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Channel
风陵渡口初相遇
@yangdaguo123
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
458subscribers
+1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1003872155848 |
|---|---|
| Type | Channel |
| Username | @yangdaguo123 |
| Created | Between 1 February 2026 and 7 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 2 times, most recently 14 August 2026 |
| On Telegram | t.me/yangdaguo123 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 06:50 | 458 | +1 |
| 6 Aug 2026, 20:32 | 457 | first reading |
Engagement
10 posts held, back to 7 June 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 · 30 days
- 9.83%
- avg views ÷ 458 subscribers
- Avg views / post
- 45.0
- 1 post measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 1
- of 10 held
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 5 August 2026 |
|---|---|
| Posts held | 10 (7 June 2026 – 5 August 2026) |
| Views total | 45 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 20:32 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.
Reaction mix
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 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 3 of the 10 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 2reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 10 most recent posts we hold, published 7 June 2026 to 5 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.
Recent posts
《论复刷》 🍵 我赞美复刷。复刷对 ly 更经济,对 ls 更奖惩分明,复刷让出击生态更健康。 之所以写这篇,是因为伯昌君下午吃了两个半价,一个留了三张就漂移了,另一个吃坏了肚子——别问是哪个,我不会说的。回来的路上贤者附体,万念俱空,就有了这篇。 (一)复刷,是把钱花在明处 先说个人经验:伯昌君每出击四个,一个值得复刷,一个觉得非常不值,剩下两个和价格刚好匹配。 既然大概率如此,就没有道理去赌盲池。 盲池唯一的好处,是偶尔捞到一个半价工兵。可假如你把时间、精力的成本,也当成和课费一样的真钱来算(因人而异)——那半价省下的,也不过是让总成本打了个75折。 实在不值。复刷不是省钱,是把钱花在你已经验过的明处。 (二)复刷,给老师一点获得感 不能默认老师都是理性人。 她也要情绪价值,也要在这份工作里的获得感和自我实现。一个 ly 的复刷,是对她最实在的反馈——不是嘴上的五星,是用脚投的票。 老师看得见谁又回来了…
抽奖端午节 白嫖抽奖(编号L178175724316)已成功开奖: 创建人:柏林[7198140553] 已参与人数:706 中奖名单如下: arunchahal89[6505593305](奖品为55的红包) 去看海[7290176697](奖品为米其林豌豆单p免单) 心雨见晴[7307473325](奖品为55的红包)
Channel name was changed to «风陵渡口初相遇»
抽奖编号:L178175724316 抽奖标题:端午节 白嫖抽奖 抽奖说明:米其林豌豆 举办频道关注活动 https://t.me/godagent007/411 关注豌豆的频道和各位特工的频道,参加端午抽奖 参与条件: 🎫 必须有用户名 🎫 加入-魔都光明顶教学课程展览室2 🎫 加入-特工验证榜 🎫 加入-魔都光明顶总舵入口 🎫 加入-豌豆朋友圈 🎫 加入-圣火喵喵教 🎫 加入-夢遊日記2.0 🎫 加入-ZHAO 片集 🎫 加入-Tom猫的笔记 🎫 加入-9拆盲盒 🎫 加入-心有灵犀一点通 🎫 加入-《七宗罪》实录 🎫 加入-灭火救援台账 🎫 加入-床头柜先生的日常 🎫 加入-水月洞天_二月红 🎫 加入-🍵伯昌君的休假记录 🎫 加入-风林渡口初相遇 奖品内容: 💰️ 55的红包 × 2 💰️ 米其林豌豆单p免单 × 1 开奖条件:2026-06-24 14:00自动开奖 参与抽奖链接:https://t.me/cutelott…
米其林特工验证 老师名字:温婉 老师电报号:@wenwan_1602 硬件: 颜值 4.25(小美女长相,瓜子脸,眼睛很大,一头乌黑茂密的长发,标准排骨妹,喜欢笑) 妆品 4.25(妆画的很好很舒服,近距离看也没有卡粉) 身高体重 160cm 45kg 皮肤 3.5(黄皮偏黑皮,一条胳膊上大花臂,背上痘痘明显) 胸 3(标准对A,乳头淡褐色,大小适中 腰 4(A4腰,腰身很细) 臀 4(屁股小没啥肉) 腿 4(长腿直腿,大腿有肉小腿很细) 足 4(嫩妹小脚,白色指甲油,脚上很干净) 逼 3.5(阴毛非常浓密,阴道口比较偏下,阴唇较大,整体黑色素沉淀明显) 软件: 陪浴 4(认真陪浴,主动水中萧) 亲嘴 4(蟒蛇要就给,热情有余技巧待提高,老师因为抽烟比较重能吃到淡淡的烟味) 口活 4(老师口活还不错,从下到上来回撩拨,包裹感舒适度不错) 舔逼 3.5(第一口下去有淡淡的鱼腥味,没有继续吃了) 其它服务…
❤1
Channel name was changed to «风林渡口初相遇»
风陵渡口初相遇 pinned a photo
米其林特工验证 老师名字:悠然 老师电报号:@youran1244 硬件: 颜值 3.5(人照相似度高,略高于路人颜值,看着算挺顺眼的) 妆品 3.5(妆画的比较好,老师很适合淡妆系) 身高体重 165cm 55kg 皮肤 3(偏黄皮,皮肤整体有点推油店的感觉,手感偏滑偏软) 胸 3.5(b胸,胸型偏干瘪,乳头大小适中) 腰 3(小肚子比较明显,骨架大腰身偏粗) 臀 4.5(屁股又大又紧致,后入的时候完全被埋没,感受明显) 腿 3(偏粗腿肉腿,大腿粗壮) 足 3.5(脚上肉肉的,两侧有磨出的茧) 逼 4(外部看黑色素明显,掰开里面粉嫩,阴唇小,逼型好) 软件: 陪浴 4.5(非常认真的前后冲洗和szx,服务系老师没得说) 亲嘴 4.5(超级大蟒蛇,老师舌头很软很灵活,很好吃) 口活 4.5(服务系老师的口活很好,从上到下从浅到深,从舔蛋蛋到整根含住,感受非常舒服) 舔逼 3.5(轻轻舔了会,无异味)…
❤1
米其林特工验证 老师名字:安婷 老师电报号:@antingggjj 硬件: 颜值 3.5(相比照片真人更成熟些,眉眼五官有美女的影子,笑起来眼角皱纹明显,真实年龄在30左右) 妆品 3.5(妆画的恰到好处,和颜值搭配合适) 身高体重 165cm 45kg 皮肤 3.5(偏黑皮,身体比较干净,皮肤手感较好) 胸 4(b+胸,相比排骨身材胸不小,脂肪感不算强,乳头很敏感一摸就硬) 腰 4(非常瘦的A4腰,没啥脂肪) 臀 4.5(屁股上肉比较多,波浪线明显) 腿 4(瘦腿长腿,骨感过重了少了点美感,整体还是不错的腿) 足 3.5(脚上没什么肉,脚背有点厚,两侧有磨出的茧) 逼 4(外黑嫩粉的逼,逼型好) 软件: 陪浴 4.5(do前do后的非常认真的冲洗及擦拭,包括脚也很认真在擦) 亲嘴 4(主动的蟒蛇,随便管够) 口活 5(服务系老师的顶级口活了,老师非常善于调动身体的节奏和情绪,整个口的过程让人感觉很舒…
Showing the 10 most recent of 10 posts we hold for @yangdaguo123. 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
Citation-graph rank — 1,231,294 of 1,480,975entries 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.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Mentions
Named by 2 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.
@bochangjun · 6,4032 posts魔都光明顶教学课程展览室2
@moduguangmingding2 · 53,3812 posts床头柜先生的日常
@chuangtougui99 · 2,2891 post特工验证榜
@godagent007 · 16,6871 post圣火喵喵教
@miaoshopping · 3,2861 post夢遊日記2.0
@penguin_never_die · 5,5781 post《七宗罪》实录
@qizongzui01 · 4951 post9拆盲盒
@sapper_996 · 5411 post魔都光明顶总舵入口
@shmdgmd · 37,6571 postTom猫的笔记
@Tomcatnotes · 2,1751 post豌豆朋友圈
@wandou15 · 1,6881 post
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.
Cite this entry
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“风陵渡口初相遇” (@yangdaguo123), 458 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/yangdaguo123.
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.