Telegram RegisterThe public register of Telegram

Channel

两性知识「新」

@liangxing1024

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

2,923subscribers

+3 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003811556105
TypeChannel
Username@liangxing1024
CreatedBetween 1 February 2026 and 8 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/liangxing1024

Growth

2,9202,9232,921.56 August 2026 — 2,920 subscribers6 August 2026 — 2,920 subscribers10 August 2026 — 2,923 subscribers6 August 202610 August 2026
3 measurements spanning 4 days, net +3. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 2,920–2,923 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 00:512,923+3
6 Aug 2026, 05:042,920no change
6 Aug 2026, 03:372,920first reading

Engagement

16 posts held, back to 8 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
5.95%
avg views ÷ 2,923 subscribers
Avg views / post
174
1 post measured
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 16 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held16 (8 June 20267 August 2026)
Views total174
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 17:07 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.

What this channel posts

Video runtime
34s
Average length
9s

Measured directly from 4 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.

Reaction mix

46 reactions across 13 posts, in 5 distinct kinds. The most used accounts for 76.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3576.1%
💩715.2%
🥰24.35%
👍12.17%
😁12.17%

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 13 of the 16 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 46reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 16 most recent posts we hold, published 8 June 2026 to 7 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

7 Aug 2026, 01:00 UTC174 viewsread 7 August 2026

#频道互推 你不知道的内幕消息🅥 美女写真套图-每日更新 美好的小姐姐 粉馒头🩷推特|福利姬👿 写真花絮系列 极品风韵魅妇 两性知识「新」 树洞秘语🌳 【匿名】 ──── 💡 互推: @jxht_bot

10 Jun 2026, 05:24 UTC≈8,960 views3 reactionsread 7 August 2026

此频道为 @liangxing365 备用频道,后期更新缓慢,仅发精品消息

2👍1

9 Jun 2026, 14:09 UTC≈8,660 views11 reactionsread 7 August 2026
Video

“男生找对象就一条准则” ———— 两性知识 | 两性知识「备」 树洞秘语 | 精品短片

💩74

9 Jun 2026, 12:58 UTC≈6,430 views1 reactionsread 7 August 2026
Video

你知道怎么调情吗?你知道怎么让女人对你欲罢不能吗? ———— 两性知识 | 两性知识「备」 树洞秘语 | 精品短片

1

9 Jun 2026, 10:15 UTC≈5,880 views12 reactionsread 7 August 2026
Video

警方抓获卖淫女后,为何不用交易记录寻嫖客? 你记住了,一旦被警察认定你是嫖客,所谓的宽大不宽大,其实都是一个样,无非就是拘留十天还是15天,所以,当警方打电传唤你的时候,最好的办法不是说我不去,就是说我不在当地,等我回来,马上去派出所,不过暂时回不来,然后连夜买张票跑路,派出所民警是不能异地执法的,只要你离开辖区,他就没法上门,我知道有杠精,会说,他可以找异地派出所协助上门,问你可以继续跑路啊, 给朋友们讲个案例…… 叔叔抓到小霞以后,根据她的转账记录,确定了很多的嫌疑人,这时候只是嫌疑人没有任何直接证据证明你和小霞有交易 然后叔叔合法传唤你,但是你人确实在外地,合法的告诉叔叔,我一回来马上就回去接受传唤 这种情况下,叔叔是绝对不会为了你这种治安案件的嫌疑人跑去异地抓人的,因为哪怕抓到你,也就是个治安案件 有人说这一直会挂着,说的没错,会挂着,但是你要知道那个小霞最多拘留15天,等你新疆南北疆溜了16天回来,小霞早就被放了,哪怕

11😁1

9 Jun 2026, 07:16 UTC≈3,800 views2 reactionsread 7 August 2026
Photo

温泉后续来啦 老觉得写不出当时的感觉,所以删删写写让大家久等了 其实当天晚上整个人处于一种大胆后的发蒙状态,很多细节不太记得了,这个到时候让姐夫哥写。我平时也特别喜欢问他当时的视角和感觉,他说出一些我当时没注意甚至大相径庭的感受我觉得挺有意思的。 ———— 两性知识 | 两性知识「备」 树洞秘语 | 精品短片

2

9 Jun 2026, 03:58 UTC≈3,390 views1 reactionsread 7 August 2026
Photo

高阶撩妹法,学到4成直接强撩女神 🔗:https://pan.quark.cn/s/8b3d7c24b0f1 ———— 两性知识 | 两性知识「备」 树洞秘语 | 精品短片

1

9 Jun 2026, 01:15 UTC≈2,940 views3 reactionsread 7 August 2026
Video

三十几岁的男的找00后小姑娘谈爱或结婚的能是什么好东西吗? ———— 两性知识 | 两性知识「备」 树洞秘语 | 精品短片

🥰21

8 Jun 2026, 17:23 UTC≈4,000 views2 reactionsread 7 August 2026
Photo

soul上的色女还是比较多,可以用打直球的术来筛选这些妹子,我来写一下我常用的钓色女的99条文案,给大家做参考。 注意这类文案有违规风险,尽量隐晦表达。最好是人能看懂,但是ai看不懂。 配上身材照,身材照片也不要裸露,最好打码。不要原封不动使用,自己适当修改。 真心换真心,力度换声音。 耐力换音量,节奏换表情。 有些动静,比情更动听。 我的电池可是耐用型,撑得住长续航 拥抱换频率,汗水换晚安。 不要礼貌的边界,要超薄的危险。 别保持距离,我想超薄零距离。 别说距离产生美,我只要超薄 家里的电池续航不足,你会怎么办 当你让我躲床底那一刻我就知道,一个比我更有资格爱你的人来了 出来吃烧烤,这家店很特殊,必须带sfz 今天请你吃烧烤,前提是你先能吃冰 段位和你,我都想下 早上升起的不止有太阳 站着的时候吊着,坐着的时候靠着,走的时候摆着,跑的时候甩着,猜猜是什么 我的茶壶半小时水烧开,她们说这是好壶,你家的壶多长时间烧开 今天晚吃生蚝

2

8 Jun 2026, 17:23 UTC≈3,010 views5 reactionsread 7 August 2026

车 你忙的时候我就去爱别人,你不忙的时候我就拒绝所有人只爱你一个,你永远是我见一个爱一个里最爱的一个! 我:你处过几个男朋友 她:三四个吧 我:到底几个? 她:到底一个都没有 我弟弟他喜欢你很久了,特喜欢你迷离的眼睛,我说“人家那么漂亮,你配不上她,死了那条心吧”他气的脸红脖子粗,站立着的爆粗口,最后我掐着他脖子把他揍吐了,你说我做得对吗? 花径可曾缘客扫,蓬门今始为君开? 全校最帅的叫校草 那全球呢 wsxmg,sbhy,lgkyndjbcw,Igjbhd,cdwhs,cw,wsndxmg, sh,听说是情侣之间说的,我看了半天都没看懂,有人知道这些神秘代码什么意思吗? 脚踏两条船,迟早要翻船,脚踏多条船,翻都翻不完 爱一个女孩,不要让眼泪从眼睛里流出来。 在悉尼的时候遇见过一个奶奶,住在我隔壁。她人特别好,经常给我送一些她自己做的小零食,有什么困难也会帮助我。回国两年了,本来都快把她忘了,但是一看到你又想起来了,我想悉尼的奶

5

8 Jun 2026, 14:09 UTC≈2,090 views1 reactionsread 7 August 2026

应与心理韧性的考验:从贵州山区到繁华都市,洗脚妹们面对语言、习俗和人际差异,需快速适应客人需求与店规,同时应对潜在的误解或骚扰。她们在姐妹间寻找慰藉,却也学会提防竞争。这种韧性令人共鸣:底层打工者常在“边缘人”状态中挣扎,既保留乡村纯朴,又被迫练就城市生存智慧,体现了人性在压力下的弹性与脆弱。 8. 健康与青春代价的隐痛:长期接触药水、长时间站立或弯腰,导致手部皮肤问、腰背劳损和睡眠不足,是洗脚妹的常见职业病。她们年轻时用身体换取经济独立,却可能在30岁后面临健康隐忧。这条路径唤起共鸣:许多低端服务工作者都在“透支青春”换取家庭改善,提醒社会需更多关注职业保护,而非仅停留在收入数字上。 9. 社会流动的有限循环:部分洗脚妹存钱回乡开小店、结婚生子,或转行其他服务工作,形成“进城-积累-返乡”的循环。贵州女孩的经历常体现这种务实路径:不奢望大城市安家,却用双手为家乡注入新活力。但循环也有限,教育、户籍等壁垒让向上流动缓慢,这让无数

1

8 Jun 2026, 14:09 UTC≈1,950 viewsread 7 August 2026
Photo

为什么在全国足浴会所贵州技师数量最多: 1. 贫困山区的“第一桶金”出口:贵州许多农村家庭仍面临土地贫瘠、收入单一的困境,年轻女孩初中或高中毕业后,很难在家乡找到稳定工作。洗脚行业门槛低、包吃住、能快速寄钱回家,成为她们改变家庭命运的现实起点。这种选择虽辛苦,却承载着“先苦后甜”的朴素信念,让无数家庭从温饱线向上迈出一小步,却也折射出城乡差距下底层青年的无奈与韧性。 2. 外出务工潮中的性别分工:贵州作为劳务输出大省,男性多从事建筑、矿业等重体力活,而女性因身体条件和社会期望,更倾向于服务行业。足浴店需求稳定、分布广泛(从省内到沿海城市),自然吸纳大量年轻女性。这种“男工女服”的隐形分工,不是刻意安排,而是家庭经济压力下的默契分工,背后是无数母亲或姐姐用双手支撑起弟弟上学、父母养老的默默付出。 3. 教育资源不足的连锁反应:贵州部分山区教育基础设施相对薄弱,许多女孩早早辍学或学历停留在初中。洗脚妹工作不需要高文凭,只需勤快和基本

Showing the 12 most recent of 16 posts we hold for @liangxing1024. 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 — 220,682 of 1,151,006entries 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.

Mentions

Named by 7 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.

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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“两性知识「新」” (@liangxing1024), 2,923 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/liangxing1024.

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.