Channel
@jzhigd
On this record: Growth · Engagement · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
1,175subscribers
-4 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002447129833 |
|---|---|
| Type | Channel |
| Username | @jzhigd |
| Created | 23 January 2025 — measured — dated from the channel’s first post |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/jzhigd |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 21:44 | 1,175 | -3 |
| 7 Aug 2026, 16:58 | 1,178 | -1 |
| 6 Aug 2026, 19:47 | 1,179 | first reading |
11 posts held, back to 23 January 2025 — 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.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 11 (23 January 2025 – 6 August 2026) |
| Views total | 11 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 19:47 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.
32 reactions across 7 posts, in 3 distinct kinds. The most used accounts for 93.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 30 | 93.8% | |
| 😁 | 1 | 3.13% | |
| 🥰 | 1 | 3.13% |
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 7 of the 11 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 32reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 23 January 2025 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.
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❤8
Hubite Hubite主页上的搜索栏看起来好像人畜无害，但是我不建议你在里面键入任何名字，除非你手上有很多空余时间。我想写这篇评论已经好几天了，但是每次我开始写的时候，我都会被这里大量的裸体妹子给吸引而最终一事无成。 🌐网址：https://hubite.com 🎭标签：视频 电影 搜索 色情
❤2
FindTubes 当你在找某个特定主题的色情内容，而又不知道应该去哪个视频网站上找的时候，那么这时候Find Tubes就变得很有用了。这是个很简单的网站，只有很基本的功能和一个非常简约的设计，但是它能快速地完成搜索任务。 🌐网址：https://findtubes.com 🎭标签：视频 电影 搜索 色情
❤5
Xfantazy 你们是不是都准备还要来了解一下这个星球上最为热辣的免费色情视频网站了吗？我希望你们已经准备好了，因为我们今天要来看一下Xfantasy.tv这个网站，它是这个星球上最大的免费色情视频收藏库之一。你很难相信这个地方有多大，以及你能在这做的所有精彩的事情。但是，我们都知道你将在这做的一件主要事情，那就是用这个网站提供的完全没有观看显示的数以千计的视频撸管。不过你要当心一点，不要落得跟那个因为自慰过度而死掉的家伙一样的下场。 🌐网址：https://thefantazy.com 🎭标签：视频 电影 搜索 色情
❤2
PornMD 第一次打开Porn Md以后，你可能会感到有点迷糊，因为网站的界面做得非常简单。但是，你不必感到失望，因为Porn MD其实是一个AV搜索引擎。风格上跟谷歌类似（但也不是完全相同），你会在网站上看到一个搜索栏，你可以在里面键入你想要找的任何类型的色情内容。 你还可以选择直男、男同和人妖向的内容，做完这些后，你就只需要点击搜索按键，所有满足你的搜索条件的结果就会被加载在网页上。这个页面也是很好用的，因为你可以用长度、质量、日期及来源来过滤内容。 🌐网址：https://pornmd.com 🎭标签：视频 电影 搜索 色情
❤8🥰1
NudeVista 你是在找一个既有很多免费影片又很简单的网站吗？Nudevista是一个以视频网站为搜索目标的搜索引擎，我从它的名字上就猜到这点了。这个充满了一页页的视频缩略图的网站有着现代化简约的设计风格。点击任何一个缩略图，浏览器就会加载一个完全不同的网站，所以我不能保证每一个视频的质量。 这些视频的长度各不相同，从几分钟到25分钟，甚至更长的都有。这个网站的搜索功能也非常强大。网站上的模特页允许你用不同的参数来搜索你想要找的模特，比如胸部大小、国籍和头发颜色等等，或者，如果你知道那个模特的名字的话，你也可以直接使用以名字字母排序的模特列表。有些模特名下有好几百部的影片！ 🌐网址：https://nudevista.com 🎭标签：视频 电影 搜索 色情
❤1😁1
NoodleMagazine Noodle Magazine！让我们欢迎我的俄罗斯粉丝们，因为我今天要专门为你们评论一个网站。它就是NoodleMagazine.com，这将是你们心目中的理想色情网站。听着，如果你是一个正在寻找免费色情内容的俄罗斯男人，而且你还想要完整的色情影片的话，那么你就太幸运了。我猜你会选择继续阅读这篇评论，以决定这是否真的就是你正在寻找的网站。让我们来好好看一下NoodleMagazine，了解一下它都提供些什么功能，以及你能在这里找到什么样的内容。我认为你会被我们能在这个色情视频网站上找到的内容给惊艳到。所以让我们来仔细看看吧。 🌐网址：https://noodlemagazine.com 🎭标签：视频 电影 搜索 色情
❤4
Channel photo updated
Channel created
Showing the 11 most recent of 11 posts we hold for @jzhigd. 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 — 411,401 of 1,160,990entries 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.
Named by 21 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.
@jzhigd named 3 handles 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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“色情搜寻引擎” (@jzhigd), 1,175 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/jzhigd.
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.