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Channel

思思的朋友圈

@zisidpyq1

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

425subscribers

+109 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1004454149903
TypeChannel
Username@zisidpyq1
Created3 August 2026measured — dated from the channel’s first post
First recorded7 August 2026
Last confirmed live16 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 16 August 2026
On Telegramt.me/zisidpyq1

Growth

316425370.57 August 2026 — 316 subscribers8 August 2026 — 359 subscribers16 August 2026 — 425 subscribers7 August 202616 August 2026
3 measurements spanning 9 days, net +109. 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 300–441 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Aug 2026, 18:39425+66
8 Aug 2026, 06:07359+43
7 Aug 2026, 07:16316first reading

Engagement

11 posts held, back to 3 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 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
194.6%
avg views ÷ 425 subscribers
Avg views / post
827
9 posts measured
Reaction rate
0.359%
reactions ÷ views · ER floor
Posts in window
11
of 11 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 9 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 7 August 2026
Posts held11 (3 August 20267 August 2026)
Views total7,443
Reactions total17
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 07:16 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.

Reaction mix

17 reactions across 6 posts, in 3 distinct kinds. The most used accounts for 88.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1588.2%
👍15.88%
💩15.88%

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 6 of the 11 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 17reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 11 most recent posts we hold, published 3 August 2026 to 7 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

7 Aug 2026, 06:17 UTC103 views1 reactionsread 7 August 2026

突然来大姨妈了预约的哥哥不好意思了,暂时红休。这段时间可以找我小姐妹 @jinnin1p

💩1

6 Aug 2026, 10:07 UTC740 viewsread 7 August 2026
Photo

哥哥们我晚上开课位置有限因为前天被柱伤了希望理解一下,有希望的可以找我小姐妹。 @jinnin1p

5 Aug 2026, 12:51 UTC≈1,110 viewsread 7 August 2026
Photo

🎰 坂田 思思 半价抽奖活动(@sisiss10) 📮 参与条件: 🎫 加入-思思的朋友圈 🎫 加入-深圳乌鸦🐦‍⬛️已出击认证榜单+优惠情报 🎫 加入-乌鸦成群🐦‍⬛️🐦‍⬛️嫩妹聊天吧 └ 🎟️ 发言数大于 8 条 🎫 加入-深圳乌鸦のSex Note 🍌 🎁 奖品内容: 💰️ ❤️半价优惠劵❤️ × 1 ⚠️ 抽奖说明: 中奖后3天内出击,出击后24小时发报告,否则拉黑。 🔋 人品加成:⚡️× 9 规则 📅 开奖日期:(北京时间) 2026年08月08日 12时00分00秒

5 Aug 2026, 09:38 UTC668 views6 reactionsread 7 August 2026
Forwarded from @bantianchiji

#狼友投稿 @sisiss10 #坂田 思思 第一面映像,大胸,嫩妹,腼腆,内向。像是一只有点受惊的小兔子。 妹妹像极了大多数新人一样,话很少,眼神不知道看哪里。科室的环境条件很差,出奇的捡漏,还能听到隔壁工地的声音。但是妹子将房间收的很整齐,很干净。这一切好像是回到了初恋的样子。虽然物质条件很差,但是妹子的眼神很纯净,两人的心跳的很凌乱。 写长了你们也不爱看,直接总结。 爽点: 1 胸大,D杯,挺,腺粒体胸,手感超级好。洗面奶无敌。 2 逼嫩,一线天,还深埋在里面,粉嫩,红润,紧致,无异味,超级敏感。 3 皮肤光滑细腻,白皙透亮,0纹身。腿长且直。小脚圆润饱满。 不足: 1. 经验很少,很多动作,姿势都不会。不太会口,女上也菜,纯小白。 2.不耐桩。10分钟就会觉得有点疼,大屌桩机,手下留情。 3.有点感冒了,没有体验到蛇。暂不评论。期待早点好起来。 4.肚子,大腿比较怕痒。 总结,这是一个优点和缺点都非常明显的

6

4 Aug 2026, 12:16 UTC642 views4 reactionsread 7 August 2026
Forwarded from @bantianchiji

#狼友投稿 @sisiss10 #坂田 思思 初见印象:人照8分,可爱圆脸,淡妆。声音带点奶气,语气柔和。 身材:前凸后翘,丰乳肥臀。C+巨乳,见面的时候穿着黑色包臀裙,乳沟深不见底。脱掉衣物可以看到一点点小肚子,大腿较粗,屁股挺翘。乳头小小的,微棕,乳晕一元硬币左右大小。下面毛毛不算浓密,应该有修剪,很短。小穴粉嫩,偏肉色,户型好看。整体肤色偏白,皮肤细腻光滑。 服务:嫩妹正常洗吹做,不太熟练但胜在听话配合。因为妹子刚开,没有备漱口水,所以没要求🐍。 环境:课室较小,环境一般,不过妹妹收拾的很干净。铁架床,靠近门口,不能太大声。 爽点:c+巨乳,胸型饱满,弹性十足,手感很棒。可以埋半个脑袋进去,洗面奶体验极佳。 整体来说:可返。 By 云衫

4

3 Aug 2026, 17:45 UTC≈1,170 views2 reactionsread 7 August 2026
Photo

Photo, posted without a caption

1👍1

Showing the 11 most recent of 11 posts we hold for @zisidpyq1. 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

Citation-graph rank — 1,123,538 of 1,548,671entries 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.

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 2 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 16 August 2026 — this entry's latest reading, not the date you are reading this.

“思思的朋友圈” (@zisidpyq1), 425 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/zisidpyq1.

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.