Channel
@taotu_kb4
On this record: Topic · Observations · Growth · Engagement · Posts · Citations · Handles named that no longer answer · Cite this entry
1,881subscribers
-215 since we began measuring on 13 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1003534269219 |
|---|---|
| Type | Channel |
| Username | @taotu_kb4 |
| Created | Between 1 December 2025 and 31 May 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 13 August 2026 |
| Last confirmed live | 2 September 2026 |
| Measurements held | 8 |
| Confirmed unchanged | 1 time, most recently 2 September 2026 |
| On Telegram | t.me/taotu_kb4 |
Hacking & security — 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 15 August 2026 and assigned it the closest of 31 fixed categories, at 38% 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.
1.9 average views per post against 1,881 subscribers — an engagement rate of 0.101%. Across the 1,129 registered channels in the same cohort — 1,002–3,162 subscribers, posting mainly in Chinese — the middle half sit between 4.39% and 30.1%, with a median of 12.5%.
| Window | 30 days (3 August 2026 – 2 September 2026) |
|---|---|
| Posts measured | 20 of 20 published in the window (20 exact, 0 rounded by Telegram) |
| Views totalled | 38 |
| Mature posts only | 0.16% over 8 posts read at least 24h after publication |
| Subscribers | 1,881 measured 2 September 2026 |
| Cohort | b1000:zho · 1,129 channels · p10 1.24% · p25 4.39% · p50 12.5% · p75 30.1% · p90 59.2% |
| Position in cohort | 0.798th percentile · 1/125 the cohort median |
| Uncertainty | ±0.153% of the figure, from Telegram’s rounding |
| Post language | Chinese · 100.0% of the window’s posts |
When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_low, last confirmed 2 September 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 2 Sept 2026, 12:45 | 1,881 | -51 |
| 30 Aug 2026, 04:28 | 1,932 | -101 |
| 27 Aug 2026, 00:38 | 2,033 | -15 |
| 23 Aug 2026, 18:27 | 2,048 | -15 |
| 20 Aug 2026, 00:51 | 2,063 | -11 |
| 16 Aug 2026, 18:23 | 2,074 | -22 |
| 13 Aug 2026, 08:47 | 2,096 | no change |
| 13 Aug 2026, 07:33 | 2,096 | first reading |
20 posts held, back to 8 August 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 1 page 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 13 August 2026 |
|---|---|
| Posts held | 20 (8 August 2026 – 13 August 2026) |
| Views total | 38 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Aug 2026, 07:33 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.
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编号UK110 生活日常🌟🌟🌟🌟 #英国 型男 正装 商务 富二代 自拍多 生活场景丰富 自拍多 聚会 旅游 风景 生活日常 照片328张 视屏66个（带IG）
编号UK120 生活日常🌟🌟🌟🌟 #英国 职业 医生 正装 宝爸 家人合照 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片434张 视屏11个（带IG）
编号UK119 生活日常🌟🌟🌟🌟 #法国 定居 #迪拜 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片364张 视屏35个（带IG）
编号UK118 生活日常🌟🌟🌟🌟 #西班牙 宝爸 正装 家人合照 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片552张 视屏暂无（带IG）
编号UK117 生活日常🌟🌟🌟🌟 #西班牙 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片626张 视屏5个（带IG）
编号UK116 生活日常🌟🌟🌟🌟 #法国 职业 服装店老板 正装 商务 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片81张 视屏1个（带IG）
编号UK115 生活日常🌟🌟🌟🌟 #西班牙 正装 商务 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片1242张 视屏20个（带IG）
编号UK114 生活日常🌟🌟🌟🌟 #法国 健身 肌肉 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 《证件照》 照片514张 视屏36个（带IG）
编号UK113 生活日常🌟🌟🌟🌟 #德国 肌肉 正装 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 照片689张 视屏70个（带IG）
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编号UK111 生活日常🌟🌟🌟🌟 #美国 职业 空少 正装 商务 自拍多 生活场景丰富 聚会 旅游 风景 生活日常 《合适虚拟视屏》 照片634张 视屏16个（带IG）
Showing the 12 most recent of 20 posts we hold for @taotu_kb4. 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 — 1,422,314 of 1,629,808 entries 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.
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.
@taotu_kb4 named 3 handles 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.
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 2 September 2026 — this entry's latest reading, not the date you are reading this.
“人设套图-三方素材-欧美男-人物包装” (@taotu_kb4), 1,881 subscribers as measured 2 September 2026. Telegram Register, tgregister.com/channel/taotu_kb4.
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.