ما به شما کمک میکنیم تا سریعتر زبان انگلیسی را بیاموزید,
ادمین شما @O2021
کانال های دوره های ما👇🏻👇🏻
@Friends_en
@Coding_Toefl
@Extra_en
@Joey_en
نظرات و نتایج 👈 @coding_comments
Created
Between 1 September 2015 and 31 December 2015— 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 why it has no browse page of its own yet.
Previous handles
Recorded in 2019 as “🎓 coding 504 🎓” — the title held for this same channel (matched by Telegram id, not by handle) in the Pushshift Telegram Dataset, a third-party archive captured in 2019-2020, years before this register made its own first observation. CC BY 4.0, Baumgartner, Zannettou, Squire & Blackburn (2020), Zenodo. A third party’s dated snapshot, not a measurement this register made itself.
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 3 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. None of the 39 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 7,667 comparable posts for this entry, running 6 October 2017 to 5 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 4, the earliest publisher we hold is @coding_504 — 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 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 3 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.
10 measurements spanning 10 days, net -128. 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 53,398–53,564 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Aug 2026, 17:05
53,417
-8
14 Aug 2026, 07:54
53,425
-19
13 Aug 2026, 01:34
53,444
-14
12 Aug 2026, 00:55
53,458
-8
11 Aug 2026, 00:41
53,466
-19
9 Aug 2026, 22:12
53,485
-16
8 Aug 2026, 19:50
53,501
-14
7 Aug 2026, 20:31
53,515
-11
6 Aug 2026, 19:10
53,526
-19
5 Aug 2026, 18:18
53,545
first reading
Engagement
17,451 posts held, back to 6 October 2017 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 943 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
1.68%
avg views ÷ 53,417 subscribers
Avg views / post
896
86 posts measured
Reaction rate
0.117%
reactions ÷ views · ER floor
Posts in window
87
of 17,451 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 86 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 15 August 2026
Posts held
17,451 (6 October 2017 – 15 August 2026)
Views total
77,054
Reactions total
4
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
16 Aug 2026, 14:39 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
≈5,350
Videos
≈2,970
Links
≈5,650
Lifetime counters from Telegram’s own channel header, read 16 August 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
18m 55s
Average length
1m 43s
Measured directly from 11 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.
🎼 Bang Bang 🎵
🎤 Dua Lipa 🎙
I was five, and he was six
من پنج ساله بودم و اون شیش سالش بود
We rode on horses made of sticks
ما اسبای چوبی مون رو میروندیم
He wore black, and I wore white
اون سیاه پوشیده بود و من سفید
He would always win the fight
اون همیشه دوئل مون رو میبرد
Bang bang
بنگ بنگ
He shot me down
بهم شلیک کرد
Bang bang
بنگ بنگ
I hit the ground
خوردم زمین
Bang bang
بنگ بنگ
That awful sound
صدای وحشتناکی بلند…
📺 هم اتاقی جدید چندلر
قسمت های کوتاهی از سریال محبوب فرندز با زیرنویس انگلیسی و فارسی
🇺🇸 A short movie . Listen to it
If you wanna improve your English
👈🏻 فوق العاده موثر برای تقویت مکالمه و لیسنینگ
برای تهیه ی مجموعه کامل سریال فرندز با دو زیرنویس انگلیسی و فارسی در فروش ویژه عدد 5 را یه ایدی زیر ارسال کنید👈🏻 🆔 T.me/O2021 @O2021
🇺🇸 Join @Friends_en
نظر مبین عزیز یکی از اعضای VIP سریالها دو زبانه
تخفیف ویژه تا ساعت ۲۴ فرداشب برای تهیه مجموعه کامل سریالها
تخفیف ۴۰ درصدی
۶۰۰ هزارتومان
فقط۳۰۰ هزارتومان
برای تهیه ی مجموعه کامل سریالها در فروش ویژه عدد 55 را به ایدی زیر ارسال کنید👈🏻 🆔 T.me/O2021
🔵 با سلام و عرض احترام
در کانالی که ایدی اون رو در انتهای این پست قرار دادیم داستان و روایت های آکسفورد از کتاب
Anecdotes in American English
By L. A. Hill
پست و تدریس شده است
🔰 ۳۰ درس اول مربوط به سطح یا لِوِل
Elementary 1000 Word Level
🔰۳۰ درس دوم به سطح
Intermediate 1500 Word Level
🔰 و دروس انتهایی برای دوره ی پیشرفته
Advanced 2075 Word Level
است.
🙏 امید که برای شما زبان آموزان مفید باشد، و انگیزه ی یادگیری …
🎉 کل سریال های ما را با تخفیف ویژه تهیه کنید
💎 مجموعه بی نظیر Friends
⚡️ ۱۰ فصل کامل ۲۳۶ قسمت
⚡️ دو زیرنویس انگلیسی و فارسی همزمان و تکی
⚡️ متن مکالمات هر قسمت بصورت pdf
💎 مجموعه How I Met Your Mother
⚡️۹ فصل کامل شامل ۲۰۸ قسمت
⚡️ دو زیرنویس انگلیسی و فارسی همزمان و تکی
💎 مجموعه Extra
⚡️۳۰ قسمت کامل با دو زیرنویس انگلیسی و فارسی
⚡️متن مکالمات تمام قسمتها بصورت pdf
⚡️کتاب کار و کتاب معلم بصورت pdf
💎 سریال Joey
⚡️د…
قسمت های کوتاهی از سریال محبوب فرندز با زیرنویس انگلیسی و فارسی
🇺🇸 A short movie . Listen to it
If you wanna improve your English
📺 وقتی فیبی عاشق مشتریش میشه 3⃣
👈🏻 فوق العاده موثر برای تقویت مکالمه و لیسنینگ
برای تهیه ی مجموعه کامل سریال فرندز با دو زیرنویس انگلیسی و فارسی در فروش ویژه عدد 5 را یه ایدی زیر ارسال کنید👈🏻 🆔 T.me/O2021
🇺🇸 Join @Friends_en
#conceal
پنهان کردن، مخفی کردن
کدینگ: قرارکاری که کنسل شد رو از بقیه پنهان کرد
➖➖➖➖➖➖➖➖➖
برای تهیه کل ۵۰۴ لغت به روش کدینگ عدد ۱ را به ادمین ثبتنام ارسال کنید👇👇😍
@O2021
Showing the 12 most recent of 17,451 posts we hold for @coding_504. 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.
Citation-graph rank
Citation-graph rank — 11,162 of 1,481,243entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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.
Handles this channel named that no longer answer
Dead references
15
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
15
vacant every time we have ever looked
@coding_504 named 15 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.
@yekta_504 named in 90 posts, 8 August 2026 – 8 August 2026
@how_i_met_your_mother_en named in 37 posts, 8 August 2026 – 8 August 2026
@how_i_met_your_mother_per named in 26 posts, 8 August 2026 – 8 August 2026
@coding_archive named in 15 posts, 8 August 2026 – 8 August 2026
@codind_504 named in 14 posts, 8 August 2026 – 8 August 2026
@yektaenglushclass named in 3 posts, 8 August 2026 – 8 August 2026
@en_coureses named in 3 posts, 8 August 2026 – 8 August 2026
@codin_toefl named in 3 posts, 8 August 2026 – 8 August 2026
@funnzaban named in 2 posts, 8 August 2026 – 8 August 2026
@hotgram_ir named in 1 post, 8 August 2026 – 8 August 2026
@coding_ielts named in 1 post, 8 August 2026 – 8 August 2026
@codg_504 named in 1 post, 8 August 2026 – 8 August 2026
@mono_ir named in 1 post, 8 August 2026 – 8 August 2026
@officialenglishtwitte named in 1 post, 8 August 2026 – 8 August 2026
@yekta504 named in 1 post, 8 August 2026 – 8 August 2026
Domains linked from posts
10 domainsthis 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 15 August 2026 — this
entry's latest reading, not the date you are reading this.
“کدینگ ۵۰۴ | سریال فرندز” (@coding_504), 53,417 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/coding_504.
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.