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Channel
NOVELS | Crypto
@booksandcrypto
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
27,306subscribers
-1,500 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002459777637 |
|---|---|
| Type | Channel |
| Username | @booksandcrypto |
| Description | Your daily mix of Crypto insights and Web3 trends + curated Novel summaries for smart readers. Clean, simple, and valuable content only. #Crypto #Novels #Blockchain #Web3 |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 4 October 2026 |
| Measurements held | 35 |
| Confirmed unchanged | 1 time, most recently 4 October 2026 |
| On Telegram | t.me/booksandcrypto |
Topic
Education — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 43% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 4 Oct 2026, 15:00 | 27,306 | -217 |
| 26 Sept 2026, 10:59 | 27,523 | -191 |
| 19 Sept 2026, 11:00 | 27,714 | -50 |
| 17 Sept 2026, 03:16 | 27,764 | -41 |
| 15 Sept 2026, 05:18 | 27,805 | -20 |
| 13 Sept 2026, 16:39 | 27,825 | -40 |
| 11 Sept 2026, 23:59 | 27,865 | -57 |
| 9 Sept 2026, 15:40 | 27,922 | -88 |
| 6 Sept 2026, 06:15 | 28,010 | -56 |
| 3 Sept 2026, 22:18 | 28,066 | -35 |
| 2 Sept 2026, 15:52 | 28,101 | -32 |
| 1 Sept 2026, 14:26 | 28,133 | -31 |
| 31 Aug 2026, 12:28 | 28,164 | -20 |
| 30 Aug 2026, 12:58 | 28,184 | -33 |
| 29 Aug 2026, 13:25 | 28,217 | -29 |
| 28 Aug 2026, 15:11 | 28,246 | -21 |
| 27 Aug 2026, 12:45 | 28,267 | -27 |
| 26 Aug 2026, 09:27 | 28,294 | -30 |
| 25 Aug 2026, 08:42 | 28,324 | -29 |
| 24 Aug 2026, 09:28 | 28,353 | first reading |
Engagement
19 posts held, back to 28 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 87 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.51%
- avg views ÷ 27,306 subscribers
- Avg views / post
- 412
- 4 posts measured
- Reaction rate
- 0.189%
- reactions ÷ views · ER floor
- Posts in window
- 4
- of 19 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. It is computed over the 1 of 4 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 7 October 2026 |
|---|---|
| Posts held | 19 (28 April 2026 – 7 October 2026) |
| Views total | 1,648 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Oct 2026, 18:03 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
- 38
- Links
- 24
Lifetime counters from Telegram’s own channel header, read 8 October 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
29 reactions across 9 posts, in 3 distinct kinds. The most used accounts for 89.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 26 | 89.7% | |
| 👍 | 2 | 6.90% | |
| 🔥 | 1 | 3.45% |
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 10 of the 19 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 29 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 28 April 2026 to 7 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.
Recent posts
📚 Book List 1. Contentious — Marie Force 2. AI Applications in Industry — Wai Yie Leong 3. Behind the Castle Walls: My Thirty Years at the Happiest Place on Earth — Bob Chapek 4. Sexting My Bratva Daddies — Sofia T Summers 5. Such a Good Man — AJ Campbell 6. The CEO: The Role, the Reality, the Responsibility — Nitin Nohria 7. Trust Fall — Lynn Painter 👉 click here
- Psychopathia Sexualis — Richard von Krafft-Ebing (1886) — Public Domain - The Interpretation of Dreams — Sigmund Freud (1899) — Public Domain - Sex and Character — Otto Weininger (1903) — Public Domain - Come as You Are — Emily Nagoski — All Rights Reserved — Respect the Author’s Copyright - The Psychology of Women — Margaret W. Matlin — All Rights Reserved — Respect the Author’s Copyright 👉 click here
❤1
📚 Book List 1. Emergence — Bob Burgin 2. Situated — Angela Duckworth 3. Stay Calm: Learn to Embrace Uncertainty in Investing and Life — David Booth 4. The New Rules of AI Search — Crystal Carter 5. The Troll — Maria Frankland 6. Your Normal Mind — John Hannan 👉 click here 🚀 Let's go together: GOLDEN PRECISION drops real-time market analysis + trading strategies—spot the setup before you place a trade 🔍🎯 | InsideAd
📚 6 BOOKS TO UPGRADE YOUR BUSINESS & MINDSET Looking to improve your business knowledge, leadership, creativity, and understanding of the modern workplace? 🚀 Here are 6 valuable books worth adding to your reading list: 📘 1. AI at Work ✍️ James Poulter 🤖 Learn how AI is transforming organizations, jobs, leadership, and the future of work. 📕 2. Business Book 🏢 DK Publishing 💼 A visual guide to essential business co…
Posted without readable text
📚 Proper Book List 1. Common Stocks and Uncommon Profits — Philip Fisher 2. Crushing It! — Gary Vaynerchuk 3. How to Write a Business Plan 4. The Billion Dollar Secret — Rafael Badziag 5. The Power of Your Subconscious Mind — Joseph Murphy 6. Think and Grow Rich — Napoleon Hill 👉 Click here to get all books
📚 17 UNIQUE BOOKS COLLECTION 💰 MONEY & WEALTH 1. The Millionaire Next Door 2. Secrets of the Millionaire Mind 3. FAKE: Fake Money, Fake Teachers, Fake Assets 4. Learn to Earn 🧠 MINDSET & PSYCHOLOGY 5. How Successful People Think 6. The Power of Your Subconscious Mind 7. Dark Psychology 8. The Mind of the Buyer 💼 BUSINESS & ENTREPRENEURSHIP 9. How to Write a Business Plan 10. The 4-Hour Workweek ×4 📈 SALES & NEGOTIATI…
❤1
Fooled by Randomness — Nassim Nicholas Taleb - Art of Man Making (Vol. 1) — Swami Chinmayananda - Elon Musk — Walter - Incerto 4-Book Bundle: Fooled by Randomness(Duplicate Copy) — Nassim Nicholas Taleb - Outlive (German Edition) — Peter Attia - Personality Development — Swami Vivekananda - The Brothers Karamazov: A New Translation — Michael R. Katz - The Complete Book of Yoga — Swami Vivekananda click here :…
📚 Bestselling Books Collection (2023–2025) ✅ Fourth Wing (Special Edition) – Rebecca Yarros ✅ Iron Flame – Rebecca Yarros ✅ Memory Rescue – Daniel G. Amen ✅ Onyx Storm (The Empyrean #3) – Rebecca Yarros ✅ Sources of Power: How People Make Decisions – Gary Klein ✅ StrengthsFinder 2.0 – Tom Rath ✅ The Body Keeps the Score – Bessel van der Kolk ✅ The Let Them Theory – Mel Robbins ✅ The Mountain Is You – Brianna Wiest ✅…
❤2
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Showing the 12 most recent of 19 posts we hold for @booksandcrypto. 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
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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 4 October 2026 — this entry's latest reading, not the date you are reading this.
“NOVELS | Crypto” (@booksandcrypto), 27,306 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/booksandcrypto.
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.