Film & TV — 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 8 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 why it has no browse page of its own yet.
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.
Views and reactions moved apart
On 4 of the 98 posts we watched over 30 days, the view counter climbed while the reaction counter stayed where it was — by more than this channel’s own reactions-per-view rate can account for. That rate, measured on this entry, is 0.0018 reactions per view.
Each interval, as we read it — views and reactions before and after
Expected is the view gain multiplied by this channel’s own prior reactions-per-view rate over the same post — not a corpus average, so a channel whose audience never reacts is compared only against itself. Every interval is credited in the direction that makes the observation harder to record, never easier: t.me renders views and reactions to three significant figures above ~1,000, so a raw delta can be a rendering step. Every delta below is at least 4 x the coarser reading's step, the view gain is discounted by a full step and the reaction gain credited with one. Measured by tgregister velocity.py (our own t.me/s/ readings).
What this does and does not say. It says the two counters moved apart, by more than rounding and more than this channel’s own history predicts. It asserts no cause. Views arriving from outside Telegram, an embedded or forwarded copy of the post, and a burst of readers who simply do not react all produce this shape. This detector has recorded very few observations across the whole register, and its precision has not been measured; treat it as an anomaly worth looking at, not as a finding.
Recorded under the key view_reaction_decoupling, last confirmed 20 September 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.
Growth
32 measurements spanning 42 days, net -11,015. 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 1,080,333–1,094,652 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
18 Sept 2026, 10:37
1,081,985
-852
16 Sept 2026, 00:38
1,082,837
-483
14 Sept 2026, 10:40
1,083,320
+104
12 Sept 2026, 17:18
1,083,216
+1,091
10 Sept 2026, 18:58
1,082,125
-1,291
7 Sept 2026, 16:00
1,083,416
-1,041
4 Sept 2026, 15:57
1,084,457
-758
3 Sept 2026, 00:23
1,085,215
-84
1 Sept 2026, 23:26
1,085,299
-303
1 Sept 2026, 01:18
1,085,602
-761
31 Aug 2026, 02:16
1,086,363
-497
30 Aug 2026, 00:27
1,086,860
-366
28 Aug 2026, 22:05
1,087,226
-380
27 Aug 2026, 20:43
1,087,606
-318
26 Aug 2026, 18:25
1,087,924
-440
25 Aug 2026, 19:12
1,088,364
-389
24 Aug 2026, 18:58
1,088,753
-691
23 Aug 2026, 04:05
1,089,444
+280
21 Aug 2026, 16:39
1,089,164
-348
20 Aug 2026, 12:03
1,089,512
first reading
Engagement
197 posts held, back to 5 August 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 94 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
3.10%
avg views ÷ 1,081,985 subscribers
Avg views / post
33,600
102 posts measured
Reaction rate
0.171%
reactions ÷ views · ER floor
Posts in window
102
of 197 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 20 September 2026
Posts held
197 (5 August 2026 – 20 September 2026)
Views total
3,423,920
Reactions total
5,841
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
21 Sept 2026, 05:47 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
≈2,420
Videos
≈1,390
Links
≈2,040
Lifetime counters from Telegram’s own channel header, read 21 September 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
2h 38m
Average length
59s
Measured directly from 162 videos 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
Computed from 98 of this channel’s own posts over the last 30 days: across 94 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 25 hours of being posted; a typical post has already reached 14.9% of its 24-hour view count within the first hour, and 50.2% within the first six; the median 24-hour reach across those posts is 16,300 views — 1.51% of this channel’s own subscriber count (90th percentile 18,100).
8 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed views is the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
10,734 reactions across 197 posts, in 8 distinct kinds. The most used accounts for 80.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
8,667
80.7%
🔥
577
5.38%
🥰
562
5.24%
😍
510
4.75%
👍
182
1.70%
🤯
96
0.894%
😨
88
0.82%
😢
52
0.484%
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 197 of the 197 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 10,734 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 197 most recent posts we hold, published 5 August 2026 to 20 September 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.
Telegram Stars
Stars received
9
across the posts below
Posts paid on
9
of 197 we hold a reading for · 5%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @NETFLIX23i. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 197 most recent posts we hold for this entry, published 5 August 2026 to 20 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
فيرنانديـنيو لاعب كرة قدم سابق وربّ أسرة يحاول الاستمتاع بحياة هادئة بعد اعتزاله بينما يكرّس وقته لعائلته والعمل في برنامج رياضي عبر الإنترنت لكن حياته تنقلب عندما يكتشف سرًا غريبًا يتعلق بزوج شقيقته غريغ الذي يتصرف بطريقة مريبة ويخفي حقيقة غير متوقعة: فهو مصاص دماء في البداية يحاول فيرنانديـنيو التعامل مع الأمر وكأنه مجرد مشكلة عائلية لكن سرعان ما يكتشف أن غريغ لا يمثل خطرًا على العائلة وحدها بل لديه مخططات أكبر تهد…
الأميرة سنو وايت التي تعيش تحت حكم زوجة أبيها الملكة الشريرة امرأة غيورة تسعى للحفاظ على مكانتها وسلطتها بأي ثمن ومع مرور الوقت تدرك الملكة أن سنو وايت أصبحت تشكل تهديدًا لمكانتها فتقرر التخلص منها تجد سنو وايت نفسها مجبرة على الهروب من القصر واللجوء إلى الغابة حيث تلتقي بمجموعة من الأقزام السبعة الذين يصبحون حلفاء لها في مواجهة الخطر وخلال رحلتها تتعرف سنو وايت أيضًا على جوناثان الشاب الذي يشاركها الرغبة في تغيير وا…
بارتليبي ولوكي، يجدان طريقة قد تسمح لهما بالعودة إلى الجنة بعد نفيهما منها. لكن عودتهما بهذه الطريقة قد تؤدي إلى عواقب تهدد وجود العالم بأكمله لهذا السبب يتم اختيار بيثاني، وهي امرأة فقدت الكثير من إيمانها، للقيام بمهمة غير عادية تتمثل في إيقاف الملاكين قبل أن ينجحا في تنفيذ خطتهما تنطلق بيثاني في رحلة غريبة برفقة مجموعة من الشخصيات غير المألوفة، من بينهم روفوس، الذي يدّعي أنه الرسول الثالث عشر، وجاي وسايلنت بوب، إلى…
رينيه مورغان، أم عزباء تعيش مع ابنها الصغير في حياة هادئة، وتحاول الاهتمام به رغم ظروفها الشخصية في أحد الأيام، تتعرض رينيه للاختطاف بشكل مفاجئ على يد مجموعة غامضة، وتستيقظ لتجد نفسها محتجزة داخل منشأة سرية لا تعرف مكانها أو سبب وجودها هناك يبدأ خاطفوها بإخضاعها لسلسلة من الاختبارات النفسية الغريبة، مستغلين أكثر مخاوفها عمقًا، بينما تحاول رينيه فهم سبب اختيارها وما الذي يريده منها هؤلاء الأشخاص ومع اكتشافها أن هناك أ…
روديون ميجلين، محقق غامض وبارع يتمتع بقدرة استثنائية على كشف أكثر القضايا تعقيدًا، لكنه يعمل بطريقة خاصة لا يكشف أسرارها لأحد تنضم إليه إسينيا ستيكلوفا، خريجة قانون طموحة تبدأ العمل متدربة تحت إشرافه، مدفوعة برغبة شخصية في الوصول إلى الحقيقة وراء جريمة قديمة أثرت في حياتها تجد إسينيا نفسها أمام محقق مختلف تمامًا عما توقعت فأسلوب ميجلين في فهم المجرمين وتحليل سلوكهم غير تقليدي، وكل قضية جديدة تكشف لها جانبًا أكثر غموض…
هوب فتاة مراهقة تعيش حياة هادئة وسط عائلتها ومجتمعها الصغير إلى أن تتعرف على شخص جديد تظنه صديقًا جديرًا بالثقة قبل أن تكتشف أن نواياه ليست كما تبدو تتعرض هوب للاختطاف وتجد نفسها عالقة في عالم قاسٍ تُحرم فيه من هويتها وحريتها بينما تواصل عائلتها البحث عنها وعدم التخلي عن الأمل في عودتها وبعد أن تتمكن هوب من التحرر والعودة إلى عائلتها تبدأ مرحلة جديدة أكثر تعقيدً فالأمان لا يعني أن كل شيء عاد إلى ما كان عليه عليها أن …
بن، مصور فوتوغرافي، وزوجته الجديدة جين، اللذين ينتقلان إلى اليابان بعد حصول بن على فرصة للعمل في مجال التصوير في أثناء رحلتهما يتعرض الزوجان لحادث غامض على طريق جبلي، ويعتقدان أنهما صَدما فتاة ظهرت فجأة أمام سيارتهما، لكنهما لا يعثران على أي أثر لها بعد الحادث بعد وصولهما إلى طوكيو، تبدأ جين بملاحظة أمر غريب في الصور التي يلتقطها بن، إذ تظهر فيها بقع وأشكال بيضاء غامضة تشبه ظلال أشخاص ومع تكرار هذه الظاهرة، يبدأ الزو…
طالبتَي التمريض بيكا وأروم اللتين تبدآن فترة التدريب العملي في عيادة أسنان تابعة لمستشفى صغير في جاوة الوسطى بإندونيسيا تقع العيادة داخل مكان يحمل تاريخًا غامضًا إذا كانت مغلقة لفترة طويلة بسبب أحداث مقلقة ارتبطت بها وتنتشر حولها شائعات عن طبيب توفي في ظروف غامضة قبل سنوات في إحدى الليالي تظهر مريضة غريبة بملامح وابتسامة تثير الرعب ومنذ تلك اللحظة تبدأ أحداث غير طبيعية بالحدوث داخل العيادة بينما تشعر بيكا وأروم بأن ش…
داخل مدرسة «لاس إنسيناس» إحدى أكثر المدارس الخاصة نخبةً في إسبانيا حيث يدرس أبناء العائلات الثرية والنفوذ بعد انهيار مدرستهم الحكومية يحصل ثلاثة طلاب من عائلات متواضعة صامويل ونادية وكريستيان على فرصة للالتحاق بهذه المدرسة المرموقة لكن انتقالهم إلى عالم مختلف تمامًا عن حياتهم يجعلهم يواجهون صعوبة في التأقلم خصوصًا مع الفوارق الاجتماعية الكبيرة بينهم وبين زملائهم الأثرياء ومع دخول الطلاب الجدد إلى هذا العالم المليء با…
بادرو امرأة شابة تعيش في مومباي مع زوجها حمزة الذي يعاني من مشكلة في شرب الكحول ويتعامل معها بعنف بينما تتمسك هي بالأمل في أن يتغير ويصبح الزوج الذي حلمت به تحاول بادرو الصبر على حياتها الزوجية لكن مع تكرار تصرفاته وتجاوزاته تبدأ والدتها شمشون بالوقوف إلى جانبها ومساعدتها على مواجهة الوضع بدلًا من الاستمرار في تحمّله ومع وصول الأمور إلى مرحلة لا يمكن تجاهلها تقرر الأم وابنتها اتخاذ خطوات جريئة لاستعادة السيطرة على حي…
مجموعة من طالبات الجامعة برفقة أستاذتهن نورا يقررن قضاء فترة داخل مخبأ نووي مهجور لإجراء بحث يتعلق بدراساتهن بعد أن يقودهن حارس غامض إلى أعماق المخبأ يستعد الجميع للبقاء هناك لمدة أربع وعشرين ساعة بعيدًا عن العالم الخارجي ووسائل الاتصال لكن سرعان ما تتحول الرحلة البحثية إلى كابوس عندما تختفي طالبتان بشكل غامض وتبدأ المجموعة في البحث عنهما داخل الممرات المعزولة للمخبأ ومع اكتشافهن أنهن لسن وحدهن في هذا المكان تدرك نور…
شابة تُدعى أبورفا تعيش حياة هادئة وتستعد للزواج من حبيبها سيدهارث وفي طريقها لمفاجأته تتعرض رحلتها لحادث يقلب حياتها رأسًا على عقب تجد أبورفا نفسها محتجزة في منطقة نائية على يد عصابة إجرامية خطيرة بعيدًا عن أي مساعدة وتدرك سريعًا أن عليها الاعتماد على نفسها للخروج من هذا المأزق ومع حلول الليل تبدأ رحلة صعبة من الهروب والمطاردة بينما يحاول أفراد العصابة الوصول إليها وبين الخوف والضغط الشديد تضطر أبورفا إلى التفكير بسر…
❤40😍4🔥1🥰1
Showing the 12 most recent of 197 posts we hold for @NETFLIX23i. 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 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.
Domains linked from posts
2 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“مسلسلات & افلام” (@NETFLIX23i), 1,081,985 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/NETFLIX23i.
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.
