14 measurements spanning 14 days, net +2,839. 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 20,513–24,204 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
22 Aug 2026, 03:05
23,778
+96
20 Aug 2026, 16:36
23,682
+78
19 Aug 2026, 13:05
23,604
+118
18 Aug 2026, 16:33
23,486
+515
17 Aug 2026, 12:58
22,971
+73
16 Aug 2026, 01:44
22,898
+102
14 Aug 2026, 11:24
22,796
+276
13 Aug 2026, 05:47
22,520
+159
12 Aug 2026, 03:45
22,361
+141
11 Aug 2026, 01:44
22,220
+368
10 Aug 2026, 01:41
21,852
+507
9 Aug 2026, 02:51
21,345
+346
8 Aug 2026, 02:14
20,999
+60
7 Aug 2026, 19:46
20,939
first reading
Engagement
34 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 32 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
14.0%
avg views ÷ 23,778 subscribers
Avg views / post
3,340
34 posts measured
Reaction rate
0.407%
reactions ÷ views · ER floor
Posts in window
34
of 34 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 16 August 2026
Posts held
34 (5 August 2026 – 16 August 2026)
Views total
113,582
Reactions total
462
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
22 Aug 2026, 08:04 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
≈1,640
Videos
≈265
Links
≈434
Lifetime counters from Telegram’s own channel header, read 22 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
4m 33s
Average length
21s
Measured directly from 13 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
462 reactions across 34 posts, in 12 distinct kinds. The most used accounts for 57.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
265
57.4%
🔥
74
16.0%
👏
31
6.71%
👍
26
5.63%
🫡
24
5.19%
🥰
15
3.25%
😁
12
2.60%
💯
6
1.30%
🤯
4
0.866%
😍
3
0.649%
👌
1
0.216%
👎
1
0.216%
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 34 of the 34 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 462reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 34 most recent posts we hold, published 5 August 2026 to 16 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.
https://www.danidouen.ir/viralyai
سلام رفقا! 👋 برای امروز ۱۰ تا ظرفیت اقساط داریم برای شرکت داخل دوره جامع هوش مصنوعی 🤖 که این عزیزان ۳ ماه پشتیبانی (مستقیم) من رو هم خواهند داشت. فقط دقت کنید ۱۰ تا ظرفیت بیشتر نداریم ⚠️
در ۲ قسط با مبالغ:
2/950/000 تومان
قسط دوم با فاصله ۳۰ روز
شامل مثبت ۳۰ ساعت آموزش هوش مصنوعی ✅
مثبت ۱۶ میلیون تومان هدایا 🎁
سه ماه پشتیبانی مستقیم دنی 💬
اشتراک یک ماهه ابزار Viraly AI Pro 🚀
برای…
بچهها این ویدیوهای کاراکترهای عجیب غریبی که میبینید معمولا به همین روش ویدیوی بالا ساخته میشن 👆🤖
دیگه دوران کلیپهای شانسی تموم شده.
الان با ترکیب APOB AI و Seedance 2.5 میشه ولاگهای ۳۰ ثانیهای با یه شخصیت ثابت و طبیعی ساخت 🚀
دیگه نیازی نیست برای یه خروجی خوب هی پرامپت عوض کنی و منتظر شانس بمونی.
🤖 راه ارتباط مستقیم با من 👈 @danidouen_bot
سه تا آدمی که تو این ویدیوی بالا ورزش میکنن هیچکدوم واقعی نیستن 👆
این همون بازآفرینی سبک جدید تولید محتوای وایرال با هوش مصنوعیه 🤯
یه ویدیوی وایرال باشگاه رو برداشته و فریم به فریم با همون حرکت برای سه نفر تو کشورهای مختلف کلون کرده.
با ابزار seedance 2.5 و فقط یه پرامپت میتونی هر ویدیویی رو اینجوری موبهمو بازسازی کنی 🤖
🤖 راه ارتباط مستقیم با من 👈 @danidouen_bot
راستی، ابزار هوش مصنوعی Google Flow روزانه ۵۰ کردیت رایگان بهت میده و میتونی باهاش عکسهات رو با Veo 3.1 به ویدئو تبدیل کنی 🎬
کافیه با یه حساب Gmail وارد بشی و برای مصرف کمتر، مدل Veo 3.1 Lite رو انتخاب کنی.
سایت رسمی گوگل فلو 👇
https://labs.google/fx/tools/flow
قضیه اسپاگتی خوردن Will Smith که یه زمانی سم خالص هوش مصنوعی بود رو یادتونه؟ 🍝
این خروجی وحشتناک بالا با Flux 3 ساخته شده 👆
کار تیم bfl_ai هست و قشنگ نشون میده تو همین زمان کوتاه چقدر پیشرفت کردیم 🤖
🤖 راه ارتباط مستقیم با من 👈 @danidouen_bot
اگه کیفیت برات خیلی مهمه و محدودیت بودجه نداری، مدلت رو Seedance 2.5 انتخاب کن ✨
رو دستش در حال حاضر وجود نداره 🚀
با ریاکشن بگو خروجی کار چطور شده؟ 🤔
🤖 راه ارتباط مستقیم با من 👈 @danidouen_bot
یه ایده جذاب واسه چنلهای YouTube اینه که بری سراغ داستانهای معروفی مثه خرگوش و لاکپشت 🐢
خروجیش که با seedance ساخته شده رو تو همین ویدیوی بالا میتونی ببینی 👆
کافیه با AI براش تصویر بسازی، صدا روش بذاری و ادیتش کنی تا یه ویدیوی خفن واسه آپلود داشته باشی 🤖
فقط حتما قبلش قوانین مانیتایز یوتیوب رو برای هوش مصنوعی بخون که خیالت راحت بشه؛ زنده کردن این قصههای قدیمی با ابزارهای جدید یه میانبر سریع برای رسیدن به درآ…
🚀 ۱۷ کانال یوتیوب که واقعا AI یادت میدن
اگه نمیخوای بین هزاران ویدیوی تکراری بچرخی، این لیست رو سیو کن. از آموزش ساده و کاربردی تا اتوماسیون، کسبوکار و عمق فنی؛ برای هر هدفی یه گزینه خوب اینجاست 👇
💼 کسبوکار و آژانس
۱) Sabrina Ramonov — کسبوکار یکنفره و درآمدزایی با AI
۲) Ben AI — اتوماسیون واقعی و رشد آژانس
۳) Liam Ottley — ساخت و فروش AI Agent
۴) Dan Martell — سیستمسازی و رشد بدون حجم کار بیشتر
۵) Nick Sara…
اینم خروجی ویدیوشه
فارسی صحبت کردنش مثل veo خنگه
ولی خب ویدئوشو من بدم نیومد
🥰7❤2😁2
Showing the 12 most recent of 34 posts we hold for @dani_douen. 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 — 815,387 of 1,583,249entries 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 1 registered channel — 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.
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 22 August 2026 — this
entry's latest reading, not the date you are reading this.
“دنی دوئن| کلاب ترمیناتور های هوش مصنوعی” (@dani_douen), 23,778 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/dani_douen.
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.