7 measurements spanning 15 days, net -40. 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 241–293 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
22 Aug 2026, 11:04
247
no change
21 Aug 2026, 10:23
247
-1
15 Aug 2026, 01:36
248
no change
15 Aug 2026, 01:07
248
+1
8 Aug 2026, 09:34
247
no change
7 Aug 2026, 23:23
247
-40
7 Aug 2026, 08:57
287
first reading
Engagement
20 posts held, back to 23 July 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
41.3%
avg views ÷ 247 subscribers
Avg views / post
102
1 post measured
Reaction rate
11.8%
reactions ÷ views · ER floor
Posts in window
1
of 20 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 3 August 2026
Posts held
20 (23 July 2025 – 3 August 2026)
Views total
102
Reactions total
12
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 09:34 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
Video runtime
1m 31s
Average length
1m 31s
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.
Reaction mix
275 reactions across 20 posts, in 12 distinct kinds. The most used accounts for 19.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
53
19.3%
custom 5251635527056132403
52
18.9%
custom 5251394751189518083
41
14.9%
custom 5251464686141999888
36
13.1%
❤
28
10.2%
custom 5350345742512823992
20
7.27%
👍
20
7.27%
custom 5397964556024688368
18
6.55%
☃
2
0.727%
🎄
2
0.727%
🦄
2
0.727%
👎
1
0.364%
Custom emoji. 5 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.
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 20 of the 20 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 275reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 23 July 2025 to 3 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.
Telegram Stars
Stars received
127
across the posts below
Posts paid on
7
of 20 we hold a reading for · 35%
Most on one post
101
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @papaya. 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 20 most recent posts we hold for this entry, published 23 July 2025 to 3 August 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.
Sergey (our CEO) sat down with Financial Tech Times to talk custody, dollarization, and why the best payment infrastructure is the one nobody notices.
Worth a read if you're thinking about stablecoin rails, bank adoption, or where recurring payments are headed: https://financialtechtimes.com/sergey-kravtsov-payment-infrastructure-for-financial-institutions/ @papaya
Papaya in Vietnam 🇻🇳
Sergey Kravtsov and Konstantin Zhurakovskii are at Da Nang Business, Finance & Technology Week (July 7–12).
Sergey speaks at the Vietnam Financial Forum - the flagship event of the week on recurring stablecoin payments as the missing infrastructure layer for the stablecoin economy.
July 9–10 · Ariyana Convention Centre, Da Nang
Sergey Kravtsov at Blockchain Community Day 2026:
“From One-Time Transfers to Recurring Payments: Why Settlement Cost Is the Real Bottleneck in Web3”
The talk walks through the four walls that kill crypto subscriptions and why the solution already existed in lending all along.
Collecting from a million streams costs the same as collecting from one.
youtu.be/Zc_f5mNQziQ
Today — Papaya at Blockchain Community Day 2026 🎤
Sergey Kravtsov speaks: "From One-Time Transfers to Recurring Payments: Why Settlement Cost Is the Real Bottleneck in Web3"
How 1M recurring payments settle in one transaction for under $0.01.
19:00 GMT+8 · Online · Free
luma.com/wupxaqku
Papaya at Digital Uzbekistan 🇺🇿
Our co-founder Sergey Kravtsov is speaking at the International PLUS-Forum Digital Uzbekistan — the largest digital finance event in Central Asia.
Topic: Recurring stablecoin payments — subscriptions and autopayments onchain.
May 19–20 | Tashkent | 2,500+ delegates from 36 countries
uz.plus-forum.com
Petr Kozyakov, Co-founder & CEO of Mercuryo, joins Papaya as angel investor and advisor.
Both Mercuryo co-founders now back Papaya.
Petr brings 15+ years in payments infrastructure — from cross-border settlement to scaling one of Europe’s leading crypto payment platforms.
Building recurring payment rails for the stablecoin economy 🌴
Decrypt asked our CEO Sergey Kravtsov to comment on the biggest DeFi exploit of the year — the $292M KelpDAO attack and the DeFi United recovery initiative.
https://decrypt.co/365431/aave-leads-defi-united-push-to-contain-292m-kelpdao-fallout
Papaya featured in Decrypt 🗞
Our co-founder shared his take on the SEC’s new pro-innovation stance and what it means for stablecoin infrastructure in the US.
https://decrypt.co/364720/sec-officials-push-us-crypto-ambitions-in-debut-podcast-episode
Major update just dropped. New UI, new contract, everything redesigned
papaya.finance/dca
papaya.finance/dca
papaya.finance/dca
Watch the walkthrough ↓
Greg Waisman, Co-founder & COO of Mercuryo, joins Papaya as angel investor and advisor.
Mercuryo powers 200+ apps, 10M+ users. Greg will help bring onchain DCA to wallets and build the fiat onramp flow.
Big step for Papaya 🚀
our co-founder Sergey Kravtsov is going live on Cryptic Talks in ~5 hours
topic: DeFi Infrastructure for Everyday Finance — lending, investing, and paying
alongside founders from URBNED and Spine
🕐 2pm UTC | 3pm CET
🔗 https://twitter.com/i/spaces/1RJjpzdAoXBKw
tune in and show some support
Dollar-Cost Averaging (DCA) = investing a fixed amount at regular intervals, regardless of price. No timing the market. Just consistency.
Historically, DCA during extreme fear earned 150-200% in 12 months.
Papaya DCA does this onchain: set a monthly USDC budget, protocol buys ETH for you every hour. Non-custodial, on Base.
17 updates shipped in 2 weeks. Building in public.
Try it → papaya.finance/dca
Showing the 12 most recent of 20 posts we hold for @papaya. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Declared links
3 URLs this entry has put in its own public description, shown exactly as written there. A declaration, not a verified association— we measured that the description contained this text, and nothing more. It is not a claim that this entry owns, runs or is connected to whatever the link resolves to; a description is text anyone controls, and anyone can put anyone else’s URL into it. 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 22 August 2026 — this
entry's latest reading, not the date you are reading this.
“Papaya” (@papaya), 247 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/papaya.
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.