحلیل سؤال و حذف گزینه
⦿ تحلیل کارنامه و بررسی مسیر برنامهریزی درسی
فرقی نمیکنه تازه تصمیم به …
🛡 با گسترش هوش مصنوعی، روشهای قدیمی حفاظت از اطلاعات دیگه بهتنهایی کافی نیستن!
🔴 فرض کن یک شرکت از چند AI Agent برای انجام فعالیتهای روزمره استفاده میکنه. این ایجنتها به پایگاههای داده، فایلهای داخلی و سرویسهای مختلف دسترسی دارن و میتونن بعضی وظایف رو بدون دخالت مستقیم انسان انجام بدن. اما اگه یکی از اونها به اطلاعاتی دسترسی پیدا کنه که اصلاً برای انجام وظیفهاش ضروری نیست، چه اتفاقی میافته؟
🔴 در گزارشی …
⌛ چطور ساعت مطالعهمون رو بیشتر کنیم، بدون اینکه زود خسته بشیم؟
گاهی با وجود انگیزه زیاد، نمیتونیم بیشتر از چند ساعت درس بخونیم و هر بار که تصمیم میگیریم ساعت مطالعهمون رو افزایش بدیم، بعد از چند روز به برنامه قبلی برمیگردیم. اما راهحل فقط بیشتر درس خوندن نیست! افزایش تدریجی زمان مطالعه، مدیریت حواسپرتیها، تعیین هدفهای واقعبینانه و استراحتهای منظم میتونن کمک کنن هم ساعت مطالعه بیشتری داشته باشیم و هم کیفی…
✅ وبینار رایگان جبر خطی | درس جدید، چالش جدید
جبر خطی به کنکور ارشد کامپیوتر اضافه شده؛ چطور باید براش آماده بشیم؟
با اضافهشدن جبر خطی به کنکور ارشد کامپیوتر، خیلی از داوطلبها نمیدونن این درس چه مباحثی داره و چطور باید براش آماده بشن. توی این وبینار قراره با سرفصلهای مهم جبر خطی و بهترین مسیر مطالعه اون برای کنکور آشنا بشیم.
⚡️ رضا شکرزاد، مدرس کلاس جبرخطی کنکور ارشد کامپیوتر
📣 موضوعات اصلی وبینار:
📌 آشنایی …
✅✅ توضیحات رضا شکرزاد درباره رویداد حضوری MBA 360 | ویژه داوطلبان کنکور ۱۴۰۶
📚 توی این رویداد برای ریاضی چه برنامههایی داریم؟
⦿ بررسی روشهای مطالعه ریاضی و حل چند سؤال منتخب بهصورت حضوری
⦿ یادگیری کاربردی استفاده از هوش مصنوعی و چتباتها برای درک بهتر مفاهیم ریاضی
⦿ بررسی و تحلیل نمونه کارنامههای کنکور از نگاه رضا شکرزاد
⦿ گفتوگو و مشاوره درباره مسیر مطالعه و چالشهای آمادگی کنکور
📆 سهشنبه، ۱۹ آبان
⏰ ساعت ۱…
❤6👍3🔥3
Showing the 12 most recent of 191 posts we hold for @Cafetadris. 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 recorded as deleted after publishing
We recorded 1 post on @Cafetadris 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
20 August 2026
Most recent seen missing
20 August 2026
Median time before seen missing
13 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 63 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.
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.
برنامه ریزی رایگان مطالعه زبان ارشد و دکتری @GeneralEnglishPlan · 33,423 Telegram ranks this channel #11 of 90 here — alongside 89 others — read 5 September 2026
کنکور ارشد کامپیوتر @Konkurcomputer · 49,752 Telegram ranks this channel #11 of 88 here — alongside 87 others — read 25 August 2026
آموزش پایان نامه و مقاله نویسی پژوهه @pajoohehgroup · 59,296 Telegram ranks this channel #23 of 87 here — alongside 86 others — read 22 August 2026
روانشناسی|محمد وظیفه شناس @mohamadvzs · 32,436 Telegram ranks this channel #30 of 83 here — alongside 82 others — read 5 September 2026
منابع پروپوزال،مقاله،پایان نامه @PAPhd · 63,655 Telegram ranks this channel #34 of 76 here — alongside 75 others — read 21 August 2026
جزوه بازان | JozveBazan @jozve_bazan · 24,627 Telegram ranks this channel #37 of 83 here — alongside 82 others — read 15 September 2026
شبکه کارشناسی ارشد @mastertest · 49,524 Telegram ranks this channel #38 of 93 here — alongside 92 others — read 27 August 2026
ژورنال آکادمیک @journalacademic · 26,504 Telegram ranks this channel #42 of 78 here — alongside 77 others — read 12 September 2026
Englishturbo آموزش رایگان زبان با انگلیش توربو @englishturbo · 54,228 Telegram ranks this channel #42 of 75 here — alongside 74 others — read 24 August 2026
US @Yadbood_Ma · 25,765 Telegram ranks this channel #52 of 66 here — alongside 65 others — read 12 September 2026
اخبار دانشگاهی @akhbaredaneshgahi · 23,736 Telegram ranks this channel #57 of 90 here — alongside 89 others — read 16 September 2026
استخدام خراسان رضوی - مشهد @eestekhdam_khorasanerazavi · 29,675 Telegram ranks this channel #72 of 75 here — alongside 74 others — read 9 September 2026
استخدام بانک ها | ایران استخدام @iranestekhdam24_bank · 35,955 Telegram ranks this channel #72 of 81 here — alongside 80 others — read 2 September 2026
موسسه بین المللی علوم نوبنیاد @iins_ir · 36,154 Telegram ranks this channel #92 of 94 here — alongside 93 others — read 8 September 2026
This channel appears in 14 seed channels' Telegram-generated recommendation lists in total. 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“کافه تدریس | Cafetadris.com” (@Cafetadris), 12,560 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/Cafetadris.
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.