Channel
@theShibaKnows
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
303subscribers
+2 since we began measuring on 23 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002521938395 |
|---|---|
| Type | Channel |
| Username | @theShibaKnows |
| Created | Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 23 August 2026 |
| Last confirmed live | 9 September 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 9 September 2026 |
| On Telegram | t.me/theShibaKnows |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Sept 2026, 17:18 | 303 | +2 |
| 24 Aug 2026, 17:02 | 301 | no change |
| 23 Aug 2026, 19:01 | 301 | first reading |
18 posts held, back to 18 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 1 page 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 1 of 2 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 19 August 2026 |
|---|---|
| Posts held | 18 (18 July 2026 – 19 August 2026) |
| Views total | 298 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 23 Aug 2026, 19:01 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.
16 reactions across 9 posts, in 3 distinct kinds. The most used accounts for 81.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 13 | 81.3% | |
| 👍 | 2 | 12.5% | |
| 👌 | 1 | 6.25% |
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 9 of the 18 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 16 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 18 July 2026 to 19 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.
#上海 12 熙熙安 @xixian520 二探盘丝洞，略有落差。事后反思，去之前期望值确实拉得过高了，源自于一是雪儿那里近乎完美的体验，二是熙熙安本身的口碑也一直很稳，可能主观上形成了一加一大于二的效果。结果第一眼看到熙熙安的反应是有点普通，然后一旦形成了这个先入为主的印象。感觉后面整体的体验都一直处于这个“阴影”之下。 平心而论，熙熙安的一双媚眼非常好看，辨识度很高，颜值是可以的。整体身材也没有太大的短板。床上开始之后，熙熙安的床技更是令人眼前一亮，她的口和女上的技术是我见过数一数二的强，不是靠花哨的动作，而单是靠上强度，以频率和力度取胜。她自己也说很多人在她口的阶段就交代了（这才是可靠的第一手证据，而不是狼友报告里的“ 我认为 ”！）。其他姿势的体验相对比较普通一些。 休息时熙熙安会按摩，而且按摩得非常认真，从头到脚舔过去再用胸推，如果喜欢服务的应该会很满意。类似的，事前事后的陪浴同样也很仔细，每一个步骤都执行得很…
👍1
#八卦
#上海 11 雪儿 @xueer_999 首探盘丝洞，不愧是驰名温柔乡，雪儿的颜值身材均属上乘，软硬件都没有短板，体验极佳，可以给个超级好评。人照8.5，去美颜瘦脸效果即可，偏御姐美人，肉感丰腴而不多余，有健身痕迹。长腿翘臀。 小区是黄浦老小区，四通八达比较安全，就是住宅楼的底楼是二楼，需要先上一层，搞得我这个路痴有点摸不着头脑，绕了好大一个圈子。 雪儿给我印象最深的点，一方面是天然去雕饰的感觉，说话温温柔柔的，无论交流还是性爱，基本没有风尘感，就好像是和美丽的邻家女孩在一起的感觉，甚至在约课时，我就感到这个妹子比别的老师都要更有礼貌一些。 另一方面，雪儿的“性商”又很高，技巧方面毫不含糊，女上咣咣坐，反馈真实不做作，还让我手指探入小穴体会了她真空吸吮的绝技，非常厉害。特别有意思的是至少有两次，她在我提出要求之前就主动提出调整姿势，完全契合我的想法，预判准确得令人吃惊。第一次是从正面女上转到背面女上，第二次是第二p出不来…
👌1
https://t.me/shlsbb 原来是深圳雷师榜，做得还挺大的，现在开设上海分榜了。多一个分享踩坑信息的渠道总是好事。
#上海 10 #深圳 林杉杉 @DAQIAO1669 半年前第一次深圳出击时，林杉杉已经是我的首选之一了，只是时间安排不过来。这几个月她在上海又收割了一波流量。去这种在两大市场都有口碑的老师，完全没有什么好担心的，心情就特别轻松。 老师开课的地方相当偏僻，小区也是新的人很少，感觉安全系数很高。她给的指引一步步很清楚，上楼推门而入，光线比较暗，看到一个一身黑色吊带长裙的177高个女孩，一头乌黑长发，身材凹凸有致，样子和频道8月1日新发的白色长裙照片几乎一模一样。虽然是个大车御姐，但老师声音很温柔，气质则是偏高冷一类的。我看有的人说她有点“傲娇”，可能就是她的这种气质吧，我倒也没有觉得有什么不舒服的。 交了钱，简单交谈几句，她就去放水，脱衣服，略显仓促。但确实是完美的身材，丰乳肥臀细腰长腿，属于丰腴型的美人，又一点不显胖，同时也没有任何人造的痕迹。陪浴比较简单，洗完后她换上一身黑红色情趣连体吊带丝袜，显得更加性感了，天生的衣…
不亏是ai，人脑绝对没有这种想象力。🤣🤣 #八卦
最近看报告看得厌蠢症发作了，现在好多人喜欢写“敏感的人可能这时候就交代了”“123可能这时就被秒了”，还有蠢人一篇报告里每个阶段都要重复一次的。 非要靠臆想才能描述老师活很好吗？ #八卦
❤1👍1
威海市硬笔书法协会，网页还在。 #八卦
❤1
#上海 9 妮妮 @ninibaby99 和妮妮近在咫尺，真想约却有点一波三折。第一次约好她红休意外提前了，第二次刚要约她发频道感冒了，等第三次已经过去了一月有余，妮妮广受各方好评，已晋升满姐了。还好在各个“满”字之间觅得一个“空”，赶紧约上。 虽然在步行距离内，但毒日高挂，还是骑上心爱的小电驴前往。老师开课的地点是在一个高档小区里开的酒店公寓，隐蔽性不错，且据老师说有认识人，比较安全。小区门口有保安但不会管，老师指引也很清楚，直接走过前台上电梯，出电梯老师已留好门，整个过程非常丝滑。 进门就被妮妮的车灯晃的有点睁不开眼，胸型很漂亮。老师非常活泼热情，话多爱笑，毫无第一次见面的距离感。洗澡前会先让挑制服，选择挺多的，陪浴的时候会有胸推和水中萧。 到了床上，妮妮的舌吻非常投入，量大管饱。舔耳舔胸后开始口，口的力度很大，还有深喉。她还会主动送上洗面奶，其实我不是匈奴人，但也不介意配合一下。舔她下面时她的反馈也很大，包括接下来…
（续上） 这声音就是很标准的“警铃大作”，一听就知道有事情发生了。妹子立刻就变了脸，赶快下床并示意我起来。好几个其他妹子也从四面八方出现，之前那个黑衣妹子不知从哪里拿出我的浴袍给我，知道是同一件，因为里面还有我的储物柜钥匙。我的妹子示意我穿衣去床上等着，然后她们就跑了，跑了… 整个过程算是忙而不乱，她们肯定见多了，基本上30秒就完成了。我内心倒是没有太多波澜，因为还没怎么做呢，真要是警察来了我就咬定是马杀鸡，还有语言障碍和外国人身份作为挡箭牌，这么多层护甲，他再深究我也只好认栽。 接下来大约二十分钟的等待时间里，最大的问题竟然是无聊。手机是不能带入的，基本就什么事情也不能做了。想睡会吧，可音乐和灯光都没停。实在坐/卧不下去了，我就溜达了一圈，此时发现整层楼似乎就我一个人。（也不排除之前有韩国本地客人，但没有语言障碍所以也跟着跑了？）一层楼一共也就十间房的样子，那要是高峰时间来估计很热闹了，肯定都是满满当当的，淫声浪语此起彼伏…
❤2
Video, posted without a caption
Donuts的价位表和休息等待区。
Showing the 12 most recent of 18 posts we hold for @theShibaKnows. 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.
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.
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 9 September 2026 — this entry's latest reading, not the date you are reading this.
“the insatiable Shiba” (@theShibaKnows), 303 subscribers as measured 9 September 2026. Telegram Register, tgregister.com/channel/theShibaKnows.
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.