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Channel
@WebcamDictionary
On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
5,893subscribers
+175 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001586644292 |
|---|---|
| Type | Channel |
| Username | @WebcamDictionary |
| Created | Between 1 August 2021 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 13 November 2026 |
| Measurements held | 26 |
| Confirmed unchanged | 1 time, most recently 13 November 2026 |
| On Telegram | t.me/WebcamDictionary |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 91% 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.
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 in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. 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 |
|---|---|---|---|
| @AuroraWeb/90023 Jun 2026, 10:00 UTC | @WebcamDictionary/341 · this entry29 Jun 2026, 07:02 UTC | 1.00 | 6 days |
| @AuroraWeb/90414 Jul 2026, 13:10 UTC | @WebcamDictionary/345 · this entry19 Jul 2026, 09:31 UTC | 1.00 | 5 days |
| @WebcamDictionary/347 · this entry26 Jul 2026, 15:59 UTC | @AuroraWeb/90931 Jul 2026, 07:59 UTC | 1.00 | 5 days |
| @AuroraWeb/92116 Sept 2026, 08:59 UTC | @WebcamDictionary/373 · this entry28 Sept 2026, 12:59 UTC | 1.00 | 12 days |
| @WebcamDictionary/376 · this entry19 Oct 2026, 08:01 UTC | @AuroraWeb/93226 Oct 2026, 09:03 UTC | 1.00 | 7 days |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @AuroraWeb | 5 (5/5 hand-verifiable sample passed) | 1.00 | 6 days | @AuroraWeb (3–2) |
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. 1 of the 3 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 27 comparable posts for this entry, running 1 April 2026 to 27 October 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.
Of the group of 2 channels, the one whose matching posts we hold earliest is @AuroraWeb. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, last confirmed 11 November 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 is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Nov 2026, 10:00 | 5,893 | +15 |
| 9 Nov 2026, 07:46 | 5,878 | +7 |
| 5 Nov 2026, 17:45 | 5,871 | +16 |
| 3 Nov 2026, 03:18 | 5,855 | -1 |
| 31 Oct 2026, 08:35 | 5,856 | +6 |
| 28 Oct 2026, 16:50 | 5,850 | -1 |
| 25 Oct 2026, 12:18 | 5,851 | +10 |
| 22 Oct 2026, 09:40 | 5,841 | -3 |
| 18 Oct 2026, 20:38 | 5,844 | +8 |
| 15 Oct 2026, 23:58 | 5,836 | -4 |
| 13 Oct 2026, 01:21 | 5,840 | -7 |
| 6 Oct 2026, 20:56 | 5,847 | -9 |
| 29 Sept 2026, 23:41 | 5,856 | -7 |
| 19 Sept 2026, 15:20 | 5,863 | +4 |
| 15 Sept 2026, 05:17 | 5,859 | +1 |
| 11 Sept 2026, 08:38 | 5,858 | -9 |
| 7 Sept 2026, 00:41 | 5,867 | +7 |
| 2 Sept 2026, 11:23 | 5,860 | +12 |
| 30 Aug 2026, 13:07 | 5,848 | +82 |
| 27 Aug 2026, 07:35 | 5,766 | first reading |
30 posts held, back to 1 April 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 9 pages of 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.
| Window | Rolling 30 days · latest post in window 31 October 2026 |
|---|---|
| Posts held | 30 (1 April 2026 – 31 October 2026) |
| Views total | 5,485 |
| Reactions total | 70 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 4 Nov 2026, 16:01 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.
787 reactions across 30 posts, in 18 distinct kinds. The most used accounts for 56.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 446 | 56.7% | |
| 🔥 | 143 | 18.2% | |
| ❤🔥 | 39 | 4.96% | |
| 👏 | 37 | 4.70% | |
| 👍 | 25 | 3.18% | |
| 😈 | 24 | 3.05% | |
| 🙏 | 16 | 2.03% | |
| 🤣 | 13 | 1.65% | |
| 🐳 | 12 | 1.52% | |
| 🍓 | 10 | 1.27% | |
| 🍌 | 5 | 0.635% | |
| 🍾 | 4 | 0.508% | |
| 🕊 | 3 | 0.381% | |
| 😍 | 3 | 0.381% | |
| 🥰 | 3 | 0.381% | |
| 💯 | 2 | 0.254% | |
| 🌭 | 1 | 0.127% | |
| 😱 | 1 | 0.127% |
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 30 of the 30 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 787 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 30 most recent posts we hold, published 1 April 2026 to 31 October 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’s own ‘edited’ marker: 1 of 5 posts held from the last 30 days (20.0%) 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).
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Как сформулировано твоё тип-меню? Show feet. Pinch nipples. I love you. You look amazing today. Одни слова мембер пролистывает. За другие платит. Разница не в цене, а в том, под какую задачу собрано меню. Взяла три реальных тип-меню со Stripchat. Одно собрано под трафик. Второе под чек. Третье просто прайс. Угадаешь, где какое? 👉Игра: три меню Слова решают и в диалогах. Модель на Chaturbate + MFC годами теряла ден…
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Достаём твои сокровища из морских пучин - выгодно, удобно. 🤩🌊 Быть Сиреной — это не только сводить с ума одним взглядом и собирать сокровища со всего моря. Это ещё и уметь быстро, выгодно и без нервов забирать своё. Потому что твои деньги — не затонувший клад. В подводном царстве Manytips магия работает с 2022 года: @aurora_8888_bot поможет легко и удобно вывести заработанное с рабочих вебкам сайтов 🤩 Что умеет …
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🌟 Самые ПОЗИТИВНЫЕ эмоции на английском. Прошлый пост о негативных эмоциях набрал более 50 реакций! Выполняем обещанное и рассказываем как передать состояние абсолютного блаженства. Эмоциональные оттенки, которыми необходимо владеть не только в лексиконе, но и на практике 🌟 🌟 EXCITEMENT — восторг, приятное волнение, предвкушение чего-то крутого. excited — восторженный, ждущий с нетерпением exciting — захватывающий t…
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$7700 за месяц на Stripchat - это реальность КАК? Здесь разбор: что делали и что повлияло 👉Кейс целиком В твоей комнате сидят шесть типов мемберов. Пятерых ты, скорее всего, не различаешь. Карта мемберов + разбор фетишистов - кто из них платит, а кто занимает место. Разборы моделей-подписчиц продолжаются: по шагам, где именно теряются деньги и как начать их зарабатывать. Подпишись 👇
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👠 Виды обуви на английском. Пост-словарь, в котором собраны практически ВСЕ виды обуви, о которых только может спросить мембер. Shoes — обувь Boots — все ботинки Flats — сокращенное название для всей обуви на плоской подошве Heels — общее название для всей обуви на каблуке Sole — подошва Insole — стелька Heel — каблук Laces или Shoelaces — шнурки Tongue — язычок Upper — верхняя часть обуви Toe box — мыс или носок об…
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✌️ Язык тела: фразеологизмы, которые точно стоит использовать. Некоторые любопытные "телесные" фразы для красоты речи. 👁 Глаза (Eyes) ✏️To keep an eye on — приглядывать за кем-то/чем-то. Please keep an eye on my goal. — Пригляди за моей целью. ✏️To turn a blind eye — закрывать глаза на что-то, игнорировать. I had to turn a blind eye to it. — Мне пришло закрыть на это глаза. ✏️To see eye to eye (with someone) — схо…
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🎣 Заманухи для мужчин: на что они чаще всего клюют? Заигрывающие фразы, чтобы зацепить с первого диалога. 🌸Мужчины чаще отвечают на сообщения, которые: ✔️создают ощущение личного внимания (Я заметила тебя — I noticed you); ✔️вызывают желание оправдать ожидания (Я чувствую, что ты другой — I have a feeling you're different); ✔️предлагают маленький вызов (Удиви меня, убеди меня — Surprise me, Convince me); ✔️оставляют…
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🖕Обидные клички для раба. Эмоциональное доминирование. Как наказывать раба мы разбирали здесь в двух частях тут (психологически) и тут (физически). Рассказываем, как назвать раба так, чтобы ему понравилось (и чтобы было обидно). 👮♀️ БАЗОВЫЕ ОБОЗНАЧЕНИЯ. Sub (от submissive) — покорный, нижний Slave — раб/рабыня Bottom — нижний (принимающий действия в сессии) Pet — питомец (для анималистических практик/petplay) 🤩 …
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😳 7 идей для cuckold-игры. Источник картинки - etymonline.com Лови СЕМЬ (!) сценариев, чтобы рогоносец точно разорился на щедрые чаевые! 🤩 Doctor's Examination. Осмотр у врача. Plot/Сюжет. Ты пришла на осмотр. Что-то пошло не так, и вы занялись горячим сексом. Бонусом: сюда можно втиснуть любимый кинк мема. Например, беременность или, допустим, латекс (застряла в латексном костюме, потребовалась помощь). - The doc…
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Showing the 12 most recent of 30 posts we hold for @WebcamDictionary. 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.
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.
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.
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.
This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 13 November 2026 — this entry's latest reading, not the date you are reading this.
“WebcamDictionary” (@WebcamDictionary), 5,893 subscribers as measured 13 November 2026. Telegram Register, tgregister.com/channel/WebcamDictionary.
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.