Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 90% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Growth
55 measurements spanning 91 days, net +2,570. 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”.
Measurement log — every subscribers count we have recorded, most recent 20 of 55
Measured (UTC)
Subscribers
Change
5 Nov 2026, 07:15
17,480
-24
4 Nov 2026, 03:26
17,504
-4
3 Nov 2026, 00:05
17,508
-9
1 Nov 2026, 22:57
17,517
-9
1 Nov 2026, 01:59
17,526
-8
31 Oct 2026, 03:50
17,534
-3
30 Oct 2026, 05:29
17,537
-30
29 Oct 2026, 02:41
17,567
-24
27 Oct 2026, 23:18
17,591
-18
26 Oct 2026, 22:35
17,609
-9
25 Oct 2026, 20:11
17,618
-28
24 Oct 2026, 18:11
17,646
-6
23 Oct 2026, 16:54
17,652
-33
22 Oct 2026, 14:45
17,685
-24
21 Oct 2026, 11:26
17,709
-12
20 Oct 2026, 08:44
17,721
-14
19 Oct 2026, 11:31
17,735
-13
18 Oct 2026, 11:27
17,748
-23
17 Oct 2026, 08:00
17,771
-11
16 Oct 2026, 11:14
17,782
first reading
Engagement
208 posts held, back to 2 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 59 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
5.71%
avg views ÷ 17,480 subscribers
Avg views / post
998
26 posts measured
Reaction rate
2.35%
reactions ÷ views · ER floor
Posts in window
26
of 208 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 25 of 26 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 4 November 2026
Posts held
208 (2 August 2026 – 4 November 2026)
Views total
25,955
Reactions total
597
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 05:07 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
Video runtime
2m 16s
Average length
19s
Measured directly from 7 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
5,731 reactions across 187 posts, in 19 distinct kinds. The most used accounts for 38.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
2,208
38.5%
👍
842
14.7%
😁
554
9.67%
🔥
477
8.32%
😭
442
7.71%
🤣
408
7.12%
🍓
250
4.36%
💔
172
3.00%
👏
139
2.43%
🥰
57
0.995%
🌚
55
0.96%
🕊
51
0.89%
🐳
22
0.384%
👎
22
0.384%
💘
16
0.279%
👀
8
0.14%
🤯
4
0.07%
🗿
3
0.052%
⚡
1
0.017%
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 196 of the 208 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 5,895 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 208 most recent posts we hold, published 2 August 2026 to 4 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 26 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
دریا تو چنلش خاصترین کتابها رو معرفی میکنه و میذاره!
daily dose of books🐈⬛️📚
🧛♀- کتاب کلاسیک خونآشامی کوییر
🧆- کتاب ژاپنی راجع به آدمخواری
🍽- یک منتقد غذا که دوستپسرهاش رو تبدیل به غذاهای لاکچری میکرد
🕰- زنی که توی سال ۱۸۵۵ بیدار شد
🪶- بازنویسی کوییر از داستان سقوط لوسیفر
#کتاب 📚
🌀 نام: مدهآ
🌀 نویسنده: اوریپید
این نمایشنامهی تراژیک اثر اوریپید از یونان باستان است و براساس اسطوره یاسون و مدهآ نوشته شده است.
مدهآ برای رسیدن به جیسون به پدر و برادر خودش خیانت کرده است، اما جیسون برای رسیدن به پادشاهی باید با زنی دیگر ازدواج کند، همین موضوع باعث انتقامی بزرگ میشود. نمایشنامه مدهآ داستان انتقام این زن است.
✏️ @benevis_s
اگه میخواید زبانتون خوب بشه، کتابهای زبان اصلی اینجا رو امتحان کنین:
daily dose of books🐈⬛️📚
دانلود کتابهای کلاسیک، وحشت، فانتزی، دارکرومنس و کوییر🩸🌚
📚|• هفت سوالی که قبل از کشتن شخصیت باید از خودت بپرسی:
💜۱. آیا مرگ این شخصیت تأثیر قابلتوجهی روی پیرنگ داستان میذاره یا فقط حالوهوای داستان رو تغییر میده؟ با حذف این شخصیت، چه چیزی در داستان از دست میره؟
💙۲. آیا نبودن این شخصیت میتونه بیشتر از مرگش به پیشبرد داستان کمک کنه؟
🩵۳. آیا داری این شخصیت رو میکشی چون نمیخوای تغییراتش تا انتها رو بنویسی؟ اگه زنده نگهش داری، ممکنه تغییر شخصیتش تا پایان تاثیرگذارتر ب…
من ساعت ۱۰:۴۷ شب: فقط میخوام یه خط از دیالوگ رو یه کوچولو اصلاح کنم.
۳:۱۲ صبح:
کل پردهی سوم رو از نو نوشتم.
شخصیت موردعلاقهم رو کشتم.
دچار بحران وجودی شدم.
#توییت📝
✏️ @benevis_s
چندتا سوال دربارهی کتابت✍
📖|• میتونی:
●این سوالها رو دربارهی داستان خودت از خودت بپرسی.
● این سوالها رو از کسی که قراره نوشتهش رو نقد کنی بپرسی.
۱۱. داستانت رو به زمان گذشته مینویسی یا حال؟
۱۲. کدوم رابطهی بین شخصیتهات رو بیشتر دوست داری؟
۱۳. از کدوم رابطهی بین شخصیتها کمتر خوشت میاد؟
۱۴. تا اینجای کار، صحنهی موردعلاقهات کدومه؟
۱۵. شخصیت محبوبت کیه؟
۱۶. مکانهای اصلی داستانت کجان؟
۱۷. یه حقیقت جالب در…
•[🌄]• پنج راه برای فضاسازی در داستاننویسی
🪶۵. روی زبان تمرکز کن
🎪|• فضاسازی فقط به توصیف کردن مربوط نمیشه. برای تکتک واژههایی که مینویسی، با دقت تصمیم بگیر تا حالوهوای داستانت رو بسازی.
🛕|• میخوای حس ناآرامی یا سردرگمی ایجاد کنی؟ با نحو جملهها بازی کن، طول جملهها رو تغییر بده، از واژههای نامعمولتر استفاده کن و گاهی جملههای ناقص به کار ببر.
🎨|• اما اگه میخوای خواننده احساس آرامش و شادی کنه، ساختارهای …
چون چرخ به کامِ یک خردمند نگشت
خواهی تو فلک هَفت شُمُر، خواهی هَشت
چون باید مُرد و آرزوها همه هِشت
چه مور خورَد به گور و چه گرگ به دشت!
👤| خیام
🕊| #شعر
✏️ @benevis_s
•[🌄]• پنج راه برای فضاسازی در داستاننویسی
🪶۴. تصویرسازیهات رو محدود کن.
🧊|• یه لحظه داری چیزی رو به سیب گندیده تشبیه میکنی؛ یه لحظه بعد سر از یک لولهی صنعتی درمیاری، بعد میرسی به هزارتو، حشره، پرتو نور خورشید، معبد، برنامههای تلویزیونی، کلاه سیلندری و... فکر کنم منظورم رو گرفتی!
🪽|• استفادهی بیقاعده و بیدلیل از استعارههای تصویری باعث میشه فضای داستان آشفته و ناهماهنگ به نظر برسه؛ درحالیکه بهتره فضایی م…
❤9👍3💘1
Showing the 12 most recent of 208 posts we hold for @benevis_s. 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.
Posts edited after publishing
@benevis_s edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
8 August 2026
Most recent edit
2 September 2026
Posts recorded as deleted after publishing
We recorded 26 posts on @benevis_s as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
7 August 2026
Most recent seen missing
5 November 2026
Median time before seen missing
34 hours
Seen missing in the last 30 days
2
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 10 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
نویسندگی @ErnestMillerHemingway · 31,288 Telegram ranks this channel #19 of 87 here — alongside 86 others — read 8 September 2026
⊰ Good Reads⛄ کتاب @CityOfBooks · 70,420 Telegram ranks this channel #38 of 76 here — alongside 75 others — read 20 August 2026
This channel appears in 2 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“بنویس :)” (@benevis_s), 17,480 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/benevis_s.
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.