3 measurements spanning 7 days, net +11. 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 459–474 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 22:13
472
+11
6 Aug 2026, 19:04
461
no change
5 Aug 2026, 23:38
461
first reading
Engagement
16 posts held, back to 2 March 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
19.1%
avg views ÷ 472 subscribers
Avg views / post
90.0
1 post measured
Reaction rate
1.11%
reactions ÷ views · ER floor
Posts in window
1
of 16 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 18 July 2026
Posts held
16 (2 March 2025 – 18 July 2026)
Views total
90
Reactions total
1
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Aug 2026, 19:04 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
42 reactions across 13 posts, in 7 distinct kinds. The most used accounts for 42.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
18
42.9%
❤
9
21.4%
👏
4
9.52%
😱
4
9.52%
🤣
4
9.52%
😐
2
4.76%
👎
1
2.38%
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 13 of the 16 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 42reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 2 March 2025 to 18 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.
تصویر ساختگی منتسب به وجود لانچر در مقابل بیمارستان بقایی اهواز
🔹تصویری در شبکههای اجتماعی منتشر شده که ادعا میکند یک لانچر را در محوطه بیمارستان بقایی اهواز نشان میدهد.
🔹این تصویر ساختگی است.
🔹تابلوهای سردرهای بیمارستان بقایی اهواز، با آنچه در این تصویر دیده میشود، شباهتی ندارند.
🔹در این عکس، ساختمانهای بلندتر از بیمارستان در اطراف آن دیده میشود، اما در حوالی محل واقعی بیمارستان، چنین ساختمانهایی وجود ندا…
این تصویر منتسب به درگیری مسلحانه در مشهد، ساختگی است
تصویری در شبکههای اجتماعی منتشر شده که ادعا میشود مربوط به درگیری مسلحانه ۱۸ تیر ۱۴۰۵ در مشهد است.
این تصویر جعلی است و با ابزارهای هوش مصنوعی تولید شده است.
کلمه «NISSAN» در پشت یک وانت پیکان آن هم با دیکته اشتباه، درهمریخته بودن پلاک خودرو، علامت راهنمایی و رانندگی بیمعنی، ایرادهای ساختاری در بدنهای افراد و غیرمنطقی بودن وضعیت شلیکها، از جمله نشانههای …
این فیلم مربوط به ایران نیست
طی بررسی ها، فیلمی که با عنوان ضرب و شتم یک زن جوان توسط نیروهای امنیتی ایران منتشر شده مربوط به ترکیه است. این فیلم در سال ۲۰۲۵ در رسانههای ترکیه منتشر و ضارب هم توسط پلیس بازداشت شده است.
@khatarnegaran
امنیت هوش مصنوعی
این موارد را به چتباتها در میان نگذارید
ـ شماره کارت بانکی و رمزها
ـ شماره ملی یا شناسنامه
ـ آدرس دقیق محل سکونت
ـ شماره تلفن ثابت و همراه
ـ عکس کارت ملی یا پاسپورت
ـ اطلاعات شغلی محرمانه
ـ اطلاعات پزشکی خصوصی
ـ قراردادهای کاری
ـ مدارک حقوقی
ـ پروژههای دارای حق مالکیت فکری
ـ مکاتبات خصوصی
ـ اسرار خانوادگی یا کاری
@khatarnagaran
تکنیک های تیترزنی
استقبال شعری
«باران میبارد امشب»
هرگاه بخواهیم، از غنای شعری در روزنامه نگاری نیز استفاده کنیم، دامنه آن بسیار گسترده میشود؛ به ویژه هنگام نگارش و ساخت یک متن، اما در تیتر استفاده از این تکنیک که از آن به نقیضه نیز یاد میشود، کاربرد محدودی دارد.
مثال:
باران میبارد امشب
یادآور ترانۀ معروف «رحمان شکوفه» با صدای امید؛ تیتری که نویدباران و امید به بارندگی را در دل دارد.
@khatarnegaran
زیباترین تیترهای روزنامه ها در مورد حذف صفر از پول ایرانی
تیتر غلط به خاطر تکرار یک واژه: ریال جدید در آستانه صدسالگی ریال (ایران)
تیتر معمولی و خبری: اقتصاد ایران در چالش صفرها (آرمان ملی)
تیتر نسبتا جالب: جراحی زیبایی ریال ( دنیای اقتصاد)
تیتر برتر، زیبا و خلاقانه:
صفرشویی (جام جم)
✍محمدامین خوش نیت
@khatarnegaran
انتشار تصویر انفجار گاز در رضوانشهر به اسم تبریز!
تصویری از آتش سوزی یک واحد مسکونی(انفجار گاز) در رضوانشهر گیلان با عنوان حمله ریزپرندهها به مقر فرماندهی انتظامی آذربایجان شرقی در خیابان صائب تبریز به صورت گسترده منتشر شده که صحت ندارد
@khatarnegaran
بازنشر خبر بارش برف در آزادراه تبریز زنجان محدوده شهرستان بستان آباد توسط برخی رسانههای محلی!
این ویدئو که در حال انتشار است مربوط به ۲۶ فروردین سال جاری است
@khatarnegaran
فریب تصاویر هوش مصنوعی را نخورید!
همه این تصاویر ساخته هوش مصنوعی است
حتی خود اکانت سازنده تصاویر هم به ساختگی
بودن آنها اشاره کرده است.
@khatarnegaran
برگزاری کارگاه آموزشی «خبرنگاری بحران» ویژه اصحاب رسانه آذربایجانشرقی
شرکتکنندگان در این کارگاه، گواهی معتبر جهاددانشگاهی را دریافت خواهند کرد.
شرکت در این کارگاه برای تمامی خبرنگاران استان رایگان و آزاد است.
@khatarnegaran
بازهم انتشار خبر فیک!
تصویر بالا با عنوان «پوشاندن چهره قاتل الهه حسین نژاد و پخش تصاویر دانش آموزان متقلب » منتشر شده، در حالی که این تصویر مربوط به پلاتوی پایانی گزارش خبر ۲۱ در مورد حفاظت از امتحانات نهایی در تاریخ ۲۹ اردیبهشت سال ۱۴۰۳ است و ربطی به دانش آموزان متقلب و شناسایی متقلبان در امتحانات ندارد.
@khatarnegaran
Showing the 12 most recent of 16 posts we hold for @khatarnegaran. 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 — 426,462 of 1,481,217entries 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 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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@khatarnegaran named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@khatarnagaran named in 1 post, 8 August 2026 – 8 August 2026
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.
“خطرنگاران” (@khatarnegaran), 472 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/khatarnegaran.
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.