3 measurements spanning 4 days, net -4. 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 1,978–1,984 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
11 Aug 2026, 07:16
1,979
-4
7 Aug 2026, 12:02
1,983
no change
7 Aug 2026, 11:48
1,983
first reading
Engagement
20 posts held, back to 23 March 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
43.7%
avg views ÷ 1,979 subscribers
Avg views / post
866
3 posts measured
Reaction rate
4.39%
reactions ÷ views · ER floor
Posts in window
3
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 6 August 2026
Posts held
20 (23 March 2026 – 6 August 2026)
Views total
2,597
Reactions total
114
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 18:05 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
356 reactions across 17 posts, in 2 distinct kinds. The most used accounts for 98.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
349
98.0%
👎
7
1.97%
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 17 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 356reactions 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 23 March 2026 to 6 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.
وطن جایی است که کنار دریایش که نشسته ای،بچه مردم می آید با تویوپ طرح پرچم آمریکایش و به زبان مادری بهت میگوید خاله بیا بازی و تو خاله اش هستی...
وطن یعنی میتوانی حرفهای آدمها رو گوش کنی و از لهجه شان بفهمی آن پدر و دختری که قلعه میسازند خوزستانی اند و آن خواهرانی که بچه هایشان را آماده آب بازی میکنند ترکمنند و آنها که روی زیرانداز نشسته اند بلوچند و ...
وطن یعنی لهجه آدمها و چهره شان و لباسشان و رنج هایشان را میشناسی…
گروه روانشناسی اجتماعی و شورای دانشجویی انجمن جامعه شناسی ایران برگزار می کنند:
نشست نهم از سلسله نشست های زیست در زمانه بحران:
«امید رسیدن یا جرأت ادامه دادن؟»
سخنران:سعید مدنی
دبیر نشست: پریا اسماعیلی
زمان: سه شنبه ۶ مرداد ۱۴۰۵ ساعت ۱۵:۳۰
مکان: گوگل میت
لینک نشست:
https://meet.google.com/ptz-dmbh-psx
#انجمن_جامعه_شناسی_ایران
@iran_sociology
پناه بر بخار فنجان ها
فاطمه علمدار
۱_در فیلم (۲۰۱۰)Inception, شغل آدمها به خواب رفتن بود و گاهی آنقدر شرایط پیچیده میشد که نمیتوانستند تشخیص بدهند الان خواب هستند یا بیدار؛ پس چیزی ساختند به نام "توتم". هرکس توتم خودش را داشت.چیزی که تابع قوانین طبیعت بود، مثل فرفره ای که در دنیای واقعی وقتی بچرخانی اش بالاخره از چرخش خواهد افتاد ولی در خواب میتواند تا ابد بچرخد...آدمها به توتم هایشان پناه میبردند تا بفهمند خواب هس…
اگر داستانی مینوشتم دربارهی روزگاری که میگذرانیم میشد که نامش را «حباب» بگذارم.
مینوشتم چطور زندگیهامان به زیستن درون حبابی از کف میمانست.
ما که بیپناه و بیحفاظ میکوشیدیم حریم خود را از بیرون جدا کنیم اما ضمنا میدیدیم که دیوارهای نگهبان ما چه پایه ضعیف و نازکند.
برای خود، برای این زندگیهای سادهی خواستنی که از آن ما بود، وزن و شأنی قائل بودیم، اما هر لحظه هم میشد که ناگاه به خود آییم و با تلنگری بیدار ش…
گذار از سرزمین عجایب
محمدرضا کلاهی
مدتی است انگار وارد سرزمین عجایب شدهایم. تصور کنید یک سال پیش چند دقیقه به امروز پرتاب میشدید و در خبرها میدیدید هزاران نفر در خیابانهای ایران شعار جاوید شاه دادهاند و به گلوله بسته شدهاند. آمریکا و اسرائیل به ایران حمله کرده و چهل روز مراکز نظامی و نفتی و زیرساختی ایران را بمباران کردهاند. یک مدرسهای ابتدایی بمب خورده و بیش از ۲۷۰ بچه کشته شدهاند. ایران به تلافی، تأسیسات …
گاهی بحران تمام نمیشود.
فقط شکلش عوض میشود و میآید داخل زندگی روزمره.
آنقدر تکرار میشود که دیگر اسمش را «عادی» میگذاریم.
خبرهای بد، ناامنی، فشار اقتصادی، ترسهای پراکنده…
همه در پسزمینهی زندگی روشن میمانند؛
مثل صدایی که قطع نمیشود، فقط عادتش میکنیم.
اما عادتکردن به درد، به معنای حلشدنش نیست.
چیزی که مجال روایت پیدا نکند،
در بدن میماند:
در بیخوابی، خستگی مزمن، بیحوصلگی، دلآشوبی.
وقتی فرصت سوگواری ن…
وضعیت روانی جامعه ایران را میتوان از خلال یک استعاره فهمید:
«ترنزیشن»
نه فقط بهعنوان تجربهی فردی ترنسجندر، بلکه بهمثابه یک فرآیند روانی-جمعی.
در تجربه ترنسجندر، ترنزیشن فقط تغییر بدن نیست؛
عبور از یک نظم نمادین قدیمی به سوی نظمی دیگر است.
با اضطراب، فقدان، سوگ و بازساخت هویت همراه است.
جامعه ایران نیز در چنین برزخی قرار دارد.
از منظر لکانی، سوژه درون «نظم نمادین» تعریف میشود.
وقتی این نظم ترک برمیدارد، سوژه …
یادداشت های فاطمه علمدار pinned «مدتی است که با اسم این کانال راحت نیستم. حس میکنم آنچه در اینجا میگذرد روانشناسی اجتماعی ایرانیان نیست، هرچند که قصد داشتم این باشد... این روزها ولی نمی توانم به آن قصد پای بند باشم و ترجیح میدهم کسی برای این اسم وارد این کانال نشود و به آنچه که میخواهد نرسد...…»
مدتی است که با اسم این کانال راحت نیستم. حس میکنم آنچه در اینجا میگذرد روانشناسی اجتماعی ایرانیان نیست، هرچند که قصد داشتم این باشد...
این روزها ولی نمی توانم به آن قصد پای بند باشم و ترجیح میدهم کسی برای این اسم وارد این کانال نشود و به آنچه که میخواهد نرسد...
اینجا یادداشت های من است.فاطمه علمدار که جامعه شناسی خوانده ام و با عینک روانشناسی اجتماعی سراغ جامعه میروم و دغدغه ام بیش از همه فکر کردن به ما ایرانیها و حا…
یک عمر و آتش بس و ۱۶ روز
۱/از ایران آمدم بیرون.در اتوبوس بودم که آتش بس شد.آن سه شنبه سهمگین را در جاده ها گذراندم و زمین و آسمان و پل و کابل برق و مردم را گریه کردم.
جای دوری نرفتم.همین بغل خودمان. ترکیه.
۲/هفته اول به جان دادن گذشت.از هفته دوم کم کم توانستم اطراف را ببینم.اینترنت آزاد بود.بعد از ده سال توانستم تلگرام و واتس آپ را روی لپ تاپ نصب کنم و چتgpt را هم.
اینجا پر از عکس و مجسمه آتاتورک است و خیلی کم اردو…
👍31👎1
Showing the 12 most recent of 20 posts we hold for @fsalamdar63. 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 — 1,063,656 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
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
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.
Handles this channel named that no longer answer
Dead references
2
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
2
vacant every time we have ever looked
@fsalamdar63 named 2 handles 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.
@ravanshid_group named in 2 posts, 8 August 2026 – 8 August 2026
@neoritic 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 11 August 2026 — this
entry's latest reading, not the date you are reading this.
“یادداشت های فاطمه علمدار” (@fsalamdar63), 1,979 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/fsalamdar63.
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.