Religion — 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 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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 the other topics.
Observations
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.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. 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.
Matching posts — open both and compare (2 of the pairs behind the counts below)
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 2 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 24 comparable posts for this entry, running 26 July 2026 to 7 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.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @tafsiroqs. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, 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.
63 measurements spanning 94 days, net +152. 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 65,122–65,796 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 63
Measured (UTC)
Subscribers
Change
8 Nov 2026, 10:56
65,718
+11
7 Nov 2026, 08:25
65,707
+6
6 Nov 2026, 09:17
65,701
-9
5 Nov 2026, 11:17
65,710
+1
4 Nov 2026, 12:29
65,709
+15
3 Nov 2026, 13:09
65,694
+14
2 Nov 2026, 15:50
65,680
+20
1 Nov 2026, 12:39
65,660
+10
31 Oct 2026, 10:29
65,650
+7
30 Oct 2026, 13:18
65,643
+2
29 Oct 2026, 12:19
65,641
+4
28 Oct 2026, 09:19
65,637
+12
27 Oct 2026, 10:06
65,625
+55
26 Oct 2026, 13:35
65,570
+35
25 Oct 2026, 13:14
65,535
+38
24 Oct 2026, 14:25
65,497
+31
23 Oct 2026, 14:36
65,466
+27
22 Oct 2026, 17:10
65,439
+47
21 Oct 2026, 11:57
65,392
+11
20 Oct 2026, 12:40
65,381
first reading
Engagement
144 posts held, back to 26 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 190 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
6.10%
avg views ÷ 65,718 subscribers
Avg views / post
4,010
29 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
29
of 144 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 8 November 2026
Posts held
144 (26 July 2026 – 8 November 2026)
Views total
116,213
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Nov 2026, 21:27 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
Photos
≈5,240
Videos
≈203
Links
≈5,130
Lifetime counters from Telegram’s own channel header, read 8 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
1m 08s
Average length
1m 08s
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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 29 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
تقدم هذه المقالة قراءة نقدية لكتاب (تلاد الإعجاز) للدكتور/ عبد اللطيف التويجري، فتناقش منهجه في استجلاء وجوه الإعجاز القرآني من آثار السلف، وما يتعلّق بتحرير المصطلحات والتقسيمات، ومدى انطلاقه من أقوال السلف في معالجة قضية الإعجاز.
🔗| https://tafsir.net/articles/24887
#مركز_تفسير
🎙 ضيفنا هذا الشهر في #لقاء_أهل_التفسير_الـ86
د.حسن بن محمد الحفظي
عضو هيئة التدريس بجامعة الإمام محمد بن سعود الإسلامية (سابقًا)
📄 عنوان اللقاء:
العلاقة بين النحويين وعلوم القرآن
🗓 الموعد:
بعد غدٍ الثلاثاء ٣٠ جمادى الأولى ١٤٤٨هـ
الموافق: ١٠ نوفمبر ٢٠٢٦م
⏰ بعد صلاة العشاء
📍 في ديوانية أسرة الشدي - الرياض (مخرج ٥):
https://maps.app.goo.gl/hd734KfX8TR6pRf98?g_st=ic
#لقاءات_أهل_التفسير #مركز_تفسير
تسعى هذه المقالة لتتبُّع ما ذكره القرآن الكريم من أسباب بقاء النِّعم وزيادتها، وما ذكره من موجبات زوالها، وعواقب كفرانها، مع الاستدلال بالآيات وقصص الأُمَم التي حفظَت النعم بالشُّكْر أو بدّلتها بالكفران.
https://tafsir.net/articles/24842
#مركز_تفسير
✨ يسرنا في #مركز_تفسير دعوتكم لحضور #لقاء_أهل_التفسير_الـ86
📄 بعنوان:
العلاقة بين النحويين وعلوم القرآن
🎙 ضيف اللقاء:
د. حسن بن محمد الحفظي
عضو هيئة التدريس بجامعة الإمام محمد بن سعود الإسلامية (سابقًا)
🗓 يوم الثلاثاء ٣٠ جمادى الأولى ١٤٤٨هـ
الموافق: ١٠ نوفمبر ٢٠٢٦م
⏰ بعد صلاة العشاء
📍 المكان:
ديوانية أسرة الشدي - الرياض (مخرج ٥):
https://maps.app.goo.gl/hd734KfX8TR6pRf98?g_st=ic
فأهلًا وسهلًا بكم،،
#لقاءات_أهل_…
تتناول هذه المقالة منهج القرآن الكريم في بيان الأحكام الشرعية، من حيث أساليب العرض والتدرّج والتيسير ومراعاة المقاصد، مع إبراز الخصائص التشريعية للخطاب القرآني وأثرها في بناء التصوّر الفقهي وترسيخ الهداية والتكليف.
https://tafsir.net/articles/24789
#مركز_تفسير
تناقش المقالةُ حدود الفهم والتدبر القرآني في عصر الذكاء الاصطناعي، وتميّز بين معالجة النصّ ومحاكاة خطاب التدبّر وممارسته، وتسعى إلى تحديد موقع الذكاء الاصطناعي بوصفه أداة معرفية مسانِدة مع بقاء المسؤولية العلمية لدى الباحث.
🔗| https://tafsir.net/articles/24880
#مركز_تفسير
تبحث المقالة في صحة الثناء المنسوب إلى النووي على (جامع البيان عن تأويل آي القرآن)، للإمام محمد بن جرير الطبري، وتذهب إلى عدم صحته.
https://tafsir.net/articles/24786
#مركز_تفسير
في هذه المقالة نقدِّم عددًا من ملخّصات الدراسات المنشورة في بعض المجلات العلمية الغربية المعاصرة، من أجلِ لفتِ أنظار الباحثين إلى أهم ما يُنشر في هذه الدوريات العلمية حول القرآن الكريم وعلومه.
🔗| https://tafsir.net/papers/24874
#مركز_تفسير
تعرِض هذه المقالة أبرز ملامح منهج ابن جرير الطبري في نقد المرويات عن الصحابة، من خلال تقديم أقوالهم، وتمييز أصحّها، ونقد أسانيدها ومتونها، ومقارنة طُرُقِها، وبيان موقفه من مرويات الرواة المجروحين عنهم، وهي مستلّة من كتاب (الصناعة النقدية في تفسير ابن جرير الطبري).
https://tafsir.net/articles/24840
#مركز_تفسير
يعدّ كتاب: The Early Qur'an in Mecca: Apocalyptic Expectation at the Dawn of Islam من الكتب الغربية الصادرة مؤخرًا، نقدِّم هنا تعريفًا بالكتاب، وبمحتويات فصوله، كما نشير لبعض جوانب أهميته للدارِسين.
https://tafsir.net/definitions/24783
#مركز_تفسير
تيسيراً لمهام الباحثين والدارسين، يُعلن مركز تفسير للدراسات القرآنية عن إطلاق الموقع الإلكتروني لمنظومة باحوث «باحوث دوت نت»، بالتزامن مع صدور التحديث البرمجي الجديد للتطبيق (الإصدار 13.3.3)، والذي يتضمن حزمة من الخصائص البحثية والإحصائية المستحدثة:
1- البحث الموضوعي
اختيار الموضوع لتظهر الآيات المعنية به مباشرة.
2- البحث بين الآيات
البحث عن كلمات متفرقة في آيات متجاورة، لا في آية واحدة فحسب.
3- التشابه الشكلي
الت…
Showing the 12 most recent of 144 posts we hold for @tafsircenter. 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.
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 2 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 21 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
أكاديمية البرهان @alborhanacademy · 35,634 Telegram ranks this channel #6 of 97 here — alongside 96 others — read 1 September 2026
اقرأ التفسير في ٣٠٠ يوم @TafseerReads · 29,488 Telegram ranks this channel #31 of 83 here — alongside 82 others — read 8 September 2026
برنامج "مُدَّكِر" - القناة العامة @ModdakerELearn · 49,055 Telegram ranks this channel #37 of 95 here — alongside 94 others — read 26 August 2026
📚 أخلاق إسلامية 📚 @akhlakaslamea · 70,059 Telegram ranks this channel #50 of 93 here — alongside 92 others — read 20 August 2026
المكتبة القرآنية @Mishref_Quran · 61,131 Telegram ranks this channel #52 of 96 here — alongside 95 others — read 22 August 2026
المجالس القرآنية @majals_quran · 28,135 Telegram ranks this channel #53 of 85 here — alongside 84 others — read 12 September 2026
نماء - تربية وبناء 📊 @YanabeeTaN · 19,415 Telegram ranks this channel #73 of 94 here — alongside 93 others — read 1 October 2026
اقرأ السنة في ٣٠٠ يوم @SonnaReads · 18,954 Telegram ranks this channel #76 of 92 here — alongside 91 others — read 3 October 2026
شبكة الطريق إلى الله - Way2allah.com @way2allahcom · 32,688 Telegram ranks this channel #84 of 94 here — alongside 93 others — read 4 September 2026
صناعة الشخصِيَّة القرْآنيَّة - القناة العامة. @quranyhayatty · 34,656 Telegram ranks this channel #88 of 95 here — alongside 94 others — read 2 September 2026
أكاديمية علوم الدولية - الدبلومات والدورات العلمية @isaonlinenet · 39,847 Telegram ranks this channel #91 of 95 here — alongside 94 others — read 30 August 2026
This channel appears in 11 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
3 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 8 November 2026 — this
entry's latest reading, not the date you are reading this.
“مركز تفسير للدراسات القرآنية” (@tafsircenter), 65,718 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/tafsircenter.
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.