球球:156.43.C.18歲 可愛俏皮 鄰家女孩的感覺 很會聊天 性慾很強 很會配合做愛 身體很敏感 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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Channel
@xchat87
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
1,127subscribers
-11 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002798754519 |
|---|---|
| Type | Channel |
| Username | @xchat87 |
| Created | Between 1 June 2025 and 30 September 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/xchat87 |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 92% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 1 other registered channel. They sit inside a group of 3 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @uc5689/22726 Aug 2026, 07:09 UTC | @xchat87/1929 · this entry6 Aug 2026, 07:15 UTC | 1.00 | 6 minutes |
| @uc5689/22746 Aug 2026, 07:09 UTC | @xchat87/1927 · this entry6 Aug 2026, 07:14 UTC | 1.00 | 5 minutes |
| @uc5689/22766 Aug 2026, 07:10 UTC | @xchat87/1925 · this entry6 Aug 2026, 07:14 UTC | 1.00 | 4 minutes |
| @uc5689/22786 Aug 2026, 07:11 UTC | @xchat87/1923 · this entry6 Aug 2026, 07:14 UTC | 1.00 | 4 minutes |
| @uc5689/22806 Aug 2026, 07:12 UTC | @xchat87/1921 · this entry6 Aug 2026, 07:14 UTC | 1.00 | 2 minutes |
| @uc5689/22826 Aug 2026, 07:13 UTC | @xchat87/1919 · this entry6 Aug 2026, 07:14 UTC | 1.00 | 72 seconds |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @uc5689 | 7 (7/7 hand-verifiable sample passed) | 1.00 | 4 minutes | @uc5689 (7–0) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 7 of the 7 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 8 comparable posts for this entry, running 5 August 2026 to 6 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 3, the earliest publisher we hold is @xchat87 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
This channel’s posts match, word for word or near enough, posts on 2 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 08:52 | 1,127 | -7 |
| 8 Aug 2026, 00:08 | 1,134 | -4 |
| 7 Aug 2026, 01:32 | 1,138 | first reading |
12 posts held, back to 5 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. It is computed over the 5 of 12 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 12 (5 August 2026 – 6 August 2026) |
| Views total | 593 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 01:32 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.
5 reactions across 5 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 5 | 100.0% |
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 5 of the 12 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 5reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 12 most recent posts we hold, published 5 August 2026 to 6 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.
球球:156.43.C.18歲 可愛俏皮 鄰家女孩的感覺 很會聊天 性慾很強 很會配合做愛 身體很敏感 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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悠悠 158cm/Ccup/20歲/45kg 首次兼職學生妹 皮膚滑嫩香氣乾淨 聲音奶奶的 說話輕輕軟軟 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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艾蜜 160.45.E+.19歲 美腿纖細. 小蠻腰柔軟 翹臀有肉 後背式撞擊很爽 皮膚白皙,粉嫩小穴超緊實,敏感度極高 摸一摸就會噴水 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
晴天 156cm 44kg B奶 19歲 小璇 155cm 44kg B奶 19歲 #學生3P 配合度100% 享受尊貴服務 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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采珍 163.47.D .32歲 淫蕩人妻 私下卻超騷 服務細膩 又主動 很會用長腿夾你 反差感強 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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晴子 163 46kg / D+杯 / 25歲 介紹:電動馬達般的翹臀 淫蕩誘惑 完美身材 若隱若現的兩顆乳球你眼前晃動 ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
小靜 163.D.46.25歲 服務:口爆、顏射、變裝、殘廢澡、#全程無套.... ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
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又是被班上的一天吶~
Sticker, posted without a caption
語遙 165 48 E 23歲 性感人妻好敢玩 為了刺激下海偷情 還嘗試在老公電話期間邊被後入!簡直是妥妥的NTR 最佳人選!圓潤飽滿的Q彈美尻 撞起來可是超快活的啊!!NTR 人妻愛好者趕緊約起來!有機會還能發展長期喔! ➖➖➖➖➖➖➖➖➖➖ 🤪北部外約 | 中部外約 🤪南部外約 | 熟女外約 🤪新手外約 | 客評專區 🤪學生外約 | 📱Line:tag91 ⭐gleezy私訊 📱TG私訊 ⭐gleezy:tw6699【ID】 🌎營業時間:下午13:00-04:00 #台灣喝茶 #台灣找小姐 #台灣外流 #台灣外約 #全台外約 #正妹優選
Showing the 12 most recent of 12 posts we hold for @xchat87. 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 — 287,726 of 1,151,006entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
@xchat87 named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“🇹🇼台灣小愛茶坊 ‧ 本土小姐 最高CP值” (@xchat87), 1,127 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/xchat87.
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.