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Channel

心心得频道

@xinxinshuiduo159

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

427subscribers

+364 since we began measuring on 15 October 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1004382404412
TypeChannel
Username@xinxinshuiduo159
CreatedBetween 1 June 2026 and 30 September 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded16 October 2026
Last confirmed live23 October 2026
Measurements held4
Confirmed unchanged1 time, most recently 23 October 2026
On Telegramt.me/xinxinshuiduo159

Growth

6342724515 October 2026 — 63 subscribers16 October 2026 — 63 subscribers16 October 2026 — 73 subscribers23 October 2026 — 427 subscribers15 October 202623 October 2026
4 measurements spanning 7 days, net +364. 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 8–482 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
23 Oct 2026, 11:28427+354
16 Oct 2026, 02:1873+10
16 Oct 2026, 00:2263no change
15 Oct 2026, 23:4763first reading

Engagement

13 posts held, back to 15 October 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 · 30 days
55.8%
avg views ÷ 427 subscribers
Avg views / post
238
13 posts measured
Reaction rate
0.195%
reactions ÷ views · ER floor
Posts in window
13
of 13 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 2 of 13 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 15 October 2026
Posts held13 (15 October 2026 – 15 October 2026)
Views total3,098
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Oct 2026, 00:22 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
40s
Average length
13s

Measured directly from 3 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

1 reaction across 1 post, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1100.0%

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 13 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 15 October 2026 to 15 October 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

15 Oct 2026, 14:27 UTC290 viewsread 16 October 2026

心心 已经通过👉 上海【沪城】榜单 真人验证✔️(群内有优惠名额) 💬沪城街巷【交流群】 🌐沪城官网【小程序】 上榜管理:沪城 爆爆📣 被骗定金群主包赔付。现金红包 半价 白嫖 出击补贴 等你来拿

15 Oct 2026, 14:19 UTC276 viewsread 16 October 2026

心心 已经通过👉 上海【沪城】榜单 真人验证✔️(群内有优惠名额) 💬沪城街巷【交流群】 🌐沪城官网【小程序】 上榜管理:沪城 爆爆📣 被骗定金群主包赔付。现金红包 半价 白嫖 出击补贴 等你来拿

15 Oct 2026, 14:17 UTC270 viewsread 16 October 2026

上海安全可信的修车平台(免费上榜) 💯公开真资源、真老师,视频认证,不定期无门槛白嫖、半价福利,👏欢迎进群! 总站入口:@XFL98(防失联) 上海凤栖楼公告群: http://t.me/xflgg 上海凤栖楼甄选榜: http://t.me/xfltop 📲请点击>> 【上榜管理】 【双向客服】

15 Oct 2026, 14:07 UTC233 viewsread 16 October 2026
Photo

📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 🚩 编号: TE179207296975 📣 艺名: 心心 🌐 区域: #浦东 #康桥 💵 价格: 600P 1100PP 🔗 联系: @xinxinshuiduo 🔗 双向: @xinxindshuanxiongbot 🖥 资料: 年龄26 身高165 体重45KG 胸D ✏️ 服务: 舌吻 六九 鸳鸯浴 简单按摩 📌 标签: 颜值系 身材好 性价比 📝 评价: https://t.me/shlyddgj_bot?start=commentTeacher-TE179207296975

15 Oct 2026, 13:55 UTC231 viewsread 16 October 2026

每月红包、抽奖、半价、白嫖各种福利 上海大群(广告混合群) https://t.me/+TWOk2tNhl0xlMDY1 上海频道(选妃频道) https://t.me/+1pnOFefrdSM1YjVl 评价频道(评价总频道) https://t.me/+EbWEgRAWO000ZDc1 上海狼友小分队(红包白嫖各种福利) https://t.me/+xQ2RwMOlgYs5MDE1 💎一键关注所有💎

15 Oct 2026, 13:30 UTC227 viewsread 16 October 2026

👍👍👍【艺术展览会福利群】⬇️ 免费拿5折6折7折优惠 和抽奖 白嫖 现金红包🧧福利 本群专属手势认证高质量老师 上海艺术展览会福利群: https://t.me/+nFnE0wANtSRkMjEx 点击进去备用群 上海艺术展览会总榜单:https://t.me/+Bc16na5DQI82MDli 上海艺术展览会人气推荐榜 https://t.me/+vOj1VuT48NE3MDc1 上海艺术展览会中转平台 https://t.me/+jzWwy36Lm1M0MGEx 展览会老师广告群 @shanghaiyishu 个人推荐频道88🧧 📡 上榜管理:@yishuja_bot 📡 管理秘书:@Yishujia798_bot 📡 投稿报告:@Yszbgbot

15 Oct 2026, 13:25 UTC196 viewsread 16 October 2026

修车总部免费上榜: https://t.me/bjxiuchezb 修车总部综合群:https://t.me/ncnxxnx131 唯一管理员; @xcguanzong

15 Oct 2026, 12:15 UTC239 viewsread 16 October 2026
Video

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Showing the 12 most recent of 13 posts we hold for @xinxinshuiduo159. 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.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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.

Mentions

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.

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 23 October 2026 — this entry's latest reading, not the date you are reading this.

“心心得频道” (@xinxinshuiduo159), 427 subscribers as measured 23 October 2026. Telegram Register, tgregister.com/channel/xinxinshuiduo159.

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.