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Channel

深圳福田-林灿的恋爱小窝休息🀄

@FTlchome

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

6,012subscribers

+2,243 since we began measuring on 24 August 2026

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

Register entry

Telegram ID-1001373354493
TypeChannel
Username@FTlchome
CreatedBetween 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded24 August 2026
Last confirmed live4 November 2026
Measurements held19
Confirmed unchanged1 time, most recently 4 November 2026
On Telegramt.me/FTlchome

Topic

Other / unclassifiable — 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 13 September 2026 and assigned it the closest of 31 fixed categories, at 58% 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 the other topics.

Growth

3,7696,0224,895.524 August 2026 — 3,769 subscribers24 August 2026 — 3,769 subscribers25 August 2026 — 3,811 subscribers28 August 2026 — 3,950 subscribers31 August 2026 — 4,198 subscribers3 September 2026 — 4,395 subscribers8 September 2026 — 4,488 subscribers12 September 2026 — 4,519 subscribers16 September 2026 — 4,541 subscribers30 September 2026 — 5,291 subscribers6 October 2026 — 5,692 subscribers13 October 2026 — 5,876 subscribers16 October 2026 — 5,937 subscribers19 October 2026 — 5,970 subscribers22 October 2026 — 5,987 subscribers26 October 2026 — 6,000 subscribers29 October 2026 — 6,018 subscribers31 October 2026 — 6,022 subscribers4 November 2026 — 6,012 subscribers6,01224 August 20264 November 2026
19 measurements spanning 72 days, net +2,243. 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 3,431–6,360 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
4 Nov 2026, 00:096,012-10
31 Oct 2026, 18:576,022+4
29 Oct 2026, 00:176,018+18
26 Oct 2026, 00:216,000+13
22 Oct 2026, 20:575,987+17
19 Oct 2026, 21:295,970+33
16 Oct 2026, 16:265,937+61
13 Oct 2026, 07:555,876+184
6 Oct 2026, 21:545,692+401
30 Sept 2026, 00:585,291+750
16 Sept 2026, 00:584,541+22
12 Sept 2026, 13:394,519+31
8 Sept 2026, 21:374,488+93
3 Sept 2026, 20:424,395+197
31 Aug 2026, 08:174,198+248
28 Aug 2026, 00:043,950+139
25 Aug 2026, 03:363,811+42
24 Aug 2026, 07:003,769no change
24 Aug 2026, 06:453,769first reading

Engagement

21 posts held, back to 19 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 4 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
49.7%
avg views ÷ 6,012 subscribers
Avg views / post
2,990
9 posts measured
Reaction rate
0.136%
reactions ÷ views · ER floor
Posts in window
9
of 21 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 6 of 9 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 20 October 2026
Posts held21 (19 August 2026 – 20 October 2026)
Views total26,870
Reactions total25
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken5 Nov 2026, 02:00 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

Photos
125
Videos
13
Links
55

Lifetime counters from Telegram’s own channel header, read 5 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
41s
Average length
8s

Measured directly from 5 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

42 reactions across 9 posts, in 7 distinct kinds. The most used accounts for 66.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤2866.7%
🔥49.52%
👏37.14%
🥰37.14%
😭24.76%
🍓12.38%
👍12.38%

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 14 of the 21 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 42 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 19 August 2026 to 20 October 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

Telegram’s own ‘edited’ marker: 2 of 9 posts held from the last 30 days (22.2%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

20 Oct 2026, 06:29 UTC≈2,400 views0 reactionsread 5 November 2026
Photo

休假🀄-可以先找好闺蜜奶糖 一线天白虎馒头比 36D蜜桃臀 A4腰马甲线三点粉 少数民族 她的光环实在太多 请亲自体会 冲: https://t.me/+mgb6RQVl3E42NzI1

12 Oct 2026, 03:27 UTC≈4,170 views8 reactionsread 5 November 2026
Photo

《请假条》 我想赎回 我自己了 频道的信息是安静的 但我的呼吸是满的 我要赖床 泡茶 翻书 逗猫 晒太阳 把所有被叫作浪费的事 心安理得做一遍 也愿大家忙碌有度 喜乐如常 休息🀄 开课时间留意频道动态哦 私聊:@FTlincan 双向:@FTlincanbot

❤4👏3🥰1

12 Oct 2026, 02:52 UTC≈3,560 views1 reactionsread 5 November 2026

报告模版 【学生留名】: 洛佩斯 【验证老师】: 林灿 【验证老师】: @FTlincan 【上课时间】: 10🈷️中 【本人跟照片比较如何】: 人比照片还好看 【吸引你的点】: 高颜身材顶,床上骚 【她不足的点】: 🈚🐍 【课室环境如何】: 挺温馨的,课室2室一厅。 【过程描述】: N返林灿,一样的高颜。一样床下i人,床上荡妇 【硬件情况】 以前已表,不赘述,简单概括, 纯欲顶级颜值,蜂腰,翘臀。大熊。筷子腿。 本次见🈶白了2个度。更加冷白皮了,极致白皮上3点娇嫩欲滴的粉点,让人看了就硬了,都无需前戏 衣品:稍微有点提高,没穿毛领裙子。穿了黑体恤和齐屁包臀裙。建议以后穿个紧致的吊带包臀连衣裙,更佳,保准来的人挪不开眼睛。 【软件评价】 情绪价值服务技术: 进门出门陪浴。给洗澡巾,漱口讲究卫生。陪浴仔细认真。毕竟比较熟悉了,会聊聊近况。不会像初见一样。就我自己在叭叭,她就在倾听,熟悉了有来有回。慢热型, 一到…

❤1

11 Oct 2026, 03:42 UTC≈2,780 views7 reactionsread 5 November 2026
Photo

12号上完休息啦 最后两天宝宝们~ 私聊:@FTlincan 双向:@FTlincanbot

❤4🔥2😭1

11 Oct 2026, 03:40 UTC≈2,670 viewsread 5 November 2026

超跑出击报告 花名:林灿 城市:深圳 区域:福田 私聊:@FTlincan 日期:2026-10-11 评价:10条(含报告) 出击体验:哇!很不错哦 邻家妹妹的感觉、进门看到跟照片差不多,美颜很正常啦、但是没有p过,灿灿很客气哦,笑脸相迎,温柔抱抱,拿拖鞋,拿水,一次性浴巾备好,接下来就是一起洗澡,她的胸挺拔不下垂,看起来又很养眼,之后帮我擦干水去了床上,这个时候小弟弟已经顶不住了😂,摸了一下,湿哒哒,这个时候我已经迫不及待的想进入,她又附身帮我吹,我差点都爆了,哈哈哈,我叫赶紧给我带套、中途我换了好几个之势都很配合、从后面我就没坚持住了交货了,因为很紧,水多,妹妹反差很大,骚骚的,我还会再来 查看照片 更多报告/评价

10 Oct 2026, 05:26 UTC≈2,630 views4 reactionsread 5 November 2026
Photo

花名:林灿 坐标:#福田 课费:1300p 2500pp 私聊:@FTlincan 双向:@FTlincanbot 评价:9条 (含报告) 在榜:1个月 ━━━━━━━━━━━━━━ 标签:#兼职 #模特 #00后 #高颜 #美臀 #长腿 #马甲线 #冷白皮 ━━━━━━━━━━━━━━ 流程:沟通→ 预约 → 核验 → 评价 ✅预约是争议处理凭证 ━━━━━━━━━━━━━━ 【📅 我要预约】 【💬 查看主页/评价】 【🚨 我要投诉】 【👥 群 @chaopao】

🔥2❤1🥰1

9 Oct 2026, 04:16 UTC≈3,060 viewsread 5 November 2026

超跑出击报告 花名:林灿 城市:深圳 区域:福田 私聊:@FTlincan 日期:2026-10-09 评价:9条(含报告) 出击体验:进门就看见林灿老师笑容,老师着短裙,吊带,身材超级好,大白兔漏了一大半在外面,清爽诱人,身高168🐻蛮大,给人感觉可纯可御,颜值顶级,皮肤水嫩白皙,臀部肥美,这说什么,特别和我的口味,付费开餐,一起洗澡,反馈很强烈,不敢想一会口二弟啥感觉,大白兔的质感让我爱不释手,真熊软乎不失弹性,到床上,开始进入主题,过程就不描述了,叫床声音好听,配合叫男人都喜欢听的称呼,具体各位狼友亲测,我就不多描述了,反正绝对你让情趣价值拉满,让你流连忘返,本人肯定会二刷的 优点缺点:蜜桃臀,做爱圣体 查看照片 更多报告/评价

8 Oct 2026, 07:11 UTC≈2,800 views5 reactionsread 5 November 2026
Photo

我只求与你共华发😍 12号休息啦 倒计时五天 私聊:@FTlincan 双向:@FTlincanbot

❤3🍓1😭1

7 Oct 2026, 16:50 UTC≈2,800 viewsread 5 November 2026

才上线,还是得说,你真的很漂亮,从来没见过你这么漂亮的女孩子,比什么迪丽热巴和娜扎都好看,特好看😘😘😘

6 Oct 2026, 15:20 UTC≈3,490 views3 reactionsread 5 November 2026
Forwarded from @baogaohuajianji

百花名录报告模板 { https://t.me/huaxufengnan } 位置坐标: 福田 验证留名: tg第一哥布林 上课时间: 10月4日 老师名字: 林灿 联系方式: @FTlincan 上课花费: 1300/p 颜值: 10/10 身材: 10/10 胸: 9/10 腰: 10/10 腿: 10/10 服务态度:10/10 爱爱体验: 10/10 情绪价值: 9/10 课室环境: 9/10 人照相似度:9/10 体验过程补充: 老师最近很火,马上就约上了。准时到楼下,顺利上楼。看到ls第一眼,又瘦又苗条,颜值很高。ls穿着齐b包臀,下面真空,直接看到bb,反差感拉满。交课费洗澡,回到床上,开口,很刺激。站着又口了一会儿,带t开干。房间内有个小镜子,ls胸很大,奶头粉色,一边抓奶一边后入,很刺激。ls叫声很…

❤2👍1

6 Oct 2026, 10:37 UTC≈2,870 views0 reactionsread 5 November 2026

一开始以为说像迪丽热巴是吹牛,结果是真的(个人感觉更像古力娜扎),太美了🫡

Showing the 12 most recent of 21 posts we hold for @FTlchome. 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

Named by 3 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 4 November 2026 — this entry's latest reading, not the date you are reading this.

“深圳福田-林灿的恋爱小窝休息🀄” (@FTlchome), 6,012 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/FTlchome.

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.