Channel
@lanlan99231
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
151subscribers
+4 since we began measuring on 11 September 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003861695675 |
|---|---|
| Type | Channel |
| Username | @lanlan99231 |
| Created | 16 March 2026 — measured — dated from the channel’s first post |
| First recorded | 11 September 2026 |
| Last confirmed live | 13 September 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 13 September 2026 |
| On Telegram | t.me/lanlan99231 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Sept 2026, 11:00 | 151 | +4 |
| 11 Sept 2026, 21:22 | 147 | no change |
| 11 Sept 2026, 20:47 | 147 | first reading |
15 posts held, back to 16 March 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 2 of 14 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 September 2026 |
|---|---|
| Posts held | 15 (16 March 2026 – 3 September 2026) |
| Views total | 2,552 |
| Reactions total | 2 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Sept 2026, 21:22 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.
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 2 of the 15 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 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 16 March 2026 to 3 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.
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Signed Saber
姨妈来了休息 哥哥们
Signed 辛子（零零后个人兼职）
下班了
Signed 辛子（零零后个人兼职）
Sticker, posted without a caption
Signed 辛子（零零后个人兼职）
【广州茶馆】：https://t.me/gzcg9 【时间】：2026-09-02 【老师】：辛子 【账号】：@yueyue20071 【留名】：匿名 【颜值】：不错，能看出是照片上的轮廓，带妆蛮悦眼。 【身材】：很好，挺拔，皮肤紧致光滑，身高有165， 【罩杯】：挺，紧实，手小点的话一手握不小 【服务】：嫩妹，各项都有点生疏，口的时候看出是在下决心才有动作，但算是听话。 【态度】：蛮好，开始以为是i人，聊两句后有问有答开始熟络 【位置】：交通方便，公寓 【评分】：8 【过程】：提前约了妹子，晚上按时到达，指示清晰。上楼找房间，提前留了门。进去后见到本人挺拔的身材，笔直的长腿，立刻决定留下。过程服务与课表基本一致，简单嫩妹服务，有青涩感😍 妹子乳房敏感，能看出有真实反应😄 开始进入时妹子怕疼，会有手挡着，过会儿就放开了。过程中呻吟自然，遗憾的是不太会骚话。 整体过程蛮享受的。 缺点，路上聊天的感觉有些怀疑是代聊，但见面后看着又像…
Signed 辛子（零零后个人兼职）
下班了可提前预约明天的课
Signed 辛子（零零后个人兼职）
🈵
Signed 辛子（零零后个人兼职）
🈶🈳
❤1
Signed 辛子（零零后个人兼职）
开课
Signed 辛子（零零后个人兼职）
🈳
Signed 辛子（零零后个人兼职）
Sticker, posted without a caption
Signed 辛子（零零后个人兼职）
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❤1
Signed Saber
Showing the 12 most recent of 15 posts we hold for @lanlan99231. 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.
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.
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.
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 13 September 2026 — this entry's latest reading, not the date you are reading this.
“辛子🏠” (@lanlan99231), 151 subscribers as measured 13 September 2026. Telegram Register, tgregister.com/channel/lanlan99231.
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.