#冰冰 ✅视频认证 (点击查看) #普陀 绿地世纪城 >> 📍看距离 联系她: @冰冰 (报喜茶进会员群) #千元档 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】

Channel
上海【喜茶】榜单 (中转)
@xichalsshzz
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
10,304subscribers
+1,002 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002260323549 |
|---|---|
| Type | Channel |
| Username | @xichalsshzz |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 17 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/xichalsshzz |
Topic
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 68% 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 |
|---|---|---|
| 17 Sept 2026, 23:21 | 10,304 | +92 |
| 15 Sept 2026, 18:21 | 10,212 | +31 |
| 14 Sept 2026, 05:19 | 10,181 | +21 |
| 12 Sept 2026, 12:00 | 10,160 | +50 |
| 10 Sept 2026, 08:17 | 10,110 | +151 |
| 4 Sept 2026, 22:21 | 9,959 | +71 |
| 1 Sept 2026, 16:03 | 9,888 | +67 |
| 29 Aug 2026, 23:35 | 9,821 | +58 |
| 27 Aug 2026, 09:05 | 9,763 | +53 |
| 24 Aug 2026, 18:14 | 9,710 | +81 |
| 21 Aug 2026, 10:14 | 9,629 | +77 |
| 18 Aug 2026, 16:43 | 9,552 | +58 |
| 15 Aug 2026, 16:35 | 9,494 | +81 |
| 12 Aug 2026, 08:43 | 9,413 | +46 |
| 9 Aug 2026, 18:13 | 9,367 | +65 |
| 6 Aug 2026, 22:52 | 9,302 | no change |
| 6 Aug 2026, 20:17 | 9,302 | first reading |
Engagement
87 posts held, back to 6 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 34 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.278%
- avg views ÷ 10,304 subscribers
- Avg views / post
- 28.7
- 3 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 3
- of 87 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.
| Window | Rolling 30 days · latest post in window 29 August 2026 |
|---|---|
| Posts held | 87 (6 August 2026 – 29 August 2026) |
| Views total | 86 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 29 Aug 2026, 05:15 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
- 6m 54s
- Average length
- 7s
Measured directly from 59 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.
Reaction mix
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 100.0% |
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 2 of the 87 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 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 87 most recent posts we hold, published 6 August 2026 to 29 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.
Recent posts
#点点 ✅视频认证 (点击查看) #浦东 张江 >> 📍看距离 联系她: @点点 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】 【反馈1】【反馈2】【反馈3】 【反馈4】【反馈5】【反馈6】 【反馈7】【反馈8】【反馈9】
#慧慧 ✅真人认证 (点击查看) #宝山 三花现代城 >> 📍看距离 联系她: @慧慧 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#子萱 ✅视频认证 (点击查看) #普陀 真如 >> 📍看距离 联系她: @子萱 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#小蛋挞 ✅真人认证 (点击查看) #闵行 吴泾 >> 📍看距离 联系她: @小蛋挞 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#小欲 ✅真人认证 (点击查看) #普陀 宁川路 >> 📍看距离 联系她: @小欲 (报喜茶进会员群) #千元档 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#小樱小熊二次元双飞姐妹花 ✅真人认证 (点击查看) #长宁 通斜小区 >> 📍看距离 联系她: @小樱小熊二次元双飞姐妹花 (报喜茶进会员群) >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#夕颜 ✅视频认证 (点击查看) #闵行 爱琴海购物中心 >> 📍看距离 联系她: @夕颜 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#茶冻冻 ✅视频认证 (点击查看) #浦东 潍坊二村 >> 📍看距离 联系她: @茶冻冻 (报喜茶进会员群) #千元档 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】 【反馈1】【反馈2】【反馈3】 【反馈4】【反馈5】
#萱萱 ✅真人认证 (点击查看) #普陀 真如环宇城 >> 📍看距离 联系她: @萱萱 (报喜茶进会员群) #千元档 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
#乐乐 ✅视频认证 (点击查看) #浦东 康桥 >> 📍看距离 联系她: @乐乐 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】 【反馈1】【反馈2】【反馈3】
#甜甜 ✅视频认证 (点击查看) #闵行 万兆家园 >> 📍看距离 联系她: @甜甜 (报喜茶进会员群) #千元内 >> 更多标签 详细资料或评论 >> ⛺️喜茶总榜 导航 | 写报告 | 🧧福利群 | 推荐榜 👉 一键关注【喜茶上海频道】
Showing the 12 most recent of 87 posts we hold for @xichalsshzz. 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.
Mentions
Named by 36 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
@heytealist · 9,0333 posts浦东金桥露露真实(白🐅)
@jinqiaolulu386 · 1,0722 posts浦东小骚货的福利频道
@saosaoXZMLY · 712 posts欣欣后宫
@wxinh456 · 1972 posts浦东三林笑笑
@xiaoxiao5672 · 6,8992 posts樱桃朋友圈
@bxm2233 · 3751 post浦东三林迪迪频道
@didishanghai · 761 post🍂静香
@jingxia86 · 1411 post小y的日常
@Lbs642497 · 831 post泪泪的小窝
@leilei111111 · 1221 post灵灵💓心动小窝🏠
@linglingZLJ · 2751 post夕颜
@maoer10 · 1611 post沐沐的新空间
@mumush2 · 1391 post台湾奶茶精品屋
@naichameimei01 · 2531 post奶艾斯大白兔
@naisit1 · 7381 post琪琪的小窝
@qi0826 · 2221 post十一的小满屋
@shiyi_s1 · 2931 post韩冰雨的快乐小屋🛖
@tiantian990909 · 3411 post普陀环球港f天然大奶北方有佳人
@ttyyg1253 · 3,4261 post馨儿小屋
@xinee0 · 751 post晓晓的日常
@xq11334466 · 1281 post浦东云朵的个人简介
@yunduogr · 621 post徐妍熙的☁️培训班🎓
@yuxiyand · 1401 post欣怡的朋友圈
@zai_xiao · 491 post
Names
Channels on the register whose handles appear in this channel's posts.
@xichalssh · 29,10881 posts上海【喜茶】实时推荐榜
@xichatjsh · 10,08280 posts上海【喜茶】茶友群
@xichacysh · 42,82376 posts上海【喜茶】广播站
@xichash · 10,68076 posts欢迎来找茶
@zhaocha_bot · 14,86974 posts上海【喜茶】作业报告
@xichabgsh · 12,16321 posts上海安琪抓龙筋选妃频道
@anqixuanfei · 2,3801 post👑【上海高端推油总汇】👑
@CJG9527 · 42,7051 post上海娱乐休闲评价区
@JXG168 · 2,2071 post上海「 丝足阁 」-榜
@Ks253 · 3,0971 post上海高端全果推油6T聊天群
@shty9527 · 30,6341 post少女污·情景演绎·❾❽海选
@ws2678 · 5,0921 post
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“上海【喜茶】榜单 (中转)” (@xichalsshzz), 10,304 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/xichalsshzz.
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.