3 measurements spanning 8 days, net -2. 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 422–424 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 08:49
422
-2
6 Aug 2026, 19:30
424
no change
6 Aug 2026, 18:46
424
first reading
Engagement
8 posts held, back to 3 January 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
141.9%
avg views ÷ 422 subscribers
Avg views / post
599
3 posts measured
Reaction rate
3.29%
reactions ÷ views · ER floor
Posts in window
3
of 8 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 29 July 2026
Posts held
8 (3 January 2026 – 29 July 2026)
Views total
1,796
Reactions total
59
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 19:30 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
113 reactions across 8 posts, in 5 distinct kinds. The most used accounts for 53.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
60
53.1%
❤🔥
45
39.8%
🎉
4
3.54%
🥰
3
2.65%
😍
1
0.885%
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 8 of the 8 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 113reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 8 most recent posts we hold, published 3 January 2026 to 29 July 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.
کانون آرزوی سپید با هدف جمعآوری کاغذهای بدون استفاده، پویش «سقف کاغذی» را برگزار میکند.😍
اگر جزوه، دفتر، کتاب، برگههای امتحانی، کاغذهای باطله یا سایر اوراقی دارید که دیگر به آنها نیازی ندارید، آنها را دور نریزید و به ما تحویل دهید.🌱
♻️ کاغذهای جمعآوریشده بازیافت میشوند و هزینهی حاصل، برای امور خیریه و فعالیتهای محیطزیستی اختصاص خواهد یافت.
-با یک اقدام ساده، هم در کاهش پسماند کاغذ سهیم شوید و هم از یک …
من به دنبال یک شادمانی بیدلیل بودم،
که خداوند کودکان را در مسیر زندگی من قرار داد 👧😍👦
حضور اعضای کانون آوای مهر در بخش کودکان بیمارستان بهشتی
آوای مهر ، آوای مهربانی 🦋💖
https://t.me/Avayemehr_kaums
گاهی مهربانی، در سکوتِ یک نگاه و گرمای یک لبخند معنا میشود...
در هفتهای که گذشت، اعضای کانون آوای مهر و هلال احمر میهمان قلبهای کوچک اما بزرگی بودند که روزهایشان را در بخش کودکان بیمارستان میگذرانند.
کنارشان نشستیم، با آنها خندیدیم، بازی کردیم و برای دقایقی کوتاه، تلاش کردیم رنگی از امید و شادی را به قاب روزهایشان هدیه کنیم؛ چرا که باور داریم گاهی یک لبخند صادقانه، میتواند مرهمی باشد بر خستگیِ روزهای درمان🩷💖
…
📸جلسه هماهنگی فعالیتهای ماه آینده «آوای مهر» با حضور شورای مرکزی و اعضای فعال کانون برگزار شد.
اگر دوست دارید در کنار کسب تجربه، مهارتهای فردی و گروهی خود را تقویت کنید و در فضایی پویا و صمیمی فعالیت داشته باشید، منتظر حضور شما هستیم🤗
🔻برای عضویت و کسب اطلاعات بیشتر به آیدی زیر پیام بدید:
🆔 @Sajjad_hk18
🦋آوای مهر،آوای مهربانی🦋
«آوای مهر،برای لبخند کودکانه،کنار هم»
از شما دعوت میکنیم برای عیادت و ساختن لحظاتی شاد برای کودکان بستری در بخش اطفال بیمارستان بهشتی، کنارمون باشین
اون عروسکی که تو بچگی باهاش خاطره داری، میتونه بشه خاطرهی قشنگ بچگی یه نفر دیگه...🙃🧸
🔻شما عزیزان میتونید با اهدای موارد زیر در این کار نیک، ما رو همراهی کنید:
_عروسک و اسباب بازی
_کتاب داستان
_لوازم تحریر شامل دفتر نقاشی، دفتر رنگ آمیزی، مداد رنگی، خودکار رنگی، مداد …
انتخاب سجاد حکیمی به عنوان نماینده دبیران کانونهای فرهنگی و هنری دانشگاه علوم پزشکی کاشان
🔹پس از برگزاری انتخابات کانونهای فرهنگی و هنری دانشگاه، سجاد حکیمی، دبیر کانون آوای مهر، با کسب بیشترین آرا از میان دبیران کانونها، به عنوان نماینده دبیران کانونهای فرهنگی و هنری دانشگاه علوم پزشکی کاشان انتخاب گردید.
📌ادامه خبر :
http://www.mefda.ir/news/474285/
🏷 #مفدا_کاشان
کانال روابط عمومی معاونت فرهنگی و دانشجویی…
📢 فراخوان جذب اعضای فعال کانون آوای مهر
اگر انگیزه یادگیری، روحیه کار تیمی و علاقه به فعالیتهای فرهنگی، اجتماعی و داوطلبانه را دارید، این فرصت برای شماست.
کانون آوای مهر از تمامی دانشجویان علاقهمند دعوت میکند تا با پیوستن به جمع اعضای فعال، در برنامهریزی و اجرای فعالیتهای متنوع کانون نقشآفرین باشند.
زمینههای فعالیت:
* برگزاری برنامههای فرهنگی و اجتماعی
* تولید محتوای رسانهای و تبلیغاتی
* اجرای فعالیتهای…
به همت «آوای مهر»
و با یاری کانونهای نشاط ، فیلم و رسانه ،هلالاحمر و آرزوی سپید
✅آزادی ۹ زندانی جرایم غیر عمد مالی به دستان پرمهر شما اتفاق افتاد🕊🥹
✅در جشن «دورهمی دانشجویی» عواید حاصل از بازارچهی خیریه و مبالغ هدیه شده از سوی دانشجویان و اساتید وکارکنانجمع آوری و مبلغی حدود
«۳۰۰ میلیون تومان»💸
به حساب ستاد دیه واریز شد.
مسئولین محترم ستاد دیه و حمایت از زندانیان کاشان نیز، ضمن تقدیر از این اقدام موثر و خیرخواه…
❤🔥21
Showing the 8 most recent of 8 posts we hold for @Avayemehr_kaums. 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 — 199,675 of 1,549,376entries 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 4 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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“کانون نیکوکاری دانشجویی«آوایمهر»” (@Avayemehr_kaums), 422 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/Avayemehr_kaums.
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.
