4 measurements spanning 7 days, net -8. 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 1,620–1,631 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 23:27
1,621
-5
10 Aug 2026, 09:38
1,626
-4
7 Aug 2026, 10:14
1,630
+1
6 Aug 2026, 14:22
1,629
first reading
Engagement
12 posts held, back to 11 July 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 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
20.5%
avg views ÷ 1,621 subscribers
Avg views / post
332
4 posts measured
Reaction rate
1.13%
reactions ÷ views · ER floor
Posts in window
4
of 12 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 5 August 2026
Posts held
12 (11 July 2026 – 5 August 2026)
Views total
1,329
Reactions total
15
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 17:54 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
59s
Average length
59s
Measured directly from 1 video 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
38 reactions across 11 posts, in 3 distinct kinds. The most used accounts for 84.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
32
84.2%
👍
4
10.5%
❤🔥
2
5.26%
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 11 of the 12 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 38reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 12 most recent posts we hold, published 11 July 2026 to 5 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.
🔸 مهارت داری، تلاش میکنی، اما هنوز فرصت شغلی مناسب پیدا نکردی؟
خیلیها در شروع مسیر کاری فکر میکنند فقط با یادگیری مهارت و ارسال رزومه میتوانند وارد بازار کار شوند؛ اما واقعیت این است که بخش زیادی از فرصتها از طریق ارتباطات حرفهای شکل میگیرد.
شبکهسازی یعنی یاد بگیری چطور ارتباط درست بسازی، خودت را معرفی کنی و در مسیر شغلی دیده شوی.
🖋اگر نمیدانی از کجا شروع کنی، در مقاله جدید وبلاگ درباره اصول شبکهسازی حرف…
🟠 مردم همیشه چیزی را که میگویند، نمیخرند!
در مارکتینگ به این پدیده Say-Do Gap (شکاف حرف تا عمل) می گویند.
اگر بپرسید: «محصول سالم و رژیمی میخواهید؟» همه میگویند: «بله!»
اما پای قفسه فروشگاه، آمار فروش چیز دیگری میگوید.
شما هم همینطورید؟!
برامون از تجربه خودتون تو خرید بنویسید
🟠 آکادمی اینترجاب
🆔 @enterjob_academy
🌐 https://enterjob.academy
دونستن میکروبیولوژی ضروریه؛ اما برای ورود به بازار کار کافی نیست.
🔴 امروز شرکتها به دنبال افرادی هستن که علاوه بر دانش تخصصی، بتونن دادهها رو تحلیل کنن، گزارشهای حرفهای بنویسن، با اکسل کار کنن و برای مسائل واقعی کارخانه راهحل ارائه بدن.
✅ اگه این مهارتهای کاربردی رو یاد بگیری، تو مصاحبههای شغلی یک قدم از بسیاری از فارغالتحصیلا جلوتری؛ چون کارفرما به دنبال کسیه که از روز اول بتونه ارزش خلق کنه، نه فقط مدرک ا…
پشت صحنه موفقیت بزرگترین برندهای صنعت غذا چیه؟ 🤔
توی دانشگاه یا کتابهای
تئوری، کسی از چالشهای واقعی مدیریت و ترفندهای استخدام صحبت نمیکنه. برای همین، ما در آکادمی اینترجاب صندلی گفتگو رو روبهروی مدیران ارشد و چهرههای سرشناس صنعت غذا گذاشتیم تا بیپرده از تجربهها، شکستها و رازهای رشدشون بگن.
اگر میخواهید جلوتر از بقیه حرکت کنید و نبض بازار کار دستتون باشه، تماشای این گفتگوها یک میانبرِ طلایی برای شماست.
📺 ه…
کنکور یک آزمون است، نه پایانِ مسیر.
🔴 امروز و فردا که برای کنکور میجنگید، یک حقیقت را فراموش نکنید:
«عددها و رتبهها، هیچگاه ارزشِ وجودی شما را تعریف نمیکنند.»
دانشگاه یک شروع است، اما «همهچیز» نیست.
دنیای واقعی، کار و صنعت، فراتر از مدرک، تشنهی «مهارت» است.
تواناییِ حل مسئله، هوش هیجانی، ارتباطاتِ مؤثر و یادگیریِ مداوم؛ اینها همان ابزارهایی هستند که شما را در بازار کار متمایز میکنند.
فارغ از نتیجهی کنکو…
گاهی رد کردنِ محصول، از قبول کردنش اشتباهتره.
🔴 توی خط تولید، رد کردن همیشه نشونه دقت نیست.
بعضی وقتها مشکل از فراینده، نه خودِ محصول.
✅ کیفیت یعنی قبل از رد کردن، یک سؤال بپرسیم:
«مشکل واقعاً از کجاست؟»
🟠 آکادمی اینترجاب
🆔 @enterjob_academy
🌐 https://enterjob.academy
🎖و سرانجام در آخرین سری از ماجرای برندگان، به معرفی و بررسی عملکرد گروههای منتخب سومین چالش پرداختیم.
🔴 رویکرد هر کدام از این گروهها حاوی نقاط قوتی است که آنها را با شما به اشتراک میگذاریم.
🟠 آکادمی اینترجاب
🆔 @enterjob_academy
🌐 https://enterjob.academy
🎙 رمز موفقیت چیه؟
سوال مهمی که شاید ذهن خیلی از ماها رو درگیر خودش کنه اما براش جواب مشخصی نداشته باشیم.
در اولین قسمت از گفتگوی ما با جناب محسن جلال پور، ایشون با نگاهی به سالها تجربه در عرصه تجارت، جواب جذابی به این سوال مهم دادن.
🟠 آکادمی اینترجاب
🆔 @enterjob_academy
🌐 https://enterjob.academy
بعضی سوالها از بعضی جوابها ارزشمندترند.
توی عصر هوش مصنوعی، جوابها همهجا هستن؛ اما اونی برنده میشه که بلده «سوال درست» بپرسه. این یعنی تفکر نقادانه و حل مسئله.
🔴 ولی کفِ کارخانه یه واقعیت دیگه هم داره:
هوش مصنوعی شاید فرمولها رو بده، اما نمیتونه جای ارتباط با تیم و تصمیمگیری در لحظه رو بگیره. ابزارها کار رو جلو میبرن، ولی مهارتهای نرم تو رو متمایز میکنه.
✅ یاد بگیریم چطور درست سوال بپرسیم؛ چه از ماشین،…
سه نکته طلایی وبینار از ایده تا محصول🎖
برای ورود موفق به بازار کار، فقط مدرک کافی نیست.
مهارت عملی یاد بگیر، از زاویه بازار به ایدهها نگاه کن و شبکهسازی را جدی بگیر.
مسیر حرفهای از یادگیری، شناخت بازار و ارتباطات درست ساخته میشود.
🟠 آکادمی اینترجاب
🆔 @enterjob_academy
🌐 https://enterjob.academy
سلام به همهی اینترجابیها،
امیدواریم حالتون خوب باشه🌱
گواهی شرکت در وبینارهای زیر
✅ از ایده تا محصول در بازار: R&D صنعتی، فرمولاسیون، پایدارسازی و هزینه
✅ تخمیر ضایعات کشاورزی و غذایی: از پسماند تا محصول با ارزش افزوده
صادر شده و روی سایت آکادمی قرار گرفته؛
از طریق آدرس زیر میتونید مشاهده و دانلودش کنید!🧡
📌آدرس سایت:
🆔: https://enterjob.academy
(سایت آکادمی اینترجاب > پنل کاربری > دورههای من > عنوان دوره > درخ…
❤🔥2❤1
Showing the 12 most recent of 12 posts we hold for @Enterjob_academy. 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 — 361,119 of 1,481,243entries 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 11 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“آکادمی اینترجاب” (@Enterjob_academy), 1,621 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/Enterjob_academy.
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.