9 measurements spanning 7 days, net -180. 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 57,117–57,351 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 21:08
57,144
-21
11 Aug 2026, 23:23
57,165
-35
11 Aug 2026, 00:22
57,200
-9
9 Aug 2026, 23:31
57,209
-30
8 Aug 2026, 23:01
57,239
-27
7 Aug 2026, 23:33
57,266
-44
6 Aug 2026, 23:15
57,310
-14
6 Aug 2026, 01:37
57,324
no change
5 Aug 2026, 22:22
57,324
first reading
Engagement
22 posts held, back to 30 May 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 18 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
2.41%
avg views ÷ 57,144 subscribers
Avg views / post
1,380
11 posts measured
Reaction rate
0.42%
reactions ÷ views · ER floor
Posts in window
11
of 22 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 10 of 11 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 12 August 2026
Posts held
22 (30 May 2026 – 12 August 2026)
Views total
15,154
Reactions total
60
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 07:53 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
593
Videos
529
Links
595
Lifetime counters from Telegram’s own channel header, read 13 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
6m 46s
Average length
1m 21s
Measured directly from 5 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
149 reactions across 20 posts, in 8 distinct kinds. The most used accounts for 60.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
90
60.4%
👍
27
18.1%
🙏
13
8.72%
🔥
7
4.70%
👌
5
3.36%
👏
5
3.36%
🎉
1
0.671%
😢
1
0.671%
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 21 of the 22 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 160reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 22 most recent posts we hold, published 30 May 2026 to 12 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.
📌شکایات متعددی مبنی بر عدم دسترسی به Google Flow و Gemini وجود دارد.
جهت بهرهگیری از خدمات هوش مصنوعی گوگل، استفاده از Soren VPN پیشنهاد میگردد. این سرویس برای دسترسی به پلتفرمهایی نظیر Gemini و Google Flow مناسب بوده و با اینترنت ایرانسل عملکرد بهینهای ارائه میدهد.
دانلود برای اندروید:
https://play.google.com/store/apps/details?id=com.provpn.soren
جهت مشاهده آموزشهای بیشتر کانال و صفحه ما را دنبال کنید.
#…
💥کارگاه آنلاین هوش مصنوعی پیشرفته در پژوهش یک قدم فراتر از استفاده معمولی از AI
اگر در پژوهش از هوش مصنوعی استفاده میکنید، احتمالاً با ابزارهای مختلف آشنا شدهاید
اما مرحله بعد این است که یاد بگیرید چطور حرفهایتر از AI برای انجام کارهای پژوهشی استفاده کنید.
در کارگاه هوش مصنوعی پیشرفته در پژوهش، در یک جلسه فشرده و عملی با این مباحث آشنا میشویم:
🔹 Claude در پژوهش
استفاده حرفهای از Claude برای کارهای پژوهشی، تحل…
50 ابزار هوش مصنوعی که در سال 2026، صدها ساعت از وقت شما را صرفهجویی میکنند. 🤯
1. Claude — حل هر مشکلی
2. Perplexity — تحقیق در مورد هر موضوع
3. PortfolioTab — ایجاد نمونهکار
4. Kling AI — ساخت ویدیوهای هوش مصنوعی
5. Tripo AI — ساخت مدلهای سهبعدی
6. Gemini — نگارش بینقص
7. CapCut — ویرایش ویدیو
8. The AI Library — کشف ابزارهای مفید هوش مصنوعی
9. YouLearn — خلاصهسازی ویدیوهای یوتیوب
10. Canva — طراحی گرافیک
11…
🎓 مگادوره جامع «تربیت پژوهشگر برتر»
📌 این مگادوره شما را از شرکت در دهها دوره پراکنده و گرانقیمت بینیاز میکند! چون تمام ابزارهای سنتی و مدرن (هوش مصنوعی) را یکجا به شما آموزش داده و شمارو تبدیل به یک پژوهشگر حرفه ای می کند.
✨ ویژگیهای منحصربهفرد این مگادوره:
⏱️ ۷۰ ساعت آموزش جامع و تخصصی (به صورت آفلاین و همیشگی)
📜 ارائه مدرک معتبر (معادل ۷۰ ساعت آموزش آکادمیک جهت تقویت رزومه)
🤖 آموزش کاملاً کاربردی و مجهز ب…
یک نفر گوشیش توی دفتر گم میشه و Find My هم بهخاطر محدودیت MDM کار نمیکرده.
رفته از Claude کمک گرفته؛
و اون هم بعد از یک دقیقه ابزاری طراحی کرده که قدرت سیگنال بلوتوث رو دنبال کنه و در آخر گوشی رو پیدا کرده.
Code:
https://github.com/ben-z/findphone
✨برای مشاهده آموزشهای بیشتر کانال و پیج ما را دنبال کنید.
#منابع_پارس_پژوهه
👁🗨 @tephd5
📌ابزارهای هوش مصنوعی (AI) به شما کمک میکنند تا تحقیقات را به سرعت بخوانید و مهمترین اطلاعات را استخراج کنید.
✅بهترین ابزارهایی که میتوانید از آنها استفاده کنید:
Elicit (http://elicit.org)🔹
چگونه به شما کمک میکند؟
- به طور هوشمندانه تحقیقات علمی را خلاصه میکند.
- مهمترین نکات (مشکل، نتایج، روشها) را به شما نشان میدهد، بدون اینکه نیاز به خواندن کل تحقیق داشته باشید.
- به شما کمک میکند تا تحقیقات مرتبط با مو…
📌 بهزودی GPT-6معرفی میشود
سم آلتمن قرار است این هفته پیشنمایشی از GPT-6 را ارائه کند.
بر اساس گزارشها، این مدل قابلیتهای قابلتوجهی خواهد داشت:
• توانایی انجام کشفیات علمی جدید
• حل خودکار یک مسئله ریاضی حلنشده ۸۰ ساله
• اجرای وظایف پیچیده برای مدت طولانی بدون نیاز به نظارت مداوم
• قابلیتهای پیشرفته در حوزه امنیت و سایبر
• تمرکز بر ارائه دانش و عملکرد بیشتر با هزینه کمتر، نه فقط کسب امتیاز بالاتر در بنچمارک…
ایجاد Skill در Claude
ایجاد یک Skill سفارشی در Claude تنها چند دقیقه طول میکشد. یک وظیفه مشخص تعریف کنید، مثالهای واقعی اضافه کنید و بگذارید هوش مصنوعی فرآیندهای تکراری را با نتایج پایدار خودکار کند. کلید موفقیت نه ابزار است، بلکه تبدیل دانش به سیستم.
✨برای مشاهده آموزشهای بیشتر کانال و پیج ما را دنبال کنید.
#منابع_پارس_پژوهه
👁🗨 @tephd5
✨🎓 دوست دارید مقالات ISI، اسکوپوس یا علمی-پژوهشی بنویسید و چاپ کنید ولی بلد نیستید؟
در این کارگاه فشرده، تمام مراحل نگارش و انتشار مقاله را از انتخاب عنوان تا چاپ نهایی در عرض فقط ۲ روز یاد میگیرید:
🔹 آموزش با دو رویکرد:
✔️ روش سنتی و استاندارد
✔️ روش نوین مبتنی بر هوش مصنوعی
👩🏫 مدرس:
دکتر عهدیه آقامحمدی
هیات علمی دانشگاه و داور مجلات معتبر علمی
⏰ زمان برگزاری:
📅 چهارشنبه ۷ مرداد | ۱۶ تا ۲۰
📅 پنجشنبه ۸مرداد …
📌ابزارهای عالی پژوهش:
1. http://Consensus.app
موتور جستجوی مبتنی بر هوش مصنوعی که پاسخها را مستقیماً از تحقیقات مورد تایید متخصصان پیدا میکند.
2. SciSpacec.com
ابزار بررسی متون علمی مبتنی بر هوش مصنوعی که مقالات و فایلهای PDF پیچیده را به صورت درونخط توضیح میدهد.
3. http://Elicit.com
دستیار تحقیق که بررسی متون علمی را خودکار کرده و ماتریسهای داده را استخراج میکند.
4. http://ResearchRabbit.ai
ابزار تجسم…
ترکیب بسیار جذاب gamma و claude جهت ایجاد فایلهای ارائه و پاورپوینت های عالی🌹
🎨 Gamma پاورهای جذاب میسازد، اما محتواهایش همیشه به قدرت Claude نیست.
🧠 Claude محتوای علمی، دقیق و عمیق تولید میکند، اما اگر پاورپوینت بسازد معمولاً به زیبایی Gamma نمیشود.
پس چرا از نقاط قوت هر دو استفاده نکنیم؟
✅ محتوا از Claude
✅ طراحی از Gamma
برای تست، کافی است یکی از این پرامپتها را به Claude بدهید:
🎓 «برای موضوع تأثیر رهبر…
❤9👍2🙏2🎉1👌1
Showing the 12 most recent of 22 posts we hold for @tephd5. 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 — 551,127 of 1,160,990entries 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 8 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.
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.
“آموزش کامل مقاله نويسی با هوش مصنوعی” (@tephd5), 57,144 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/tephd5.
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.