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Channel
上海大道精品榜
@shanghaidadao
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
48,039subscribers
+9,136 since we began measuring on 14 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002238173279 |
|---|---|
| Type | Channel |
| Username | @shanghaidadao |
| Created | Between 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 14 August 2026 |
| Last confirmed live | 8 November 2026 |
| Measurements held | 55 |
| Confirmed unchanged | 1 time, most recently 8 November 2026 |
| On Telegram | t.me/shanghaidadao |
Topic
Adult — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 53% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Nov 2026, 16:19 | 48,039 | +17 |
| 7 Nov 2026, 12:28 | 48,022 | -73 |
| 6 Nov 2026, 14:05 | 48,095 | -50 |
| 5 Nov 2026, 12:11 | 48,145 | +126 |
| 4 Nov 2026, 14:06 | 48,019 | -33 |
| 3 Nov 2026, 17:39 | 48,052 | +131 |
| 2 Nov 2026, 17:55 | 47,921 | +61 |
| 1 Nov 2026, 15:55 | 47,860 | -154 |
| 31 Oct 2026, 15:46 | 48,014 | +4,663 |
| 30 Oct 2026, 13:41 | 43,351 | -184 |
| 29 Oct 2026, 14:05 | 43,535 | -278 |
| 28 Oct 2026, 14:30 | 43,813 | -245 |
| 27 Oct 2026, 17:44 | 44,058 | -209 |
| 26 Oct 2026, 15:50 | 44,267 | -394 |
| 25 Oct 2026, 14:20 | 44,661 | -1,999 |
| 24 Oct 2026, 12:46 | 46,660 | -1,888 |
| 23 Oct 2026, 14:49 | 48,548 | -221 |
| 22 Oct 2026, 11:19 | 48,769 | -572 |
| 21 Oct 2026, 01:19 | 49,341 | -612 |
| 19 Oct 2026, 23:55 | 49,953 | first reading |
Engagement
248 posts held, back to 14 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 170 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.097%
- avg views ÷ 48,039 subscribers
- Avg views / post
- 46.5
- 96 posts measured
- Reaction rate
- 0.725%
- reactions ÷ views · ER floor
- Posts in window
- 96
- of 248 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. It is computed over the 6 of 96 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 November 2026 |
|---|---|
| Posts held | 248 (14 August 2026 – 8 November 2026) |
| Views total | 4,461 |
| Reactions total | 3 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Nov 2026, 13:30 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.
What this channel posts
- Video runtime
- 26m 21s
- Average length
- 7s
Measured directly from 217 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
13 reactions across 12 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 13 | 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 18 of the 248 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 13 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 248 most recent posts we hold, published 14 August 2026 to 8 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 96 posts held from the last 30 days (0%) 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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Showing the 12 most recent of 248 posts we hold for @shanghaidadao. 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 66 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.
@SHDD333 · 5,501211 posts兼职洋洋的小窝
@bvv16433 · 53212 posts梦梦的后花园
@cccbbb5353 · 43611 posts小艺的衣帽间
@okkokk28811 · 65610 posts果粒的爱巢
@qiqidejianjie1 · 34010 posts苏苏的朋友圈
@uhnbgdfd · 56810 posts嘻嘻的后宫
@jeek64773333 · 1389 posts小欣展示的地方
@sisi23222 · 4819 posts娜娜的日常
@hjghg52kju · 5978 posts苹果的日常
@kkvv8777 · 1088 posts甜柚的小窝
@liweiweitg · 5148 posts樱樱的后宫
@malimali9900 · 1338 posts米朵的家🏠
@sanmao2333444 · 3618 posts甜馨的小屋
@shushande · 5658 posts爱财的朋友圈
@fanng2616611 · 6377 posts小优的朋友圈
@fuyao8520 · 7257 posts江江朋友圈
@ggbgn6565 · 2917 posts草莓撒野的地方
@ghgh335566 · 3567 posts婷婷的后花园
@pcmm2323 · 5707 posts静安的吞精兽
@ten89888999 · 6317 posts糖糖私人空间
@uoss72331 · 4247 posts嘟嘟的秘密基地
@bbbwe993 · 7576 posts迪娜拉的小窝
@psspss9899 · 5526 posts安宁的家
@shunli299299 · 1336 posts
Names
Channels on the register whose handles appear in this channel's posts.
@SHDD333 · 5,501181 posts上海大道出击报告
@SHDCJBG · 71430 posts上海连理丝足柔式SPA水疗会馆
@lianlishuiliaoroushiSPA · 3,1968 posts2D{二次元嫩模}全类型
@ecy98zx · 1,2297 posts上海「 丝足阁 」-榜
@Ks253 · 11,6766 posts上海莞式海选
@AM03611 · 6,8735 posts小九的小窝
@BBcc135135 · 3674 posts中韩混血冰冰的新家
@ffkk563322 · 6684 posts小芊的小窝
@man1579mm · 7354 posts梦琪的美好记录📝
@miaomiaodh · 7264 postsTina的爱巢
@tianxin001001 · 7564 posts嘟嘟的秘密基地
@bbbwe993 · 7573 posts娟儿的日记
@biju29229399 · 5663 posts兼职洋洋的小窝
@bvv16433 · 5323 posts巨乳沐沐的office
@ccm57332 · 3293 posts大蜜的衣帽间
@haifai7248 · 5483 posts闵行爱己的基地
@kk3788kk · 5533 posts樱樱的后宫
@malimali9900 · 1333 posts菲儿小屋🛖
@mbamba943320000 · 2583 posts小艺的衣帽间
@okkokk28811 · 6563 posts迪娜拉的小窝
@psspss9899 · 5523 posts可乐会所
@yaoyao668668668 · 1703 posts沐瑾的家园
@zxczz2211 · 2663 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.
Handles this channel named that no longer answer
- Dead references
- 2
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 1
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@shanghaidadao named 2 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.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
named in 1 post, 23 August 2026 – 23 August 2026 · confirmed gone 3 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 2 posts, 19 August 2026 – 15 October 2026
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 8 November 2026 — this entry's latest reading, not the date you are reading this.
“上海大道精品榜” (@shanghaidadao), 48,039 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/shanghaidadao.
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.