3 measurements spanning 6 days, net -3. 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 753–756 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 04:31
753
-3
6 Aug 2026, 15:52
756
no change
5 Aug 2026, 22:06
756
first reading
Engagement
20 posts held, back to 6 September 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
19.9%
avg views ÷ 753 subscribers
Avg views / post
150
1 post measured
Reaction rate
0.667%
reactions ÷ views · ER floor
Posts in window
1
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 28 July 2026
Posts held
20 (6 September 2025 – 28 July 2026)
Views total
150
Reactions total
1
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 15:52 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
9 reactions across 6 posts, in 2 distinct kinds. The most used accounts for 77.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
7
77.8%
👏
2
22.2%
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 6 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 9reactions 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 6 September 2025 to 28 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.
هکاتون پل دوم در کارخانه هوشمصنوعی ایران
"دستیار هوشمند تحلیل و بهینهسازی پروموشنهای فروش"
«مسالهی واقعی از دل صنعت»
در هکاتون «پل دوم»، دادههای واقعی و ناشناسسازیشده فروش، قیمت، تخفیفها و کمپینهای گذشته یک صنعت در اختیار شرکتکنندگان قرار میگیرد تا با استفاده از هوشمصنوعی، راهکارهایی برای تحلیل اثر واقعی پروموشنها بر فروش و سودآوری و پیشنهاد سناریوهای مؤثرتر برای کمپینهای آینده توسعه دهند.
🏆 جایزه نق…
🔎رویداد هکاتون شهر هوشمند با محوریت حل چالش ترافیک شهری با کمک هوش مصنوعی فرصتی است برای گردهمآوردن متخصصان صنعت، تیمهای نوآور، فعالان هوش مصنوعی و انرژی تا یک روز کامل را به خلق راهحلهای واقعی و قابل اجرا اختصاص دهند.
💡در این رویداد که ۲۴ دی ۱۴۰۴ و بهصورت حضوری برگزار میشود، شرکتکنندگان تجربه میکنند:
- تیمسازی و کار گروهی
- تحلیل مسائل صنعت و طراحی راهحلهای مبتنی بر داده
- ارائه راهحل و داوری تخصصی
- شب…
🔴«آکادمی آنسو» برگزار میکند.
وبینار (آنلاین) رایگان «مدیریت محصول هوش مصنوعی»
اطلاعات رویداد به شرح زیر می باشد:
🔗لینک ورود مستقیم به وبینار:
https://event.alocom.co/class/aansoo.academy/webaipm04
📆تاریخ: دوشنبه 19 آبان ماه
🕠 ساعت: 17:30 الی 19:00
❗ راهنمایی: جهت ورود گزینه میهمان را انتخاب کرده و نام و نام خانوادگی و شماره موبایل خود را ثبت کنید.
💡اطلاعات بیشتر:
https://aanco.ir/1404/07/15/ai_product_management/
…
در یازدهمین رویداد تراکنش ایران (Transaction 2025)، مرکز نوآوری نکسترا با محوریت هوش مصنوعی و فناوریهای تحولآفرین،حضوری فعال و متفاوت داشت.
در پاویون هوش مصنوعی (غرفه ۲۸)، آخرین راهکارها و محصولات زیرساختی نکسترا برای صنعت فینتک،بانکداری و نوآوری مالی معرفی شد.
همچنین مرکزنوآوری نکسترا در پاویون هوش مصنوعی با ارائه راهکارهای نوین دیجیتال و محصولات هوشمند، نگاه تازهای به آینده بانکداری و فینتک ایران آورد.
سه روز …
هوش مصنوعی فقط ابزار نیست، یه تفکر جدیده در تصمیمگیری محصول.
وبینار رایگان «مدیریت محصول هوش مصنوعی» فرصتیه تا با حضور همه اساتید بوتکمپ و همکاری آکادمی آَنسو و نکسترا، با مسیر آینده مدیران محصول آشنا بشی.
در این رویداد آنلاین، درباره کاربردهای واقعی AI در طراحی، بازاریابی و تصمیمگیری محصول صحبت میکنیم و محتوای بوتکمپ رو از نزدیک مرور میکنیم.
🗓 پنجشنبه ۱۹ آبان
⏰ ساعت ۱۷:۳۰ تا ۱۹:۳۰
💻 حضور رایگان و آنلاین
…
💥 نکسترا، پاویون هوش مصنوعی نمایشگاه تراکنش را در دست گرفت!
🔹 مرکز نوآوری نکسترا با همکاری مرکز فابا، پاویون هوش مصنوعی نمایشگاه تراکنش ایران را راهاندازی کرد و فصل تازهای از ورود اکوسیستم هوش مصنوعی به صنعت بانکی را رقم زد.
⚙️ سعید علیوردیخانی، مدیر مارکتینگ نکسترا، میگوید:
«این همکاری نقطه عطفی است برای اتصال **استارتاپها و بانکها در پروژههای دادهمحور و شهر هوشمند».
🔹 بازدید از نمایشگاه امسال فوقالعاده…
🔹حضور فعال شرکت نکسترا در نمایشگاه یازدهم ایران
🗓۵ الی ۷ آبانماه ۱۴۰۴
📍تهران، مرکزآفرینش های کانون
🔍 اخبار مربوط به یازدهمین #رویداد_بزرگ_تراکنش_ایران را در سایت خبری #فابانیوز دنبال کنید.
🔺دومین روز از نمایشگاه بزرگ رویداد تراکنش
⚜در دومین روز از رویداد بزرگ تراکنش ایران، میزان استقبال از این نمایشگاه که از ۵ الی ۷ آبان در مرکز آفرینش های کانون و هتل لاله برگزار میشود و میزبان شرکتها و افراد فعال در حوزه صنایع بانکداری، مالی و نوآوری است بسیار بالا بود و علاقهمندان با حضور در این رویداد با شرکتها و سازمانهای فعال ارتباط برقرار میکنند.
نکسترا نیز با حضور فعال در این نمایشگاه در غرفه ۲۸ میزبان عل…
Showing the 12 most recent of 20 posts we hold for @nextera_factory. 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 — 522,250 of 1,169,250entries 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
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
Named by 3 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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“مرکز نوآوری نکسترا” (@nextera_factory), 753 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/nextera_factory.
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.