2 measurements taken within a single day. 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 179–181 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
7 Aug 2026, 08:18
180
no change
6 Aug 2026, 23:55
180
first reading
Engagement
20 posts held, back to 10 October 2025 — 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
15.8%
avg views ÷ 180 subscribers
Avg views / post
28.5
2 posts measured
Reaction rate
19.3%
reactions ÷ views · ER floor
Posts in window
2
of 20 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 30 July 2026
Posts held
20 (10 October 2025 – 30 July 2026)
Views total
57
Reactions total
11
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 08:18 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.
What this channel posts
Photos
192
Videos
30
Links
91
Lifetime counters from Telegram’s own channel header, read 7 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.
Reaction mix
117 reactions across 20 posts, in 6 distinct kinds. The most used accounts for 55.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
65
55.6%
👏
18
15.4%
😢
18
15.4%
👍
9
7.69%
🕊
6
5.13%
🤔
1
0.855%
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 20 of the 20 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 117reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 10 October 2025 to 30 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.
غم مثل یک بچهگربه بر روی قالی نشسته
یا مثل دیوانه بر خاک با بیخیالی نشسته
غم مثل رنگ گیاه است، روییده در سرزمینم
مانند یک لکّه بر پوست، حالی به حالی نشسته
گاهی گل زعفران است، گاهی حنا، نقش دستی
گاهی صدای خوشی در بزم قوالی نشسته
گه طعنهای تلخ و سنگین روی زبان رفیقی
گاهی چو بوی خوش یاس در بین شالی نشسته
گه مردمی بیزبان، غم؛ در چشمهایم، نهان، غم
گه با سپاهی خیالی در شهرِ خالی نشسته
غم، گاه فقر و فنایم، در کن…
نسخهٔ اصلی این آهنگ را اولین بار در فیلم In the Mood for Love (در حالوهوای عشق) با صدای Nat King Cole شنیدم. این نسخهٔ بازخوانی شده نیز امشب به مذاقم خوش آمد.
Siempre que te pregunto / Qué cuándo, cómo y dónde
هر وقت از تو میپرسم: کی، چطور و کجا؟
Tú siempre me respondes / Quizás, quizás, quizás
تو همیشه به من جواب میدهی: شاید، شاید، شاید
Y así pasan los días / Y yo, desesperando
و روزها اینطور میگذرند و من نا…
#آوازـوـآوار پیشکشیِ #بیداد_موریانهها به شاعران زن افغانستان است. باشد که جهان جایی برای مهرورزی و دوستی شود و سکونتگاه صلح.
بیداد موریانهها (ویژهی شعر زن):
@bidaademooriyanehaa
«انتظار»
مرثیهای برای گمشدگانِ جنگ
چهرهام را به خاطر بیاور
صورتم را به یاد ندارم
مدتهاست
خودم را به طبیعت سپردهام
درست از روزی
که لبهایم عزرائیل را دیوانه کرد.
منتظر بودم بیابی مرا
بیرونم بکشی از دندان شغالهای گرسنه
از متن خبرها
از دوربین عکاسها
از موتورهای جستوجو در اینترنت
از بندبند شاعران غمگین.
مدتهاست
علفها کنارم قد کشیدهاند
برگهای جوان پهنتر شدهاند
و پرندگان مغزم را با جفتها و جوجهها تقسیم …
بعد از جنگ
با چوبدستم
انجیرهای تازه را برای تو خواهم چید
با تو خواهم ماند
با تو خواهم خواند
و تو را در بهت آفتابیات خواهم بوسید
اگر ابرها بگذارند!
محمدابراهیم جعفری
@zahediz
آن سوی شیشه تو را دیدن
از پشت سیمها صدایت را شنیدن
بر زخمهای تو آواز خواندن...
بین من و تو
دیوار بلندِ «قانون» است
و خندههایت موی سپید تو را پنهان نمیکند
و خندههایت استخوان گونهات را پر نمیکند
گفتی برای پسرت دلتنگی
و چشمهایت مثل رودخانه بی ماهی بود.
زمان، کلمات را کوتاه کرده بود
و لبخند سختتر از همیشه بود
در اتاق ملاقات.
از آنجا که تویی
دلتنگیات را بلند میشنوم در قلبم
صدایی که با تو قدم میزند
لبی که…
دو غزل از شاعران کهن فارسی بخوانید با مضمون، وزن یکسان، قافیه و ردیف مشابه. شعر اول از خاقانی شَروانی(شاعر قرن ۶) و شعر دوم از عطار نیشابوری(شاعر قرن ۶ و ۷) است.
تشابه مضمون، انتخاب قافیه و ردیف و حتی اوزان مشترک در بسیاری از سرودههای شاعران دورههای مختلف دیده میشود. برای مثال، فخرالدین عراقی شاعر قرن ۷ نیز، غزلی با این مطلع دارد:
«ای به تو زنده جسم و جان، مونس جان کیستی؟
شیفتهٔ تو انس و جان، انس روان کیستی؟»
…
پایبند این بنای رو به ویرانی مباش
اینقدر وابستهٔ این وادی فانی مباش
ماهی دریایی و جای تو در این تنگ نیست
فکر جایی که در آن دائم نمیمانی مباش
این جهان هرچند زندان است اما ای رفیق
میله را از ذهن خود بردار زندانی مباش
«لَیسَ لِلإنسانِ الّا ما سَعیٰ» یعنی بدان
در تمام عمر خود دنبال آسانی مباش
عشق را در پینههای دست مردم دیدهایم
در پی آن پینههای روی پیشانی مباش
دست گرم مرگ میآید تکانت میدهد
وقت بیداریست در خ…
در محضر لسانالغیب حافظ شیرازی
میرِ من خوش میروی کاندر سر و پا میرمت
خوش خرامان شو که پیش قد رعنا میرمت
گفته بودی کی بمیری پیش من، تعجیل چیست؟
خوش تقاضا میکنی پیش تقاضا میرمت
عاشق و مخمور و مهجورم بتِ ساقی کجاست؟
گو که بِخرامَد که پیشِ سرو بالا میرمت
آن که عمری شد که تا بیمارم از سودای او
گو نگاهی کن که پیشِ چشمِ شهلا میرمت
گفتهای لعلِ لبم هم درد بخشد هم دوا
گاه پیش درد و گَه پیش مداوا میرمت
خوش خرامان میرو…
❤7👏1
Showing the 12 most recent of 20 posts we hold for @zahediz. 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.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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
Names
Channels on the register whose handles appear in this channel's posts.
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 7 August 2026 — this
entry's latest reading, not the date you are reading this.
“گاهنوشت” (@zahediz), 180 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/zahediz.
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.