男人長壽健康秘訣 多看美女延年益壽 👧🏻 💃🏻
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Channel
@tgnini9595
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Polls · Citations · Cite this entry
6,824subscribers
+267 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1002051047116 |
|---|---|
| Type | Channel |
| Username | @tgnini9595 |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 6 November 2026 |
| Measurements held | 21 |
| Confirmed unchanged | 1 time, most recently 6 November 2026 |
| On Telegram | t.me/tgnini9595 |
Adult — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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 the other topics.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Nov 2026, 04:21 | 6,824 | -3 |
| 30 Oct 2026, 11:55 | 6,827 | +1 |
| 27 Oct 2026, 20:27 | 6,826 | +4 |
| 22 Oct 2026, 02:31 | 6,822 | +6 |
| 18 Oct 2026, 16:28 | 6,816 | +8 |
| 12 Oct 2026, 16:51 | 6,808 | +19 |
| 6 Oct 2026, 08:21 | 6,789 | +20 |
| 29 Sept 2026, 09:40 | 6,769 | +36 |
| 19 Sept 2026, 05:41 | 6,733 | +13 |
| 14 Sept 2026, 11:17 | 6,720 | +17 |
| 11 Sept 2026, 05:59 | 6,703 | +7 |
| 6 Sept 2026, 12:39 | 6,696 | +25 |
| 30 Aug 2026, 11:57 | 6,671 | +17 |
| 27 Aug 2026, 18:18 | 6,654 | +7 |
| 24 Aug 2026, 08:03 | 6,647 | +21 |
| 20 Aug 2026, 15:35 | 6,626 | +22 |
| 17 Aug 2026, 10:26 | 6,604 | +15 |
| 13 Aug 2026, 13:36 | 6,589 | +19 |
| 10 Aug 2026, 16:31 | 6,570 | +12 |
| 8 Aug 2026, 01:17 | 6,558 | first reading |
25 posts held, back to 30 July 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 15 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 7 of 10 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 4 November 2026 |
|---|---|
| Posts held | 25 (30 July 2026 – 4 November 2026) |
| Views total | 16,250 |
| Reactions total | 32 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 00:50 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 11 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.
96 reactions across 19 posts, in 6 distinct kinds. The most used accounts for 46.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 45 | 46.9% | |
| 🔥 | 28 | 29.2% | |
| 🥰 | 10 | 10.4% | |
| 👍 | 6 | 6.25% | |
| 😍 | 6 | 6.25% | |
| 😱 | 1 | 1.04% |
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 19 of the 25 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 96 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 25 most recent posts we hold, published 30 July 2026 to 4 November 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.
Telegram’s own ‘edited’ marker: 0 of 10 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
男人長壽健康秘訣 多看美女延年益壽 👧🏻 💃🏻
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啊 不行了 最後幾個小時了 奶糖貼最大折扣 限時約妹 半價折扣 20k算10k 16k算8k 12k算6k 🍬私訊奶糖的TG @nini9595 🍬奶糖的Gleezy (大G:tw1234 🍬加入或點擊奶糖的Line:tw043 🍬奶糖外送茶選妃 @ym5280344 🌐官網 http://www.5280344.com
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有多少人,秋天的第一杯奶茶還沒喝呀?🤣 結果一轉眼,冬天都來了!🍂❄️ 秋天的可以錯過,冬天的可不能再落下啦! 冬日的快樂,第一杯奶茶,準備好了嗎?❤️
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Photo, posted without a caption
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Posted without readable text
我賭 10 號跑最快 😽
推薦一個奶糖茶莊的私藏紅牌 🍨條件:163cm.D奶.47kg.21歲 🍨地區:台北 新北 林口龜山萬壽路 🍨時間:14:00-22:00 可約 ✅整體:初見清純 深交銷魂 ✅無煙無刺青 真奶 可親親可舌吻 外貌神態 神似藝人陳庭妮 大眼與豐唇的完美交融 精緻五官自帶高級知性美 卻又無意間散發致命的性引誘力 顔值很高 外表給人一種知性、清新、不食人間煙火的文青氣息;然而,當燈光轉暗、衣物褪去,藏在骨子裡的熱情瞬間全面解凍。在激烈的節奏交織中,那份文青的矜持蕩然無存——眼白上吊、口中呢喃著讓人血脈僇張的真情實感:「好爽阿……」。 這種強烈的視覺與感官反差,絕對會讓你重新定義什麼叫做「沉浸式體驗 目前只有2個人約過 評價都是100分 沒約過的不知道 有約過的都迷上了 價位稍貴一點 有興趣的私奶糖 @nini9595
30cm 的帥哥哥們~❤️ 吃飽喝足了嗎? 要不要來點飯後運動, 順便健健身、放鬆一下呀?😏🍭
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有些人努力賺錢,是為了讓生活越來越好,買喜歡的東西,做讓自己開心的事,日子有盼頭,賺錢也更有動力。 有些人賺錢已經很辛苦了,卻捨不得對自己好一點,每天抱怨生活、反覆內耗,把日子過得越來越累。 同樣是辛苦賺錢, 為什麼不讓自己過得開心一點? 錢要努力賺,生活也要好好過。 人生已經夠辛苦了,何必連快樂都要委屈自己? 如果是你, 你會選擇哪一種生活?❤️
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極品正妹 邊荷律 👧🏻
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誰家需要打掃衛生呀 可以上門服務唷🙈
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💡 打手槍免費,為什麼男人還是想約妹?一篇文拆解「洩火」與「享受」的本質差異 很多哥哥經常說:「約妹一趟幾千塊,最後還不是幾分鐘的事?不如看個影片動動手,零成本又省時間!」 聽起來很有道理,但你真的覺得這兩件事能劃上等號嗎?如果自己解決真的能完全替代,那為什麼每次動完手、關掉視窗後,心裡總會湧上一股莫名的高冷與空虛? 觀點一:生理洩火 vs 身心代償 自己來,叫做「機械式洩火」 面對冰冷的螢幕、重複的手勢,大腦只得到了短暫的生理刺激。完事後進入「聖人模式」,剩下的往往只有疲憊、空虛,還有滿地的衛生紙。 約妹妹,叫做「身心雙重釋放」 人類是需要觸覺、嗅覺與互動的感官動物。妹妹身上的淡淡香水味、溫柔的肌膚接觸、耳邊的輕聲細語,以及眼神交會時的嬌羞——這些多維度的體驗,是任何影片和右手都永遠無法複製的。 🔥 更殘酷的事實是: 你看片的時候,永遠是「旁觀者」——你只能看著別人爽。 但你約妹的時候,你是「男主角」——她所有的反應…
Showing the 12 most recent of 25 posts we hold for @tgnini9595. 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.
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
不准說謊,你 一天最多做過幾次愛!!!!
Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 25 most recent posts we hold, published 30 July 2026 to 4 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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.
Named by 10 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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“台灣老司機入口|暗黑界🚗” (@tgnini9595), 6,824 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/tgnini9595.
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.