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Telegram profile photo for 乐蛙影视站-频道

Channel

乐蛙影视站-频道

@qingyuexuan

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

4,697subscribers

+1,708 since we began measuring on 2 September 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003757779116
TypeChannel
Username@qingyuexuan
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded2 September 2026
Last confirmed live19 September 2026
Measurements held6
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/qingyuexuan

Topic

Film & TV — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 19 September 2026 and assigned it the closest of 31 fixed categories, at 83% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

2,9894,6973,8432 September 2026 — 2,989 subscribers2 September 2026 — 2,989 subscribers6 September 2026 — 4,335 subscribers11 September 2026 — 4,524 subscribers14 September 2026 — 4,623 subscribers19 September 2026 — 4,697 subscribers2 September 202619 September 2026
6 measurements spanning 17 days, net +1,708. 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 2,733–4,953 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
19 Sept 2026, 02:224,697+74
14 Sept 2026, 23:204,623+99
11 Sept 2026, 10:414,524+189
6 Sept 2026, 16:004,335+1,346
2 Sept 2026, 03:152,989no change
2 Sept 2026, 03:002,989first reading

Engagement

16 posts held, back to 10 August 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
26.0%
avg views ÷ 4,697 subscribers
Avg views / post
1,220
4 posts measured
Reaction rate
0.132%
reactions ÷ views · ER floor
Posts in window
4
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. It is computed over the 3 of 4 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 31 August 2026
Posts held16 (10 August 2026 – 31 August 2026)
Views total4,880
Reactions total5
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Sept 2026, 03:15 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
18s
Average length
18s

Measured directly from 1 video 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

91 reactions across 9 posts, in 8 distinct kinds. The most used accounts for 65.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍6065.9%
❤1213.2%
🤡1213.2%
💩22.20%
🔥22.20%
💯11.10%
😁11.10%
😱11.10%

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 11 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 91 reactions 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 10 August 2026 to 31 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

31 Aug 2026, 10:13 UTC≈1,100 views2 reactionsread 2 September 2026

是时候研究研究月卡价格了,保留公益签到的前提下

👍2

30 Aug 2026, 00:22 UTC≈1,130 views1 reactionsread 2 September 2026
Photo

目前本地文件出现了堆积现象,优先处理本地堆积文件-求片先放一放

❤1

28 Aug 2026, 10:59 UTC≈1,550 views2 reactionsread 2 September 2026

收留佬友记难民 免费收 公益签到即可 每日签到,积分续费 逐梦不停,初心不改,我们暂别不散,静待归来之时。(期待佬友记满血复活)

❤2

27 Aug 2026, 09:14 UTC≈1,730 viewsread 2 September 2026

1美团黑钻黑金会员送你原味圆筒冰淇淋❤️复制整条信息,打开👉美团👈 http:/💰70MTkwYTM2MGQ💰

27 Aug 2026, 08:19 UTC≈1,120 views0 reactionsread 2 September 2026
Forwarded from @fdd_JSBPhoto

如果以后遇到有人给你发 你好,在吗,在不在,就把这本书发给他。 https://pan.quark.cn/s/3ee65e97b6ff #学会提问 #工具

26 Aug 2026, 15:50 UTC≈1,570 viewsread 2 September 2026
Photo

不知道是那个程序内存溢出导致死机 正常排查

22 Aug 2026, 09:47 UTC≈3,070 views0 reactionsread 2 September 2026

https://t.me/+H1QwtTTQRmc5ZDA1 白名单用户可以直接入群了

20 Aug 2026, 09:17 UTC≈2,990 views3 reactionsread 2 September 2026
File

全体欣赏音乐,声音略小,建议多点声音

💩2😱1

17 Aug 2026, 07:23 UTC≈2,260 views45 reactionsread 2 September 2026

乐蛙准备在保留公益签到的基础上,新增月卡、月卡定价10R-15R 不知各位意下如何

👍42❤2🔥1

16 Aug 2026, 14:51 UTC≈2,170 views13 reactionsread 2 September 2026
Video

Video, posted without a caption

🤡12💯1

Showing the 12 most recent of 16 posts we hold for @qingyuexuan. 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

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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“乐蛙影视站-频道” (@qingyuexuan), 4,697 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/qingyuexuan.

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.