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Channel

四海会| (苞-养) 频道②

@sihaihui888

On this record: Growth · Engagement · Posts · Citations · Cite this entry

2,353subscribers

+191 since we began measuring on 16 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001848908077
TypeChannel
Username@sihaihui888
CreatedBetween 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded16 August 2026
Last confirmed live4 September 2026
Measurements held7
Confirmed unchanged1 time, most recently 4 September 2026
On Telegramt.me/sihaihui888

Growth

2,1622,3552,258.516 August 2026 — 2,162 subscribers17 August 2026 — 2,162 subscribers23 August 2026 — 2,165 subscribers26 August 2026 — 2,355 subscribers29 August 2026 — 2,351 subscribers1 September 2026 — 2,347 subscribers4 September 2026 — 2,353 subscribers2,35316 August 20264 September 2026
7 measurements spanning 19 days, net +191. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 2,133–2,384 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
4 Sept 2026, 21:392,353+6
1 Sept 2026, 05:142,347-4
29 Aug 2026, 00:082,351-4
26 Aug 2026, 05:532,355+190
23 Aug 2026, 13:462,165+3
17 Aug 2026, 11:442,162no change
16 Aug 2026, 18:452,162first reading

Engagement

4 posts held, back to 16 August 2026the 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 · 30 days
0.042%
avg views ÷ 2,353 subscribers
Avg views / post
1.0
4 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
4
of 4 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 16 August 2026
Posts held4 (16 August 202616 August 2026)
Views total4
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Aug 2026, 18:45 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.

Recent posts

16 Aug 2026, 18:45 UTC1 viewsread 16 August 2026
Photo

🌍编号:BO8451(点击编号自动复制) 🌺一键查询验证视频🌺 🌸点击收藏此资源🌸 省份:广东 城市:深圳 年龄:24 身高:168 体重:100 罩杯:F 职业:刚毕业 是否是chu女:不是 可不可以口:可 能不能无套/体检后:不可 Sm能不能:轻微 有没有纹身:无 可否去外省:可 是否可过夜:可 可不可以同居: 可 月可陪伴天数: 3 能否去港澳台(或者安全国家):可 大概姨妈日期: 月中 月生活费多少: 2.5 分几次给生活费:2-3 自我介绍加分项: 福建师范大雪 长相纯欲 身材火辣 比例好 会写书法和钢琴 琵琶 平常爱健身 情商高 性格好 可爱 比例好 健谈 全身无整 本人比照片好看 对金🐷雷点(不接受):无 最快什么时间可以见面陪伴:随时 介绍费:7888 🌸玩家交流⑴群 🌸备用交流⑵群 🌸真实反馈成交 🌸 尊贵VIP权益 💐入会升级一键查询内部验证视频 💐

16 Aug 2026, 18:44 UTC1 viewsread 16 August 2026
Photo

🌍编号:LU6219(点击编号自动复制) 🌺一键查询验证视频🌺 🌸点击收藏此资源🌸 省份:浙江 城市: 杭州 年龄:24 身高:164 体重:43kg 罩杯: B 职业: 电商设计师 是否chu女: 否 是否能口: 🉑 是否能SM: 🉑 是否能无🍑(体检或测试纸后):否 是否能内she: 否 是否能同居: 否 是否能过夜: 🉑 月可陪伴天数: 2天-3天 最快出发时间: 提前说 大姨妈几号来: 月中 可否飞其他城市:周末🉑 有无港澳通行证: 无 是否抽烟或纹身:否 不能接受的雷点:太胖,不尊重人, 生活费需要多少: 2天6K/3天8K (生活费接受分几次):2次 自我加分项(优点/强项): 清纯御姐,平时有瑜伽,身材比例好,性格温柔,甜美清纯,可以穿你喜欢的丝袜和情趣内衣,我可以车震,叫🛏声音大,高潮大时候会喷💦,听话 可以给你满满的情绪价值 介绍费:7888

16 Aug 2026, 18:43 UTC1 viewsread 16 August 2026
Photo

🌍编号:BA7363(点击编号自动复制) 🌺一键查询验证视频🌺 🌸点击收藏此资源🌸 省份:浙江 城市:杭州 年龄:21 身高:175 体重:108 罩杯:c 雪历:本科 职业/❄生:雪生 是否chu女:否 能否接受sm(轻中重度):轻中 能否接受口:可以 能否接受体检后无🍑:否 能否接受体检后内🐍:否 能否同居:短期可以 能否过夜:可以 每月最长可陪伴天数: 都可以,钱到位都能陪 生活费需要多少:3天2.4w 生活费分几次付(2-4次):2 能否飞往其他城市:可以 能否去港/澳:可以 自我加分项(J109-3):芭蕾9年 最快见面时间:明天 对金主雷点(不接受的点):无,钱到位都可以 双方见面满意后能否开房:可以 介绍费:7888 🌸玩家交流⑴群 🌸备用交流⑵群 🌸真实反馈成交 🌸 尊贵VIP权益 💐入会升级一键查询内部验证视频 💐主动私聊强拉均为骗子切勿上当 🌺点击查

16 Aug 2026, 18:41 UTC1 viewsread 16 August 2026
Photo

🌍编号:MR9539(点击编号自动复制) 🌺一键查询验证视频🌺 🌸点击收藏此资源🌸 省份: 江苏 南京 年龄:19 身高:164 体重:55kg 罩杯:F 职业:雪生 雷点(不能接受男友的):油腻 年龄大 秃头 是否抽烟或纹身:否 是否chu女:否 能否接受SM:可一点 能否接受无套:否(加💰可) 能否接受口:可 可同居:可 可过夜:可 一个月可陪伴天数:三天 可否飞往外地:可 最快多久出发:明天 是否有港澳通行证:有 大姨妈啥时候来:24号 生活费要多少:1w (生活费短期2次 长期3-4次能否接受):可 自我加分项(认真填写自己的优点):乖巧听话 声音夹夹的 敏感体质 💦多 F罩杯 无整 会看脸色 介绍费:7888 🌸玩家交流⑴群 🌸备用交流⑵群 🌸真实反馈成交 🌸 尊贵VIP权益 💐入会升级一键查询内部验证视频 💐主动私聊强拉均为骗子切勿上当 🌺点击查看>新手必

Showing the 4 most recent of 4 posts we hold for @sihaihui888. 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 1 registered channel — 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.

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 4 September 2026 — this entry's latest reading, not the date you are reading this.

“四海会| (苞-养) 频道②” (@sihaihui888), 2,353 subscribers as measured 4 September 2026. Telegram Register, tgregister.com/channel/sihaihui888.

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.