✅ Baм дocтyпнo 5 зaдaний! 👉 Oткликнyтьcя 👈 Oткpытыe зaдaния: 🔸 Пepeпeчaтaть тeкcт – 2700₽ 🔸 Haлoжить cyбтитpы – 2300₽ 🔸 Пocтaвить лaйки – 3200₽/дeнь 🔸 Ocтaвить oтзывы – 3700₽/дeнь Eщё 30 aктyaльныx зaдaний TУT 👈
❤1

Channel
@English_Books_TG
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
46,224subscribers
-1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001295424173 |
|---|---|
| Type | Channel |
| Username | @English_Books_TG |
| Description | Наш бот - @Lexic_ON_bot Главный админ (по рекламе) - @vlada_storiesmeiker Купить рекламу: https://telega.in/c/English_Books_TG Менеджеры - @Manag_VladaMedia |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 2 times, most recently 12 August 2026 |
| On Telegram | t.me/English_Books_TG |
Education — 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 why it has no browse page of its own yet.
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 word for word on 2 other registered channels. 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 |
|---|---|---|---|
| @EngWithSongs/659827 Jul 2026, 15:20 UTC | @English_Books_TG/5918 · this entry27 Jul 2026, 15:20 UTC | 1.00 | under a minute |
| @EngWithSongs/659927 Jul 2026, 16:20 UTC | @English_Books_TG/5919 · this entry27 Jul 2026, 16:20 UTC | 1.00 | under a minute |
| @EngWithSongs/66071 Aug 2026, 10:40 UTC | @English_Books_TG/5925 · this entry1 Aug 2026, 10:40 UTC | 1.00 | under a minute |
| @EngWithSongs/66112 Aug 2026, 16:30 UTC | @English_Books_TG/5929 · this entry2 Aug 2026, 16:30 UTC | 1.00 | under a minute |
| @EngWithSongs/66196 Aug 2026, 06:00 UTC | @English_Books_TG/5935 · this entry6 Aug 2026, 06:00 UTC | 1.00 | under a minute |
| @EnglishByEar/950127 Jul 2026, 15:20 UTC | @English_Books_TG/5918 · this entry27 Jul 2026, 15:20 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @EngWithSongs | 5 (5/5 hand-verifiable sample passed) | 1.00 | under a minute | this entry (5–0) |
| @EnglishByEar | 5 (5/5 hand-verifiable sample passed) | 1.00 | under a minute | this entry (5–0) |
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 0 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 16 comparable posts for this entry, running 23 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.
Across the whole group of 3, the earliest publisher we hold is @EnglishByEar. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, 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.
This channel’s posts match, word for word or near enough, posts on 2 other registered channels, 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 14:44 | 46,224 | -12 |
| 10 Aug 2026, 15:56 | 46,236 | +19 |
| 8 Aug 2026, 15:06 | 46,217 | -1 |
| 7 Aug 2026, 13:30 | 46,218 | -7 |
| 6 Aug 2026, 20:45 | 46,225 | no change |
| 6 Aug 2026, 20:38 | 46,225 | first reading |
21 posts held, back to 23 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 19 pagesof 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. It is computed over the 16 of 21 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 10 August 2026 |
|---|---|
| Posts held | 21 (23 July 2026 – 10 August 2026) |
| Views total | 57,920 |
| Reactions total | 73 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 20:00 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.
Lifetime counters from Telegram’s own channel header, read 12 August 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.
Measured directly from 2 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.
73 reactions across 15 posts, in 3 distinct kinds. The most used accounts for 67.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 49 | 67.1% | |
| 👍 | 22 | 30.1% | |
| 🔥 | 2 | 2.74% |
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 16 of the 21 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 73reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 23 July 2026 to 10 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.
✅ Baм дocтyпнo 5 зaдaний! 👉 Oткликнyтьcя 👈 Oткpытыe зaдaния: 🔸 Пepeпeчaтaть тeкcт – 2700₽ 🔸 Haлoжить cyбтитpы – 2300₽ 🔸 Пocтaвить лaйки – 3200₽/дeнь 🔸 Ocтaвить oтзывы – 3700₽/дeнь Eщё 30 aктyaльныx зaдaний TУT 👈
❤1
👆🏻Все успели зарегистрироваться на бесплатный марафон по английскому?👆🏻
Изучаете английский? Или преподаёте его? Друзья, мы объединили каналы лучших экспертов, которые делятся готовыми интерактивами, тестами и разборами живой лексики английского языка. Вам больше не нужно искать контент по всему интернету 💕 Что внутри 👇 🔘Разбор живого языка по фильмам и сериалам 🔘Полезные тесты, викторины и понятная грамматика 🔘Советы от экспертов и подготовка к экзаменам и олимпиадам без стресса …
❤4
📗 The Murders in the Rue Morgue 👤 Edgar Allan Poe 📊#Intermediate 📖 Description: C. Auguste Dupin is a man in Paris who solves the mysterious brutal murder of two women. Numerous witnesses heard a suspect, though no one agrees on what language was spoken. At the murder scene, Dupin finds a hair that does not appear to be human. 📓 Read book
👍3
📗 A Nose for a Story 👤 Frank Brennan 📊#Elementary 📖 Description: The taxi driver noticed that the lady in the back seat was frowning from the unpleasant smell and clearly barely keeping her expensive lunch inside. The driver asked if she was all right. He explained that it was the smell of the sewerage. He said that in the place they were going to there were no sewer lines and the lady had no need to worry.kris 📓 …
❤4
📗 They Came to Baghdad 👤 Agatha Christie 📊#Intermediate 📖 Description: Lady Agatha Christie knows East very well. She worked as an archaeologist when she and her husband were in Baghdad. This experience she used to write this book. The novel belongs to the spy fiction genre, which also contains politics, criminal and a love story. 📓 Read book
❤2👍1
Знаешь грамматику, понимаешь на слух, а говорить не можешь? Talksy – бот для разговорной практики. Говоришь голосом, ИИ отвечает и разбирает ошибки. → никаких тестов, только живой разговор → отчёты каждые 2 недели → задания и фразы каждый день Начни первый разговор 👇 @TalksyEnglishBot
❤2
📗 The Pigeon 👤 Eona Macnicol 📊#Elementary 📖 Description: Strong people can easily take care of themselves. But what can the weak people do? Jan found this bird at the window of his bedroom, on a small ledge outside. The pigeon was wounded. It could not fly and clearly had to die. Ella offered Jan to give the bird to a person who had her own dovecote, but Jan refused. This is his bird and he must take care of it by …
❤4👍2
Вас пригласили в закрытый канал по английскому
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⚡️Нейросети уже заменяют носителей языка. В Telegram быстро набирает популярность ИИ-девушка Chatty, с которой можно голосом практиковать живой разговорный английский и ещё 12 языков на основе новейших моделей искусственного интеллекта. Попробовать можно бесплатно. 🇬🇧 Английский: @ChattyEnglishBot 🇩🇪 Немецкий: @ChattyGermanBot 🇪🇸 Испанский: @ChattySpanishBot 🇫🇷 Французский: @ChattyFrenchBot 🇮🇹 Итальянский: @ChattyI…
📗 Hunted down 👤 Charles Dickens 📊#Elementary 📖 Description: This is one of the detective stories of the famous English writer Charles Dickens. The main character is a smart and attentive man named Sampson. The writer once again demonstrates his talent: he perfectly describes the character and psychology of the people's behavior. Charles Dickens also gives a vivid imagery of the society of his time. The story is dyn…
❤14👍3
I have never ____ a dog Я никогда не видел собаку
Showing the 12 most recent of 21 posts we hold for @English_Books_TG. 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 — 227,285 of 1,151,006entries 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.
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.
Named by 3 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.
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.
@English_Books_TG 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.
References a handle that is not a live channel — we have no record it ever was one.
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“Книги на Английском | Аудиокниги” (@English_Books_TG), 46,224 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/English_Books_TG.
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.