🌸 柚柠私影MMK 地址 #深圳 #龙华 价位 399SS 599SSS 899 讨论群 @Xingyesy 频道 @xingysy 客服 @Youningmm #MMK #女仆 #私人影院 #制服 #性感情趣换装 龙华新店入驻 柚柠私影mmk 18-223岁阵容,颜值在线无敌。 多位稚嫩学生妹妹,主题黑丝,萝莉,御姐,sm多种风格。 体验更开放式女友服务,换装、游戏,满足你对"女友"对各种的幻想。
❤1

Channel
@szblossomsss
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
31,712subscribers
+642 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1002370893081 |
|---|---|
| Type | Channel |
| Usernames | @fanhuax @szblossomsss |
| Description | 遵循真人真照和使用非本人露脸照片需告知原则,如遭遇人照不对版、服务差等问题可提交反馈。 大群 https://t.me/+YEnBxsOycJU2Yzgx 报告 @szfanhuabg 管理 @SZCJFX001 @CJFX001_bot 防失联导航 @cjnav |
| 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 August 2026 |
| Measurements held | 23 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/szblossomsss |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 20:34 | 31,712 | +4 |
| 17 Aug 2026, 17:24 | 31,708 | +30 |
| 16 Aug 2026, 18:06 | 31,678 | +26 |
| 16 Aug 2026, 08:56 | 31,652 | +71 |
| 15 Aug 2026, 06:45 | 31,581 | +30 |
| 14 Aug 2026, 23:14 | 31,551 | +68 |
| 14 Aug 2026, 00:26 | 31,483 | +35 |
| 13 Aug 2026, 15:08 | 31,448 | +29 |
| 12 Aug 2026, 18:15 | 31,419 | +17 |
| 12 Aug 2026, 16:24 | 31,402 | +68 |
| 11 Aug 2026, 17:31 | 31,334 | +2 |
| 11 Aug 2026, 15:52 | 31,332 | +58 |
| 10 Aug 2026, 17:37 | 31,274 | +3 |
| 10 Aug 2026, 16:12 | 31,271 | +53 |
| 9 Aug 2026, 18:12 | 31,218 | +8 |
| 9 Aug 2026, 15:31 | 31,210 | +18 |
| 9 Aug 2026, 11:03 | 31,192 | +46 |
| 8 Aug 2026, 14:31 | 31,146 | +5 |
| 8 Aug 2026, 12:07 | 31,141 | +42 |
| 7 Aug 2026, 15:01 | 31,099 | first reading |
81 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 26 pagesof Telegram’s post history, 20 posts per page.
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 21 of 81 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 17 August 2026 |
|---|---|
| Posts held | 81 (6 August 2026 – 17 August 2026) |
| Views total | 54,215 |
| Reactions total | 13 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 18 Aug 2026, 01:06 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.
Lifetime counters from Telegram’s own channel header, read 18 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 43 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.
13 reactions across 11 posts, in 2 distinct kinds. The most used accounts for 92.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 12 | 92.3% | |
| 😁 | 1 | 7.69% |
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 21 of the 81 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 13reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 81 most recent posts we hold, published 6 August 2026 to 17 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.
🌸 柚柠私影MMK 地址 #深圳 #龙华 价位 399SS 599SSS 899 讨论群 @Xingyesy 频道 @xingysy 客服 @Youningmm #MMK #女仆 #私人影院 #制服 #性感情趣换装 龙华新店入驻 柚柠私影mmk 18-223岁阵容,颜值在线无敌。 多位稚嫩学生妹妹,主题黑丝,萝莉,御姐,sm多种风格。 体验更开放式女友服务,换装、游戏,满足你对"女友"对各种的幻想。
❤1
安娜 @L00150 地区课费: » #罗湖 #老街 » 900P 1600PP » 23 162cm 47kg 标签: #1000以内 #制服 #女友感 #御姐 #手势验证 #新人 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
❤2
貂蝉学妹 @Jenniferchun 地区课费: » #南山 #前海湾 » 1100P 1800PP » 03 165cm 50kg 备注:人照参考榜单手势图 标签: #1500以内 #不限次 #制服 #包时 #女友感 #学生 #无纹身 #白虎 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
小柔 @bantianxiaorou1 地区课费: » #龙岗 #坂田 » 1000P 1800PP » 22 165cm 45kg 标签: #1000以内 #手势验证 #皮肤白 #舞蹈 近期简评: 差异 人照8成像,服务真可以,真会跳舞,真的不错,6 优点 会跳舞,有才艺表演,真的可以,就差一把瓜... 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
小竹子 @xzz588 地区课费: » #南山 #荔林 » 600抓龙筋 备注:人照参考榜单首图 标签: #手势验证 #抓龙筋 近期简评: 差异 本人跟照片没有区别 优点 手法特别舒服 不足 无 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
土豆 @Hxy200701 地区课费: » #龙岗 #龙城广场 » 1000P 1800PP » 18 167cm 43kg 标签: #1000以内 #kiss #上门 #制服 #声音甜 #女友感 #手势验证 #无纹身 #甜妹 #皮肤白 近期简评: 差异 和本人一样漂亮,笑起来很可爱。 优点 很热情主动,陪洗的过程中很舒服,真的是有很认真帮你洗。课... 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
青青 @BMWbb3325 地区课费: » #宝安 #西乡 » 1000P 1688PP » 19 165cm 41kg 标签: #1000以内 #上门 #不抽烟 #包时 #女友感 #手势验证 #无纹身 #甜妹 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
萱寶 @xuanbaby01 地区课费: » #南山 » 1000P 1888PP » 24 172cm 60kg 标签: #1000以内 #一米七 #不限次 #制服 #包夜 #包时 #御姐 #微胖 #手势验证 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
诗诗 @Sshi2006 地区课费: » #龙华 #清湖 » 700P 1400PP » 06 170cm 50kg 标签: #800以内 #一米七 #不限次 #制服 #包夜 #包时 #反差 #声音甜 #女友感 #女桩机 #川渝 #御姐 #手势验证 #晚课 #皮肤白 #骚 近期简评: 差异 真人比照片更好看 课表服务都有 优点 自聊妹子,腿长皮肤白,情绪价值到位,要求都会满足,可以自... 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
乔伊伊 @Qiao118801 地区课费: » #福田 #华强北 » 998P 1798PP » 25 162cm 47kg 标签: #1000以内 #制服 #包夜 #女友感 #御姐 #手势验证 #皮肤白 近期简评: 差异 8.8分 优点 很骚,吊感好,口活很棒,床上契合度惊艳,服务态度超级 nice 不足 没有 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
依依 @askari1922 地区课费: » #龙华 #清湖 » 800P 1400PP » 26 166cm 52kg 标签: #800以内 #上门 #不限次 #亲 #包时 #手势验证 近期简评: 差异 人照合一 是本人来的! 不足 无 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
南禾宝贝 @nanhebaby 地区课费: » #龙岗 #愉园 » 1000P 1800PP » 22 170cm 48kg 备注:人照参考榜单视频 标签: #1000以内 #一米七 #制服 #川渝 #按摩 查看: » 看报告 » 写报告 » 榜单 » 群组 » 防失联
Showing the 12 most recent of 81 posts we hold for @szblossomsss. 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 — 17,003 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.
Named by 38 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.
Names
Channels on the register whose handles appear in this channel's 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.
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 August 2026 — this entry's latest reading, not the date you are reading this.
“深圳繁花资源库” (@szblossomsss), 31,712 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/szblossomsss.
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.