Channel
@txmg888
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
67subscribers
-16 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003362754723 |
|---|---|
| Type | Channel |
| Username | @txmg888 |
| Created | Between 1 November 2025 and 31 March 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 28 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 28 August 2026 |
| On Telegram | t.me/txmg888 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 28 Aug 2026, 22:38 | 67 | -1 |
| 21 Aug 2026, 00:48 | 68 | -5 |
| 15 Aug 2026, 00:46 | 73 | -10 |
| 9 Aug 2026, 18:00 | 83 | no change |
| 7 Aug 2026, 20:02 | 83 | first reading |
4 posts held, back to 8 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 1 pageof 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.
| Window | Rolling 30 days · latest post in window 9 August 2026 |
|---|---|
| Posts held | 4 (8 August 2026 – 9 August 2026) |
| Views total | 6 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Aug 2026, 18:00 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 2 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.
编号：2608091181 (点击复制) 🔍 点击查看验证视频 ⭐ 点击收藏该资源 ⭐ 布布1079 城市：澳大利亚 欧美 地区：全🌍 年龄：00 身高: 166 体重: 89 罩杯: C 职业：艺人 是否chu: 否 能否口：可 能否SM:轻 测试后能否无Tao:否 能否内射：否 能否过夜：可 有没有纹身：无 能否飞外省：可 是否有港澳通行证：可 能否出村：可 每月陪伴天数：3 期望零花钱：2.8 最早出发时间：有 自我加分项：🇦🇺澳洲选美冠军 签约艺人｜歌手｜演员 研修斯坦福大学哲学与心理学 📚 美国偶像第九季节目嘉宾 TVB国际华裔小姐 中国好声音选手 广告拍摄｜澳洲皇家赛马场地产宣传片🎬 SYF/介绍费：8888 100U入会，首单6折，单单打折 #美国包养 #洛杉矶包养 #三藩包养 💰支持比价介绍费可给最低 包养须知➡️➡️ @txxr888 ⚠️骗子曝光 @baomei888 🤖双向机器人 @tian…
编号：2608091178 (点击复制) 🔍 点击查看验证视频 ⭐ 点击收藏该资源 ⭐ 布布1089 城市：上海 地区： 年龄：05 身高: 165 体重: 95 罩杯: C 职业：📕 是否chu: 否 能否口：可 能否SM:轻 测试后能否无Tao:否 能否内射：否 能否过夜：可 有没有纹身：无 能否飞外省：可 是否有港澳通行证：可 能否出村：可 每月陪伴天数：3天，长期另议 期望零花钱：2.8W 最早出发时间：有 自我加分项：在上海财经大学投资专业本科+英国牛津交换+美国ucla游学 英语 日语 高尔夫 滑雪 钢琴 SYF/介绍费：7888 100U入会，首单6折，单单打折 #美国包养 #洛杉矶包养 #三藩包养 💰支持比价介绍费可给最低 包养须知➡️➡️ @txxr888 ⚠️骗子曝光 @baomei888 🤖双向机器人 @tianxinbaoyang_bot 🏆入会联系客服看视频认证
编号：2608090024 (点击复制) 🔍 点击查看验证视频 ⭐ 点击收藏该资源 ⭐ 省份：美国 城市：洛杉矶 年龄：23 身高：163 体重：43kg 罩杯：C➕ 职业：医美 drt-1 是否是处女：否 可不可以口：🉑 能不能无套：不 能不能内射：不 SM能不能：🉑轻微 有没有纹身：没 是否可外省：不 是否可过夜：🉑 可不可以同居：不 月可陪伴天数：3天 大概姨妈日期：月底 找金主的原因：想赚学费 月生活费多少：8000💲 分几次给生活费：都行 自我介绍加分项：性格好 脾气好 我性格温柔 乖巧懂事 活波开朗 情绪稳定 情商高 沟通能力强 相处起来能让你舒适 表面看着有点冷 其实很温柔 经常练习瑜伽 体态优雅 气质不踩雷 身材高挑 身材比例很好 圈子干净 跟我在一起 能给你满满的情绪价值 对老板雷点（不接受）：不能无套 介绍费12888 BOSS 888RMB入会，单单享折扣 #美国包养 #洛杉矶包养 #三藩包养 ❤️甜…
编号：2608081631 (点击复制) 🔍 点击查看验证视频 ⭐ 点击收藏该资源 ⭐ 昵称：比奇堡G128 昵称︌：G128 省份：美国 城市: 纽约 年龄︀：26͏ 身高︆：160 体︄重︇：84͏ 罩︈杯：B xue历︇：研︇究生在读︅͏ 职业：雪︅生︂͏͏ 可不︄可以︄kou：可︇以︍͏ 能不能︃内she：不︆能︉ 能不︎能无︊tao：不能︋ SM能不︋能：轻︃微︎ 有︈没︉有︇纹身︇：无︊ 是否️可︊外︋地︍：可 是否︊可过夜︂：可︅͏ 可︄不可以︉同︅居：不͏͏͏ 月可︎陪伴︀天︁数︀：至少4天͏ 大︇概姨︎妈︆日︍期：月︀底︍͏ 找金︄主︀的️原︃因︃：多︇一︆点︋生︍活︆费做︄事︍͏ 月生活︀费︌多︋少︌：1w美️🔪͏ 分几︉次︅给︂生︎活费︋：2次︇͏ 自︃我介绍︅加︍分︌项：名️校︆学︋历，颜值️身️材类︃͏ 对︊老︌板︆雷︁点（不︍接受︂）: 不︄接受…
Showing the 4 most recent of 4 posts we hold for @txmg888. 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 — 343,923 of 1,627,068entries 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 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.
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 28 August 2026 — this entry's latest reading, not the date you are reading this.
“【甜心包养】美国包养频道” (@txmg888), 67 subscribers as measured 28 August 2026. Telegram Register, tgregister.com/channel/txmg888.
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.