Channel
@sucaibw
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Handles named that no longer answer · Cite this entry
3,890subscribers
-10 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1002616153800 |
|---|---|
| Type | Channel |
| Username | @sucaibw |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/sucaibw |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 08:06 | 3,890 | -11 |
| 8 Aug 2026, 02:58 | 3,901 | +1 |
| 7 Aug 2026, 06:02 | 3,900 | first reading |
9 posts held, back to 18 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 4 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.
| Window | Rolling 30 days · latest post in window 25 July 2026 |
|---|---|
| Posts held | 9 (18 April 2026 – 25 July 2026) |
| Views total | 169 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 05:58 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.
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.
😊😊😊😊 😀😀😀😀😀😀😀😀 😀 ：迪安工作室：人设套图证件绘画：点击文字跳转 😃 ： 亚洲女套图 😄 ：亚洲男套图 😄 ： 欧美女套图 😄 ：欧洲男套图 😄： 女私密套图 😀 ：迪安工作室： 😃😃😃😃😃😃😃😃 😃 ：翻译软件 😃 ：智能翻译 😃 ： 彩绘素描 😃 ：证件P图 😃 ： 批发飞机 😃 ：代写人设 😃 ： 代开会员 😃 ：海外素材 😃 ： 迪安工作室： 😄😃😄😃 : 💸 😃 ： 😀😀😃 …
#办公室 美式办公室
#看书 #阅读 这是一本名为《Boundaries》（《界限》）的书，作者是Dr. Henry Cloud和Dr. John Townsend。这本书的主题是帮助读者学习如何建立健康的界限，以便在生活中实现平衡和自我掌控。 书中讨论了什么时候应该说“是”，什么时候应该说“不是”，如何管理人际关系，以及怎样避免被别人过度使用或操控。
#美腿 #早晨 早晨的阳光轻轻洒进房间，唤醒的是身体，抚慰的是心灵。人生的新一天，从慵懒的舒适中开始，美好就在脚尖轻点的每一步里。
#洗澡 #洗头发 湿漉漉的头发，静悄悄的夜晚，此刻的我只属于自己
#做饭 #午餐 #晚餐 法式鹅肝切片
#聚会 #聚餐 #食物 #餐厅 今日品尝白酒。 图片中都是美国面孔，适合很多包装。
#蔬菜 #晚餐 #玉米 今晚吃得很简单随便弄了点蔬菜和玉米，这种清清淡淡的反而挺舒服的不会有负担
#办公室 #电脑 #咖啡 新的一天，从一杯好咖啡开始 ☕️
Showing the 9 most recent of 9 posts we hold for @sucaibw. 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 — 520,764 of 1,160,990entries 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 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.
@sucaibw 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.
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.
“素材包装人设套图 taotu” (@sucaibw), 3,890 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/sucaibw.
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.