🧿|• نوشتن خرافات: یک خرافهی جدید بساز! 🐦⬛️|• یک خرافه اختراع کن که در دنیای داستانت عادیه. 🍀|• بدون اینکه مستقیم توضیح بدی چه معنایی داره، توی یک صحنه نشونش بده. 🐈⬛️|• خواننده باید خودش از رفتار مردم معناش رو کشف کنه. ✏️ @benevis_s
👍8🔥2

Channel
@benevis_s
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry
17,987subscribers
+3,077 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001293958477 |
|---|---|
| Type | Channel |
| Username | @benevis_s |
| Created | 16 February 2019 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 9 September 2026 |
| Measurements held | 25 |
| Confirmed unchanged | 1 time, most recently 9 September 2026 |
| On Telegram | t.me/benevis_s |
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 why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Sept 2026, 15:16 | 17,987 | +821 |
| 6 Sept 2026, 06:01 | 17,166 | +256 |
| 4 Sept 2026, 03:20 | 16,910 | -30 |
| 2 Sept 2026, 20:26 | 16,940 | -27 |
| 1 Sept 2026, 18:14 | 16,967 | +28 |
| 31 Aug 2026, 18:54 | 16,939 | -12 |
| 30 Aug 2026, 21:54 | 16,951 | -23 |
| 29 Aug 2026, 23:16 | 16,974 | -39 |
| 28 Aug 2026, 19:44 | 17,013 | -45 |
| 27 Aug 2026, 17:47 | 17,058 | -39 |
| 26 Aug 2026, 20:25 | 17,097 | +152 |
| 25 Aug 2026, 20:15 | 16,945 | +240 |
| 24 Aug 2026, 21:42 | 16,705 | -57 |
| 23 Aug 2026, 04:06 | 16,762 | -55 |
| 21 Aug 2026, 13:36 | 16,817 | -12 |
| 20 Aug 2026, 12:23 | 16,829 | -12 |
| 19 Aug 2026, 13:53 | 16,841 | -22 |
| 18 Aug 2026, 16:55 | 16,863 | -23 |
| 17 Aug 2026, 14:37 | 16,886 | -37 |
| 16 Aug 2026, 06:37 | 16,923 | first reading |
182 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 53 pages of Telegram’s post history, 20 posts per page.
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 130 of 139 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 September 2026 |
|---|---|
| Posts held | 182 (2 August 2026 – 3 September 2026) |
| Views total | 153,110 |
| Reactions total | 3,942 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 09:32 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.
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.
5,134 reactions across 162 posts, in 19 distinct kinds. The most used accounts for 39.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2,003 | 39.0% | |
| 👍 | 766 | 14.9% | |
| 😁 | 554 | 10.8% | |
| 🔥 | 443 | 8.63% | |
| 😭 | 383 | 7.46% | |
| 🤣 | 251 | 4.89% | |
| 🍓 | 233 | 4.54% | |
| 💔 | 170 | 3.31% | |
| 👏 | 115 | 2.24% | |
| 🥰 | 57 | 1.11% | |
| 🕊 | 49 | 0.954% | |
| 🌚 | 46 | 0.896% | |
| 🐳 | 22 | 0.429% | |
| 👎 | 22 | 0.429% | |
| 👀 | 8 | 0.156% | |
| 💘 | 4 | 0.078% | |
| 🤯 | 4 | 0.078% | |
| 🗿 | 3 | 0.058% | |
| ⚡ | 1 | 0.019% |
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 171 of the 182 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 5,298 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 182 most recent posts we hold, published 2 August 2026 to 3 September 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.
🧿|• نوشتن خرافات: یک خرافهی جدید بساز! 🐦⬛️|• یک خرافه اختراع کن که در دنیای داستانت عادیه. 🍀|• بدون اینکه مستقیم توضیح بدی چه معنایی داره، توی یک صحنه نشونش بده. 🐈⬛️|• خواننده باید خودش از رفتار مردم معناش رو کشف کنه. ✏️ @benevis_s
👍8🔥2
🎭 دورهی آموزشی شخصیتپردازی در داستان شخصیتهایی بسازید که فقط حضور نداشته باشند. بخواهند، دست به انتخاب بزنند، اشتباه کنند و تغییر بپذیرند. ✦ خواسته، نیاز و انگیزه ✦ نقاط قوت، ضعف و تناقض ✦ گذشته و تاثیر آن بر شخصیت ✦ ترس، امید و دلبستگی ✦ روابط و تعارضها ✦ شخصیتپردازی با رفتار و دیالوگ ✦ صدای منحصربفرد شخصیت ✦ طراحی قوس شخصیت 👥 ظرفیت: ۱۰ نفر 💰 ده جلسه هزینه شرکت: ۸۰۰ هزار تومان در صورت تمایل به شرکت به آیدی @Ash…
❤11👎6
❌نویسندگی ضعیف: شخصیتها از اول تا آخر همون آدمی میمونن که بودن. نه تغییری میکنن، نه چیزی به چالششون میکشه. در نتیجه هم زود فراموش میشن. ✅نویسندگی خوب: شخصیتها در طول داستان تغییر میکنن. هم اتفاقهای بیرونی و هم کشمکشهای درونی روشون اثر میذاره و داستان از نظر احساسی تأثیرگذارتر میشه. ❌نویسندگی ضعیف: دیالوگها فقط برای پُر کردن صفحهان؛ چیزهایی رو تکرار میکنن که خواننده از قبل میدونه یا هیچ کمکی به جلو رفت…
❤20👍4🍓1
تفاوتهای نویسندگی ضعیف و نویسندگی خوب✍ بخش سوم و پایانی در پست پایین👇 ✏️ @benevis_s
❤9🍓2
#میم📝 من به فامیلی که ۳۰ سال ازم بزرگتره: ببین مناسب سنت نیست. ✏️ @benevis_s
🤣66❤3🍓1
🖌|• سوزان سانتاگ: 🖌|• «به نظرم، نویسنده کسیه که به دنیا با دقت توجه میکنه.» ✏️ @benevis_s
🍓25👍8❤5
🛖|• اگه داستان تاریخی مینویسی: ⛵️|• تاریخ فقط دکور داستانته یا واقعاً اهمیت داره؟ 🪝|• اگر داستانت در سال ۱۲۹۰ اتفاق میافته ولی دقیقاً همانطور میتونستی توی سال ۱۴۰۵ تعریفش کنی، احتمالاً تاریخ فقط دکور داستانته. 🪝|• از خودت بپرس: ● اگر این داستان در زمان دیگهای اتفاق میافتاد، چه چیزی متفاوت میشد؟ 🪝|• اگر جواب این بود که «هیچچیز» یا فقط «لباس شخصیتها فرق میکرد»، هنوز از پتانسیل داستان تاریخی استفاده نکردی. …
❤23🔥3🍓2
#کتاب 📚 🌀 نام: زمین سوخته 🌀 نویسنده: احمد محمود این کتاب روایت تکاندهندهی احمد محمود از سه ماه ابتدای جنگ ایران و عراق و تأثیر آن بر زندگی مردم عادی در شهر اهواز. فصل اول آن در شهریور 1359 ورق میخورد و فصل پایانی آن در آذر ماه همان سال بسته میشود. اما بین این دو بازهی زمانی کوتاه، به اندازهی فرسخها زمین سوخته، دهها شهر بمباران شده و هزاران انسان جنگزده قصه برای گفتن هست؛ راوی داستان، بارِ روایت یکی از این م…
❤15
❌نویسندگی ضعیف: کشمکشهای بیرونی داستان اونقدر کلیان که فرقی نمیکنه برای کدوم شخصیت اتفاق بیفتن. ✅نویسندگی خوب: درگیریها دقیقاً طوری طراحی شدن که باورهای اشتباه، ترسها یا ضعفهای درونی همون شخصیت رو به چالش بکشن. ❌نویسندگی ضعیف: پر از توضیح اضافه، تکرار، کلمههای بیدلیل یا دیالوگهاییه که فقط یه چیز رو دوباره تکرار میکنن. ✅نویسندگی خوب: هر کلمه با فکر انتخاب شده و فقط چیزهایی توی متن میمونن که به تصویرسازی ی…
❤28🍓2👍2
تفاوتهای نویسندگی ضعیف و نویسندگی خوب✍ بخش دوم در پست پایین👇 ✏️ @benevis_s
❤14
📜 ری کراک میگوید: هیچچیز در دنیا نیست که جای پشتکار را بگیرد. نه استعداد؛ که هیچ چیز عادیتر از افراد ناموفق با استعداد نیست. نه نبوغ، که نابغههای ناکام ضربالمثلاند. نه تحصیلات؛ که دنیا پر است از بیخانمانهای تحصیلکرده. تنها پشتکار و اراده است که قدرقدرتاند. ✏️ @benevis_s
👍19👏7🍓3❤2
💠مقاله «چطور قوس رستگاری بنویسیم؟»💠 ✔️ قوس شخصیت یعنی روند تغییر شخصیت از اول تا آخر داستان. ✔️ یک مدل تغییر، تغییر از یک آدم بد به یک آدم خوب و توبهکردهست. قبلاً در این پست مختصر درباره قوس شخصیتی رستگاری (Redemption Arc) حرف زدیم. ✔️ در این فایل کاملتر دربارهش بخونین و یاد بگیرین که چطور بهتر بنویسینش! ✏️ @benevis_s
❤15
Showing the 12 most recent of 182 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.
@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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
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.
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.
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.
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 9 September 2026 — this entry's latest reading, not the date you are reading this.
“بنویس :)” (@benevis_s), 17,987 subscribers as measured 9 September 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.