艺名: #百香果 段位: #辅导员(青铜) 地点: #成华区 编号: #JMCD1454 黑色短发,清纯女大,中颜略高;胸B+,白,软,浅褐色旺仔小馒头;屁股大颜色黄白,肉感明显但因为骨架大仍有S曲线,较长肉腿,白嫩。 车架:22/167/98/C 车费:7p 12pp 车牌: @bxg13 机器人: @kqiai_bot 标签: #嫩妹 #女友 #敏感 #甜妹 成都交流群: @jmnu028m_a
❤4🎉1👏1🥰1

Channel
@jmnu028m
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
14,417subscribers
+240 since we began measuring on 10 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003267256462 |
|---|---|
| Type | Channel |
| Username | @jmnu028m |
| Created | Between 1 October 2025 and 31 January 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 30 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/jmnu028m |
Other / unclassifiable — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 58% 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 why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 15:38 | 14,417 | -14 |
| 15 Sept 2026, 10:21 | 14,431 | -28 |
| 13 Sept 2026, 16:38 | 14,459 | -24 |
| 11 Sept 2026, 23:38 | 14,483 | -21 |
| 9 Sept 2026, 11:38 | 14,504 | -18 |
| 6 Sept 2026, 01:39 | 14,522 | +2 |
| 3 Sept 2026, 18:39 | 14,520 | -9 |
| 2 Sept 2026, 13:08 | 14,529 | +6 |
| 1 Sept 2026, 14:35 | 14,523 | -2 |
| 31 Aug 2026, 12:28 | 14,525 | +13 |
| 30 Aug 2026, 10:13 | 14,512 | +14 |
| 29 Aug 2026, 10:55 | 14,498 | +15 |
| 28 Aug 2026, 13:07 | 14,483 | +18 |
| 27 Aug 2026, 14:13 | 14,465 | +18 |
| 26 Aug 2026, 17:44 | 14,447 | +9 |
| 25 Aug 2026, 19:52 | 14,438 | +14 |
| 24 Aug 2026, 19:42 | 14,424 | +53 |
| 23 Aug 2026, 05:26 | 14,371 | +10 |
| 21 Aug 2026, 20:36 | 14,361 | +32 |
| 20 Aug 2026, 16:06 | 14,329 | first reading |
19 posts held, back to 7 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 39 pages of 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 3 of 5 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 August 2026 |
|---|---|
| Posts held | 19 (7 August 2026 – 26 August 2026) |
| Views total | 7,918 |
| Reactions total | 17 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 2 Sept 2026, 18:35 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.
Measured directly from 8 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.
117 reactions across 17 posts, in 13 distinct kinds. The most used accounts for 41.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 48 | 41.0% | |
| 👍 | 14 | 12.0% | |
| 🥰 | 13 | 11.1% | |
| 🔥 | 11 | 9.40% | |
| 🎉 | 10 | 8.55% | |
| 👏 | 6 | 5.13% | |
| 🍓 | 4 | 3.42% | |
| 🍾 | 3 | 2.56% | |
| 🐳 | 3 | 2.56% | |
| 🍌 | 2 | 1.71% | |
| ⚡ | 1 | 0.855% | |
| 🌭 | 1 | 0.855% | |
| 💋 | 1 | 0.855% |
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 17 of the 19 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 117 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 7 August 2026 to 26 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.
艺名: #百香果 段位: #辅导员(青铜) 地点: #成华区 编号: #JMCD1454 黑色短发,清纯女大,中颜略高;胸B+,白,软,浅褐色旺仔小馒头;屁股大颜色黄白,肉感明显但因为骨架大仍有S曲线,较长肉腿,白嫩。 车架:22/167/98/C 车费:7p 12pp 车牌: @bxg13 机器人: @kqiai_bot 标签: #嫩妹 #女友 #敏感 #甜妹 成都交流群: @jmnu028m_a
❤4🎉1👏1🥰1
😀😀😀😀 ㊙️ 成都本地实体老店,安全隐私,卫生干净 每日执行一客一消毒 ✅ 项目:高端SPA、实体丝足、高颜技师 特色项目 纯到店满意消费,无任何套路 92十八项 都有 只多不少😂 📍 地址:成都锦江区58神奇空间 🕒 营业时间:13:00 - 凌晨 02:00 提前预约 不跑🈳 #成都SPA #成都会所 #成都按摩 #成都锦江 ———————————— 👥聊天群组: @chengdu_666 🗣️选妃频道: @chengdu_888 💬在线客服: @SPA1994000 🤖私信限制: @SPA8888mcbot 😎微信联系:Y770412250 ☎️联系电话:16608107162
艺名: #泡芙 段位: #辅导员(青铜) 地点: #成华区 编号: #JMCD1453 老师人照8 天然G奶 服务态度不错 身高正常 吨位较大 声音属于萝莉音 服务简单 适合喜欢巨乳的狼友去体验 车架:20/164/126/G 车费:6p 10pp 车牌: @paofu06888 机器人: @paofu06888bot 标签: #巨乳 #甜妹 #坦克 #诱惑 成都交流群: @jmnu028m_a
❤3👍1🔥1
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艺名: #小不点 段位: #辅导员(青铜) 地点: #锦江区九眼桥 编号: #JMCD1452 人照合一,真人看起来比照片小,颜值不错,冷白皮没有纹身,很嫩,服务认真,口活不错且时间久,大蟒蛇主动可以随便蛇,可能刚下水比较内向,适合喜欢小只冷白皮嫩妹的狼友出击 车架:18/158/80/B+ 车费:7p 12pp 车牌: @Bq03777 机器人: @xiaobudian22Bot 标签: #嫩妹 #萝莉 #可爱 #甜美 成都交流群: @jmnu028m_a
❤2⚡1👍1🔥1
艺名: #小迪 段位: #辅导员(青铜) 地点: #成华区 编号: #JMCD1451 四川妹子,才来成都开,嫩妹基本没服务,无纹身,下边湿紧烫,170的身高,50kg左右,照片没有本看,喜欢嫩妹的可以无脑冲了,服务基本无,嫩妹性价比值得考虑。 车架:18/170/90/B+ 车费:6p 10pp 车牌: @Tianoipo 机器人: @Xiaodi1111Bot 标签: #嫩妹 #新人 #可爱 #温柔 成都交流群: @jmnu028m_a
❤6🍓1🎉1🐳1👍1
艺名: #娇娇 段位: #辅导员(青铜) 地点: #南门 编号: #JMCD1450 人照相似度极高(9分),妆容精致,服务热情细致,情绪价值拉满。价格与体验匹配度较好,稍微有点小肚子,无纹身。适合喜欢身材好、服务到位、温柔型少妇的狼友。 车架:21/163/98/D 车费:6p 9pp 车牌: @jiaoer857 机器人: 标签: #巨乳 #颜值 #服务 #温柔 成都交流群: @jmnu028m_a
❤2🥰2👍1
艺名: #玖儿 段位: #辅导员(青铜) 地点: #高新区交子大道 编号: #JMCD1449 6p服务天花板级别,各种服务做的认真细致,口活极佳,人照9成相似、身材不胖不瘦正常、情绪价值拉满、性价比还挺高, 车架:19/163/98/A+ 车费:6p 9pp 车牌: @Jiurex 机器人: @QIyvejbot 标签: #嫩妹 #颜值 #服务 #性价比 成都交流群: @jmnu028m_a
❤3🎉3👍2
艺名: #玥曦 段位: #辅导员(青铜) 地点: #成华区石羊 编号: #JMCD1448 人照相似8.8说话温柔 态度很好 胸大 舌头灵活 比较敏感 反馈强烈 很有良家感 符文大师 很值得回锅 车架:23/170/110/D 车费:6p 9pp 车牌: @lgngcz121 机器人: @jiajia0123bot 标签: #御姐 #符文 #巨乳 #白皙 成都交流群: @jmnu028m_a
❤4👏3🔥1🥰1
艺名: #E宝 段位: #辅导员(青铜) 地点: #成华区二仙桥 编号: #JMCD1447 老师巨乳E,有乳交,有🐍,要抽烟,无纹身,颜值耐看,属于丰满bbw类型少妇服务车,适合喜欢巨乳、bbw、服务的狼友。 车架:26/164/105/E 车费:6p 9pp 车牌: @Ebao361143 机器人: @hsdhhabot 标签: #御姐 #颜值 #巨乳 #可爱 成都交流群: @jmnu028m_a
🔥3❤2🎉1👏1
😀😀😀😀 ㊙️ 成都本地实体老店,安全隐私,卫生干净 每日执行一客一消毒 ✅ 项目:高端SPA、实体丝足、高颜技师 特色项目 纯到店满意消费,无任何套路 92十八项 都有 只多不少😂 📍 地址:成都锦江区58神奇空间 🕒 营业时间:13:00 - 凌晨 02:00 提前预约 不跑🈳 #成都SPA #成都会所 #成都按摩 #成都锦江 ———————————— 👥聊天群组: @chengdu_666 🗣️选妃频道: @chengdu_888 💬在线客服: @SPA1994000 🤖私信限制: @SPA8888mcbot 😎微信联系:Y770412250 ☎️联系电话:16608107162
❤4🍾3👍1🥰1
艺名: #周于希 段位: #辅导员(青铜) 地点: #成华区昭觉寺 编号: #JMCD1446 妹妹皮肤超级光滑,肤白,奶挺柔软,穴紧这几方面算是快到千人斩的本君也少见排前茅的。 喜欢嫩妹,身材控,肤控,穴紧的值得一试。 车架:26/168/100/C 车费:8p 14pp 车牌: @zhouyuxisl 机器人: @zhouyuxisally_bot 标签: #御姐 #颜值 #风骚 #可爱 成都交流群: @jmnu028m_a
❤3🎉3🍓2👍1
Showing the 12 most recent of 19 posts we hold for @jmnu028m. 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.
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.
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 September 2026 — this entry's latest reading, not the date you are reading this.
“【集美师范大学】成都校区” (@jmnu028m), 14,417 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/jmnu028m.
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.