宝贝们!今天可以约哦

Channel
江江朋友圈
@ggbgn6565
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
479subscribers
-34 since we began measuring on 5 September 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1002705499023 |
|---|---|
| Type | Channel |
| Username | @ggbgn6565 |
| Created | Between 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 5 September 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/ggbgn6565 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 02:57 | 479 | -31 |
| 8 Sept 2026, 07:37 | 510 | -3 |
| 5 Sept 2026, 09:23 | 513 | no change |
| 5 Sept 2026, 08:47 | 513 | first reading |
Engagement
20 posts held, back to 10 January 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 page of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.835%
- avg views ÷ 479 subscribers
- Avg views / post
- 4.0
- 2 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 2
- of 20 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 September 2026 |
|---|---|
| Posts held | 20 (10 January 2026 – 5 September 2026) |
| Views total | 8 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Sept 2026, 09:23 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
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 1 | 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 1 of the 20 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 10 January 2026 to 5 September 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
Photo, posted without a caption
💃老师:#江江 🤖链接:https://t.me/shanghaidadao/11882 💒位置:#浦东 ------------------ 💌出击报告:老师很温柔,口技也很好,皮肤白,不催钟,各种姿势都很配合,挺好的一个老师,实实在在,还会返食
💃老师:#江江 🤖链接: https://t.me/shanghaidadao/10358 💒位置: #浦东 ------------------ 💌出击报告:老师课表上面写了的都有的,进门时候老师是穿着铆钉高跟鞋和尼龙色的包臀裙,很巧妙地把自己的优势都展示出来,长腿和美胸,老师的胸型是我个人比较喜欢那种坚挺的球型,没有下垂,验证过是自然的🐻,老师下面很紧致并且水很充足,放进去之前有摸了一阵子手上就全是水了,进去之后也感受到老师的下面温热且泛滥,整个过程很舒服,老师的叫声自然并且投入,让我动力十足,还和老师在客厅的镜子试了站着,不过我个人水平有限没有发挥好,最后时间到了也是和老师约定有缘再见后老师也给离别的拥抱和吻别,总结来说就是生理和心理都满足了,谢谢老师。
💃老师:#江江 🤖链接: https://t.me/shanghaidadao/11379 💒位置: #浦东 ------------------ 💌出击报告:进门后先从漫游全身开始,掌心顺着脖颈往下,经过胸口、小腹,再绕到大腿内侧,力道时轻时重,每到敏感处都会多停几秒,把人一点点从平静推到发热。动作不疾不徐,却很有存在感。 蚂蚁上树是她的前戏杀手锏。指尖从脚腕开始极轻极慢地往上爬,经过小腿、大腿内侧,最后落到最敏感的地方。力道轻到几乎只有痒意,却偏偏让人无法忽视,整根被她用这种方式从软挑到完全硬挺,耐心又坏。 花式吹箫在身体完全热起来之后接上。舌头、嘴唇、喉咙轮流切换,时而深吞到底用力吸,时而退出只用舌尖快速弹弄,变化又多又准。她会根据反应调整,快到了就放慢用喉咙研磨,不到就不停,技巧很稳。 漫游全身的细致铺垫、蚂蚁上树的细腻挑逗、花式吹箫的丰富变化,整场过程环环相扣。结束时她抬起头,嘴角还亮晶晶的,表情很放松。这种会漫游、会…
💃老师:#江江 🤖链接: https://t.me/shanghaidadao/11379 💒位置: #浦东 ------------------ 💌出击报告:江江给人的第一感觉就是待客如初恋,进门后的语气和眼神都很软,完全没有那种急着做事的感觉。她会先问累不累、想怎么开始,态度温柔得像真的在跟喜欢的人相处,让人一下子就放松下来。蚂蚁上树是她的前戏方式。指尖从大腿内侧极轻极慢地往上爬,只留下若有似无的痒意,却偏偏让人无法忽视。力道轻到几乎只有触感,整根被她用这种方式一点点挑到完全硬挺,耐心又坏。花式吹箫是在身体完全热起来之后开始的。舌头、嘴唇、喉咙轮流切换,时而深吞到底用力吸,时而退出只用舌尖快速弹弄,变化又多又准。全程她都保持着那种初恋般的眼神,含到最深的时候还会轻轻抬眼看我,又纯又色。蚂蚁上树的细腻、花式吹箫的技巧、再加上待客如初恋的温柔态度,整场又爽又安心。这种会吹、会挑逗、还让人觉得被认真对待的,上课首选没跑。
💃老师:#江江 🤖链接:https://t.me/shanghaidadao/11379 💒位置:#浦东 ------------------ 💌出击报告:开始就按流程走,先做全身按摩放松,再慢慢转入正题,每一步都衔接得很顺,完全没有生硬的地方。蚂蚁上树是她的前戏杀手锏。指尖从脚腕开始,极轻极慢地往上爬,经过小腿、大腿内侧,最后落到最敏感的地方。力道轻到只有痒意,却偏偏让人无法忽视,整根被她用这种方式从软挑到完全硬挺,耐心又坏。真正插入时她选择观音坐莲。面对面坐下来,自己把整根吞进去,胸口贴着胸口,双手环着我的脖子,腰慢慢扭动。因为体位亲密,她里面的温度和收缩都传得很清楚,还会时不时低头亲一下,动作又密又会夹。从莞式一条龙的完整流程、蚂蚁上树的细腻挑逗,到观音坐莲的深度缠绵,整场服务过程被她做得又专业又色。这种会前戏、会坐、还会把一条龙走完整的,体验完会很想再约。
可以约噢
Photo, posted without a caption
💃老师:#江江 🤖链接:https://t.me/shanghaidadao/10358 💒位置:#浦东 ------------------ 💌出击报告:江江服务很全面,属于典型的莞式一条龙,技术扎实又配合。 她先低头认真给我舔蛋,小舌头又热又软,从蛋蛋下面一路往上舔,吸得特别仔细,舌尖还轻轻顶前列腺区域,舔得我鸡巴直跳。 前戏过后,她直接骑上来观音坐莲,面对面坐在我鸡巴上,腰扭得又慢又深,下面又紧又热地包裹着我。接着切换泰山压顶,她转过身背对着我,用力往下坐,蜜桃臀压得又重又弹,撞击感特别强。 她配合各种姿势的能力极强,我换后入、侧卧、抬腿猛干、站立位,她都主动调整角度和力度,让我插得又深又爽,叫床声音又甜又浪。 整个过程她从头到尾都很主动,莞式一条龙服务做得特别到位,前戏、口活、各种姿势、事后清理一样不落。 最后一轮我把她压在床上猛操,她下面夹得特别紧,我在她体内射了。她还乖乖用嘴巴帮我清理干净。观音坐莲和泰山压顶骑得又骚…
💃老师:#江江 🤖链接: https://t.me/shanghaidadao/10358 💒位置:#浦东 ------------------ 💌出击报告:家附近的老师交通便利、我比较看重服务和态度,去之前在老师频道看了各位狼友留下的好评,就有点忍不住想去立马体验、顺利约上课、见面果然老师说话很温柔、会帮洗制服丝袜也都有、非常热情主动、会主动问敏感点去服务你、服务很认真不敷衍,口活很棒、口的时候很舒适没有齿感很不错、眼神特别到位,各种爱爱姿势配合度很高、浪叫骚话不断、情绪价值拉满、让老师事后萧老师也蛮配合、后面还有帮忙按摩放松、不催钟、很棒的一次体验!
🔥1
白玫瑰代表什么?
Showing the 12 most recent of 20 posts we hold for @ggbgn6565. 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.
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 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.
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“江江朋友圈” (@ggbgn6565), 479 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/ggbgn6565.
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.