😀😀 ⭐ 老师:#冰冰 🏠 地点:佛山禅城 ⭐ 账号:@bingTvTqi 🚀 频道:https://t.me/uu77qi 💰 价格:600P 1200PP 🏷️ 标签:#嫩妹 #舌吻 ❤️ 很年轻的一个妹妹,嫩得可以掐出水,还有好多好多服装可以选
❤2

Channel
@ecdiary003
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
16,579subscribers
+5,131 since we began measuring on 19 September 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003866919907 |
|---|---|
| Type | Channel |
| Username | @ecdiary003 |
| Description | 上榜&推广 @eatc003 聊天群 @ecchat004 备用群 @fucksenseidiary 报告厅 @ecreport001 |
| Created | Between 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 19 September 2026 |
| Last confirmed live | 5 November 2026 |
| Measurements held | 27 |
| Confirmed unchanged | 1 time, most recently 5 November 2026 |
| On Telegram | t.me/ecdiary003 |
Other / unclassifiable — 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 3 October 2026 and assigned it the closest of 31 fixed categories, at 83% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Nov 2026, 01:39 | 16,579 | +31 |
| 3 Nov 2026, 22:56 | 16,548 | +63 |
| 2 Nov 2026, 23:51 | 16,485 | +120 |
| 1 Nov 2026, 23:59 | 16,365 | +47 |
| 31 Oct 2026, 21:35 | 16,318 | +62 |
| 30 Oct 2026, 20:50 | 16,256 | +73 |
| 29 Oct 2026, 18:56 | 16,183 | +145 |
| 28 Oct 2026, 16:11 | 16,038 | +129 |
| 27 Oct 2026, 17:39 | 15,909 | +162 |
| 26 Oct 2026, 18:20 | 15,747 | +170 |
| 25 Oct 2026, 17:46 | 15,577 | +108 |
| 24 Oct 2026, 20:54 | 15,469 | +208 |
| 23 Oct 2026, 17:50 | 15,261 | +230 |
| 22 Oct 2026, 17:30 | 15,031 | +273 |
| 21 Oct 2026, 14:55 | 14,758 | +118 |
| 20 Oct 2026, 09:17 | 14,640 | +95 |
| 19 Oct 2026, 10:55 | 14,545 | +57 |
| 18 Oct 2026, 10:21 | 14,488 | +30 |
| 17 Oct 2026, 13:07 | 14,458 | +25 |
| 16 Oct 2026, 10:37 | 14,433 | first reading |
18 posts held, back to 17 September 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 7 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. It is computed over the 12 of 14 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 November 2026 |
|---|---|
| Posts held | 18 (17 September 2026 – 5 November 2026) |
| Views total | 83,331 |
| Reactions total | 39 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Nov 2026, 16:30 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 5 November 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.
Measured directly from 6 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.
51 reactions across 16 posts, in 5 distinct kinds. The most used accounts for 82.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 42 | 82.4% | |
| 👍 | 6 | 11.8% | |
| 👏 | 1 | 1.96% | |
| 🤔 | 1 | 1.96% | |
| 🥰 | 1 | 1.96% |
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 18 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 51 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 17 September 2026 to 5 November 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: 4 of 14 posts held from the last 30 days (28.6%) 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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❤2
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❤2
Posted without readable text
❤4
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❤1👍1
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👍1
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❤1🤔1
Posted without readable text
❤2
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❤8👍3
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❤1
综合考虑,课表换回上个月的课表咯😜😜 联系 @ruoni038
❤3
Showing the 12 most recent of 18 posts we hold for @ecdiary003. 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
Named by 4 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.
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 5 November 2026 — this entry's latest reading, not the date you are reading this.
“广州&佛山·EC昆记” (@ecdiary003), 16,579 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/ecdiary003.
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.