Channel
@nivauniver
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
216subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001151340376 |
|---|---|
| Type | Channel |
| Username | @nivauniver |
| Description | شرکت نیوا یونیور توسعه فردی، موفقیت و کارآفرینی ارتباط با دکتر جهانافروز احمدزاده 🆔️ @jahanafrooz51 🌐 www.nivauniver.com 📸 instagram.com/nivauniver |
| Created | Between 1 April 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/nivauniver |
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 84% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 1 other registered channel. They sit inside a group of 3 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @nivauniver/1057 · this entry27 Jul 2026, 04:39 UTC | @masterofbusiness/1001527 Jul 2026, 04:40 UTC | 1.00 | 72 seconds |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @masterofbusiness | 8 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | this entry (8–0) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 20 comparable posts for this entry, running 22 June 2026 to 3 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 3, the earliest publisher we hold is @alireza_yousefi_management. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
This channel’s posts match, word for word or near enough, posts on 2 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
1 more channel is in this same group but not listed individually here.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 03:31 | 216 | no change |
| 6 Aug 2026, 11:07 | 216 | first reading |
20 posts held, back to 22 June 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 1 pageof 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 5 of 10 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 August 2026 |
|---|---|
| Posts held | 20 (22 June 2026 – 3 August 2026) |
| Views total | 2,054 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 03:31 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.
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.
9 reactions across 9 posts, in 2 distinct kinds. The most used accounts for 77.8% of them.
| 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 9 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 22 June 2026 to 3 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.
هوش سازمانی؛ مزیت راهبردی مدیران عامل مدیرعامل موفق فقط نتایج امروز را مدیریت نمیکند؛ بلکه نشانههای فردا را نیز شناسایی میکند. هوش سازمانی یعنی توانایی سازمان برای دریافت درست اطلاعات، تصمیمگیری بهموقع و اصلاح سریع مسیر. برای تقویت هوش سازمانی، سه اقدام ضروری است: ۱. دسترسی به واقعیتهای سازمان اطمینان حاصل کنید که اطلاعات مهم، بدون فیلتر و تأخیر به مدیرعامل میرسد. اخبار نامطلوب نباید در لایههای مدیریتی متوقف …
عادات سمی مدیران کسبوکار مدیری که رفتار خودش را اصلاح نکند، دیر یا زود هزینه آن را در عملکرد تیم و سودآوری کسبوکار میپردازد. • همه کارها را خودش انجام میدهد: تیم وابسته و مدیر فرسوده میشود. راهکار: مسئولیتها را با خروجی، مهلت و اختیار مشخص واگذار کنید. • فقط هنگام خطا بازخورد میدهد: کارکنان بهجای رشد، از مدیر میترسند. راهکار: بازخورد منظم بدهید؛ ابتدا نقطه قوت، سپس فرصت بهبود. • اولویتها را دائم تغییر میده…
❤1
توان دوسویه مدیریتی و کاربرد آن در صنعت توان دوسویه مدیریتی یعنی مدیر بتواند هم از بالا به پایین مدیریت کند؛ یعنی هدف بدهد، تصمیم بگیرد و پیگیری کند، و هم از پایین به بالا ارتباط مؤثر داشته باشد؛ یعنی بازخورد بگیرد، مشکلات واقعی را بشنود و تصمیمهای خود را اصلاح کند. این ویژگی در صنعت بسیار مهم است، چون موفقیت فقط به دستور دادن نیست، بلکه به درک درست از میدان اجرا هم وابسته است. کاربردهای عملی در صنعت • در خط تولید: …
مدیران ذرهبینی؛ از نظارت تا فرسایش سازمان مدیر ذرهبینی معمولاً فکر میکند با ریزکنترل کردن همه امور، کیفیت را بالا میبرد؛ اما در عمل این سبک مدیریت، بیشتر از اینکه مفید باشد، به سازمان آسیب میزند. وقتی مدیر وارد جزئیات غیرضروری میشود، تیم از فکر کردن، تصمیم گرفتن و مسئولیتپذیری فاصله میگیرد و فقط منتظر تایید میماند. پیامدهای منفی مدیران ذرهبینی: • کاهش انگیزه و خلاقیت کارکنان • کند شدن تصمیمگیری و اجرای کار…
چگونه بزرگان فرو میریزند؟ افول افراد و سازمانهای بزرگ، معمولا نتیجه یک شکست ناگهانی نیست؛ بلکه پیامد مجموعهای از غفلتها، تصمیمهای دیرهنگام و فاصله گرفتن از واقعیتهای محیطی است. بسیاری از بزرگان زمانی دچار سقوط میشوند که موفقیت گذشته را تضمینی برای آینده تلقی میکنند و نیاز به بازنگری، یادگیری و تغییر را نادیده میگیرند. مهمترین عوامل این فروپاشی عبارتاند از: • اطمینان بیش از حد به دستاوردهای گذشته • کاهش ظرف…
❤1
هوش سازمانی توان سازمان برای فهم درست شرایط، تصمیمگیری بهموقع و یادگیری از تجربهها. چرا مهم است؟ چون در صنعت امروز، موفقیت فقط به سرمایه و تجهیزات وابسته نیست؛ بلکه به این بستگی دارد که سازمان: • چقدر زود مسئله را تشخیص میدهد • چقدر دقیق تصمیم میگیرد • چقدر کم خطای تکراری دارد نشانههای سازمان باهوش • اطلاعاتش پراکنده نیست • تصمیمها فقط سلیقهای نیست • اشتباهات مدام تکرار نمیشود • واحدها با هم هماهنگاند • در …
❤1
نظم شخصی مدیرعامل؛ مزیت پنهان رهبری مؤثر نظم شخصی برای مدیرعامل فقط بهمعنای منظم بودن در کارها نیست؛ بلکه یعنی توانایی حفظ تمرکز، تصمیمگیری دقیق، مدیریت زمان و پایبندی به اولویتهای کلان سازمان حتی در شرایط فشار و آشفتگی. مدیرعاملی که نظم شخصی دارد: • وقت خود را صرف امور کماهمیت نمیکند • جلسات، تصمیمها و پیگیریها را هدفمند مدیریت میکند • بین فوریت و اهمیت تفاوت قائل میشود • انرژی خود را روی مسائل اثرگذار متمر…
❤1
رهبری در طوفان: چگونه در اوج عدم قطعیت، سازمان را هدایت کنیم؟ همکاران و مدیران گرامی، در دنیای امروز، «عدم قطعیت» یک بحران موقت نیست؛ بلکه واقعیتِ جاری کسبوکار است. تفاوت یک مدیر معمولی با یک رهبر پیشرو، در نحوه مواجهه با همین شرایط مهآلود مشخص میشود. رهبران بزرگ منتظر آرام شدن طوفان نمیمانند؛ آنها یاد میگیرند که چگونه در طوفان پیشروی کنند. چهار استراتژی کلیدی برای رهبری حرفهای در شرایط ابهام: ۱. جهتگیریِ قاط…
آیا سازمان شما در برابر بحران واکسینه شده است یا در آستانه «فلج ساختاری»؟ بحران، نقصهای ساختاری را خلق نمیکند؛ آنها را «افشا» میکند. سازمانی که در روزهای آرام «کارآمد» است، لزوماً در روزهای پرفشار «تابآور» نیست. نشانههای هشداردهنده «فلج ساختاری»: ۱. تمرکز بیش از حد: وابستگی تمام تصمیمات کلیدی به شخصِ مدیرعامل. ۲. فیلترینگ اطلاعات: کندی یا سوگیری در انتقال اخبارِ بد به لایههای تصمیمگیر. ۳. ابهام در مسئولیت: فر…
ژن کارآفرینی به ارث نمیرسد؛ جانشین باید ساخته شود! بسیاری از مدیران و بنیانگذاران تصور میکنند فرزندشان صرفاً با حضور در شرکت یا داشتن نام خانوادگی مشترک، آمادهی در دست گرفتن سکان کسبوکار است. اما آمارها بیرحماند: بیش از ۷۰ درصد کسبوکارهای خانوادگی به نسل دوم نمیرسند. انتقال قدرت به فرزندان، انتقال یک دارایی نیست؛ انتقال یک مسئولیت سنگین است. برای اینکه میراث شما قربانی بیتجربگی نشود، این ۳ گام کاربردی را در…
👍1
📌 تلهی «هیچکس مثل خودم انجامش نمیدهد»؛ آیا شما گلوگاه رشد سازمان خود هستید؟ همکاران و مدیران عامل گرامی، بسیاری از ما مسیر کارآفرینی و مدیریت را با تکیه بر تخصص، وسواس در کیفیت و پیگیریهای جزئی خودمان آغاز کردهایم. اما واقعیت تلخ این است: «آنچه شما را به این نقطه رسانده، لزوماً نخواهد توانست شما را به مرحله بعد ببرد.» وقتی سازمان رشد میکند، اصرار بر دخالت در ریزترین جزئیات (Micromanagement)، از یک مزیت رقابتی ب…
مدیریت سبد سرمایهگذاریِ یک مدیرعامل؛ فراتر از اعداد در میان مشغلههای روزمره و چالشهای عملیاتی، گاهی فراموش میکنیم که «مدیرعامل» تنها داراییِ نقدشوندهی سازمان نیست؛ ما خودمان «پروژهی اصلی» هستیم. بیایید نگاهی به سبد سرمایهگذاری یک رهبرِ پیشرو بیندازیم. اگر بخواهیم نرخ بازگشت سرمایه (ROI) را در سه لایه اصلی بهینه کنیم، وضعیت چطور خواهد بود؟ ۱. سرمایهگذاری روی خود (لایه استراتژیک): تمرکز بر تابآوری شناختی و مدی…
Showing the 12 most recent of 20 posts we hold for @nivauniver. 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 — 698,922 of 1,151,006entries 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.
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.
Named by 1 registered channel — 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.
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.
“NIVAuniver | گروه متخصصان و خبرگان صنعتo” (@nivauniver), 216 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/nivauniver.
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.