3 measurements spanning 8 days, net -5. 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 429–436 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 16:13
430
-5
6 Aug 2026, 19:18
435
no change
6 Aug 2026, 08:50
435
first reading
Engagement
19 posts held, back to 20 February 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
45.3%
avg views ÷ 430 subscribers
Avg views / post
195
5 posts measured
Reaction rate
0.923%
reactions ÷ views · ER floor
Posts in window
5
of 19 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 4 August 2026
Posts held
19 (20 February 2026 – 4 August 2026)
Views total
975
Reactions total
9
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 19:18 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.
Reaction mix
60 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 73.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
44
73.3%
👏
5
8.33%
🔥
5
8.33%
👍
2
3.33%
😍
2
3.33%
🎃
1
1.67%
😁
1
1.67%
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 17 of the 19 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 60reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 20 February 2026 to 4 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.
💻 خفنترین آموزش امروز
کاری کن ChatGPT مثل یه انسان بنویسه، نه یه ربات!
✨ اگر زیاد با ChatGPT کار کرده باشی، حتماً متوجه شدی که متنهاش یه سری الگوهای تکراری دارن؛ مثلاً زیاد از عبارتهایی مثل «در نهایت»، «به طور کلی»، ساختارهای خیلی منظم، بولتپوینتهای همشکل و حتی یه نوع خاص از علائم نگارشی استفاده میکنه.
➕ همین الگوها باعث میشن خیلیها سریع بفهمن متن توسط هوش مصنوعی نوشته شده.
❔ خب پس چیکار کنیم که این اتفا…
دوستان عزیز فیلم کارگاه as review داخل سایت بارگذاری شد.
به شدت واسه دوستانی ک پژوهش میکنن پیشنهاد میشه 👌
جهت مشاهده 👉
غربالگری هوشمند مقالات با ابزار ASReview
🔹صرفهجویی هشتاد درصدی در زمان و انرژی در غربالگری مقالات در مطالعات مروری سیستماتیک
✅ ابزار مورد تایید ژورنالهای Nature، Lancet، BMJ و …
⏱ غربالگری مقالات بازیابیشده از جستجوی جامع دیتابیسها و منابع اطلاعاتی، یکی از وقتگیرترین مراحل مرورهای سیستمات…
⁉️🤯 هوش مصنوعی برات پوستر میسازه ولی متنهاش خرابه و نیاز به اصلاح داره؟!
🖥 اگه با ChatGPT عکس، پوستر یا کاور میسازی و مثل همیشه یه قسمت هایی از پوسترت رو خراب میکنه ، لازم نیست دوباره از اول طراحی کنی ؛ میتونی کل فایل رو قابل ویرایش وارد Canva کنی.
✔️ خب بریم سراغ آموزش :
1️⃣ وارد ChatGPT شو و از منوی سمت چپ Apps رو انتخاب کن و Canva رو فعال کن.
2️⃣ روی Canva بزن، با حسابت وارد شو و گزینه Allow رو انتخاب کن تا…
🔴هوش مصنوعی روز به روز داره به انسانها نزدیکتر میشه؛
آپدیت جدید قابلیتهای صوتی چت جیپیتی (GPT Live) از راه رسید و دیگه رسما داره شبیه آدميزاد حرف میزنه!
- دیگه لازم نیست صبر کنی حرفش تموم بشه؛ مثل آدم واقعی وسط مکالمه مکث میکنه و به حرفت گوش میده.
- موضوع صحبت رو بهتر یادش میمونه و لازم نیست هی از اول توضیح بدی.
- موقع سؤال درباره چیزهایی مثل فوتبال، بورس یا مسیر، اطلاعات رو با کارتهای گرافیکی روی صفحه ن…
تبدیل سریع ویس ب متن در تلگرام
خیلی خوبه امتحانش کنین :
@MediaTranscribeBot
فقط کافیه ویس رو برای ربات ارسال کنین.
نکته طلایی: اگر احیانا جاییش ایراد نگارشی داشت متن رو کپی کنید در باکس نوشتاری خودتون وارد کنید گزینه Ai تلگرام رو انتخاب کنید و متن رو fix کنید (تصویر رو ببین)
🔋🔋🔋🔋
💭 @MediraAcademy
📷Instagram.MEDIRA
🌐web site
🥰 گوگل تازه مدل Gemini Omni Flash رو معرفی کرده؛ یه مدل جدید برای تولید ویدیو و بهخصوص ویرایش ویدیو که کیفیت بالا رو در کنار هزینهای مقرون بهصرفه ارائه میده.
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⏺مطالعات قبلی کلی ثابت کردن که قهوه خوردن به سلامت کبد کمک میکنه. حالا یه مطالعه بزرگ دیگ انجام شده که از دیدگاه تصویر برداری و مولکولی هم به این موضوع پرداخته:
✅این مطالعه با پیگیری ۱۳ ساله انجام شده و نشون داده که هرچی قهوه بیشتر بخوری، خطر سیروز، سرطان کبد و مرگومیرهای کبدی کمتره. یعنی رابطه مستقیم داره: مصرف بیشتر قهوه، خطر کمتر بیماری. بیشترین اثر محافظتی هم وقتی دیده شده که روزی حداقل ۵ فنجان قهوه نوشیده بش…
✅آموزش کار با مایندمپ note booklm
با یک کلیک روی آیکون مربوطه توی پنل استودیو، محتوای منابع شما به صورت نمودار دستهبندی میشه (0:00 - 0:30). میتونید برای دیدن جزئیات زوم کنید (Zoom) و با درگ کردن صفحه جابجا بشید (0:35 - 0:47).
میتونید شاخهها رو باز (Expand) یا بسته (Collapse) کنید تا روی موضوعات اصلی تمرکز کنید یا جزئیات رو ببینید (0:56 - 1:13).
با کلیک روی هر گره Notebook به صورت خودکار درباره اون موضوع خاص جس…
🔘گاهی وقتا واسه ی متن رفرنس میخوای ولی نمیدونی از کجا میتونی رفرنس های معتبر و مرتبط در کمترین زمان ممکن پیدا کنی !
قراره ی ابزار خیلی مفید بهتون معرفی کنیم 🥰
🔋🔋🔋🔋🔋
💭@MediraAcademy
📷Instagram.MEDIRA
🌐web site
❤3🔥3😍2
Showing the 12 most recent of 19 posts we hold for @MediraAcademy. 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 — 94,601 of 1,478,351entries 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 16 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
1
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
1
vacant every time we have ever looked
@MediraAcademy named 1 handle 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.
@canva named in 1 post, 8 August 2026 – 8 August 2026
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“MEDIRA | مِدیرا” (@MediraAcademy), 430 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/MediraAcademy.
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.