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Channel

Fang的资源分享群

@FLMdongtianfudi

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

29,167subscribers

+2,015 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002365950566
TypeChannel
Username@FLMdongtianfudi
Description一个综合类的资源分享频道,每天分享有趣、有用的网站、软件、工具、应用、小说、影视等等 网盘资源: t.me/FLMdongtianfudi 资源搜索群: t.me/FLMziyuansousuo Twitter: x.com/FLMdongtianfudi 投稿/广告/合作请留言: @Fangtiann_bot
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live18 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/FLMdongtianfudi

Topic

Software piracy — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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

27,15229,16728,159.56 August 2026 — 27,152 subscribers7 August 2026 — 27,163 subscribers8 August 2026 — 27,215 subscribers9 August 2026 — 27,275 subscribers10 August 2026 — 27,330 subscribers11 August 2026 — 27,380 subscribers12 August 2026 — 27,443 subscribers13 August 2026 — 27,507 subscribers14 August 2026 — 27,594 subscribers16 August 2026 — 27,734 subscribers17 August 2026 — 27,827 subscribers18 August 2026 — 27,891 subscribers19 August 2026 — 27,942 subscribers20 August 2026 — 27,991 subscribers21 August 2026 — 28,051 subscribers23 August 2026 — 28,126 subscribers24 August 2026 — 28,233 subscribers25 August 2026 — 28,292 subscribers27 August 2026 — 28,356 subscribers28 August 2026 — 28,421 subscribers29 August 2026 — 28,460 subscribers30 August 2026 — 28,572 subscribers31 August 2026 — 28,621 subscribers1 September 2026 — 28,650 subscribers2 September 2026 — 28,673 subscribers3 September 2026 — 28,732 subscribers4 September 2026 — 28,820 subscribers8 September 2026 — 28,988 subscribers11 September 2026 — 29,087 subscribers13 September 2026 — 29,122 subscribers14 September 2026 — 29,135 subscribers16 September 2026 — 29,148 subscribers18 September 2026 — 29,167 subscribers6 August 202618 September 2026
33 measurements spanning 43 days, net +2,015. 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 26,850–29,469 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
18 Sept 2026, 12:3929,167+19
16 Sept 2026, 08:2129,148+13
14 Sept 2026, 17:3829,135+13
13 Sept 2026, 00:5729,122+35
11 Sept 2026, 00:4029,087+99
8 Sept 2026, 02:5728,988+168
4 Sept 2026, 22:5928,820+88
3 Sept 2026, 06:4528,732+59
2 Sept 2026, 03:0428,673+23
1 Sept 2026, 06:1728,650+29
31 Aug 2026, 04:0828,621+49
30 Aug 2026, 04:3528,572+112
29 Aug 2026, 03:3428,460+39
28 Aug 2026, 06:5228,421+65
27 Aug 2026, 03:2628,356+64
25 Aug 2026, 23:5728,292+59
24 Aug 2026, 20:4528,233+107
23 Aug 2026, 04:3528,126+75
21 Aug 2026, 19:3428,051+60
20 Aug 2026, 19:0727,991first reading

Engagement

431 posts held, back to 5 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 125 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.26%
avg views ÷ 29,167 subscribers
Avg views / post
659
183 posts measured
Reaction rate
0.141%
reactions ÷ views · ER floor
Posts in window
183
of 431 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 64 of 183 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 27 September 2026
Posts held431 (5 August 2026 – 27 September 2026)
Views total120,517
Reactions total64
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken27 Sept 2026, 08:38 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
≈13,900
Videos
≈78
Links
≈14,000

Lifetime counters from Telegram’s own channel header, read 27 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
2h 13m
Average length
11m 06s

Measured directly from 12 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

159 reactions across 123 posts, in 6 distinct kinds. The most used accounts for 53.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤8553.5%
👍6842.8%
🔥31.89%
👎10.629%
😁10.629%
🤔10.629%

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 148 of the 431 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 159 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 431 most recent posts we hold, published 5 August 2026 to 27 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.

Recent posts

27 Sept 2026, 04:30 UTC249 viewsread 27 September 2026
Photo

🔍 超级搜索 TG必备搜索神器,帮你精准找到,想要的群组,频道,视频,音乐。 👇👇 点击下方按钮,进行搜索!

27 Sept 2026, 04:02 UTC275 viewsread 27 September 2026

#频道互推 #群组推荐 DLsite Steam黄油下载 白丝雪糕anime(表频道) 书墨资源|图文影音课程软件 精选音乐收藏馆 优质-破解软件-分享基地 无损音乐分享频道 精选壁纸美图|风景美人acg 折腾IOS内测|限免频道 知识分享官 弈泽 - 审计级财报分析系统

26 Sept 2026, 13:02 UTC790 viewsread 27 September 2026
Photo

耗时2年精心收集,抖音顶级小姐姐精品切片 资源为耗时两年收集整理的抖音顶级小姐姐精品切片,含32000部短视频精选内容,适合日常浏览和休闲观看,方便集中查看。 🔗:https://pan.quark.cn/s/a31aff6c4443 #抖音切片 #精品合集 #短视频资源 #休闲观看 #资源整理 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 13:01 UTC704 viewsread 27 September 2026
Photo

海外短剧200+大合集吐血整理 收录200部海外午夜擦边短剧大合集,总277G,适合短剧爱好者深夜观看与收藏,方便集中获取稀缺资源。 🔗:https://pan.quark.cn/s/df544604f7ff #海外短剧 #短剧合集 #资源合集 #午夜短剧 #稀缺资源 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:55 UTC644 views1 reactionsread 27 September 2026
Photo

云析 云析是一款支持多个网盘的解析下载软件,可解析网盘文件并下载到本地。适合需要更方便获取网盘资源的场景,帮助完成下载流程。 🔗:https://pan.quark.cn/s/b375e6d2eeeb #网盘解析 #网盘下载 #解析下载 #多网盘支持 #云析 🔔Twitter 👥 频道 💬 群组

❤1

26 Sept 2026, 12:53 UTC598 viewsread 27 September 2026
Photo

街拍视频魔镜街拍 资源为魔镜街拍相关内容,包含高画质街拍3000张,适合街拍风格参考、选图与素材整理,方便日常浏览和取用。 🔗:https://pan.quark.cn/s/f8d2b70497c9 #街拍 #魔镜街拍 #高画质 #素材 #图片素材 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:48 UTC564 viewsread 27 September 2026
Photo

赚钱APP 趣汇看广告赚钱APP,通过观看广告完成任务获取收益,任务非常多,适合碎片时间操作,帮助了解参与流程。 🔗:https://pan.quark.cn/s/e3fb568a7aa5 #趣汇 #看广告赚钱 #任务多 #碎片时间 #手机赚钱 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:48 UTC532 views0 reactionsread 27 September 2026
Photo

图片搜索引擎 一个据称高精度的日本AV识图引擎,通过图片搜索查找相关出处,适合需要识别图片来源或寻找相似内容的场景,帮助快速定位参考信息。 🔗:https://pan.quark.cn/s/24c032c91518 #图片搜索 #识图引擎 #资源查找 #工具推荐 #亲测可用 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:44 UTC521 views0 reactionsread 27 September 2026
Photo

抖音图文问答类玩法,几分钟一条轻松撸伙伴计划 介绍抖音图文问答类玩法的操作流程,适合想利用碎片时间制作图文问答内容的伙伴计划参与者参考,帮助快速理解选题、配图与发布思路。 🔗:https://pan.quark.cn/s/0bc905c08125 #抖音图文 #问答玩法 #伙伴计划 #内容创作 #短视频运营 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:44 UTC507 views1 reactionsread 27 September 2026
Photo

《万物皆模型:85个思维模型》图解 《万物皆模型:85个思维模型》图解用图示方式梳理85个思维模型,适合学习、工作和决策时查阅,帮助拓宽思考角度、理清问题结构并辅助分析。 🔗:https://pan.quark.cn/s/98257bdd2f3b #思维模型 #图解 #认知提升 #学习方法 #决策分析 🔔Twitter 👥 频道 💬 群组

❤1

26 Sept 2026, 12:44 UTC494 viewsread 27 September 2026
Photo

厦门湖明小学 本资源围绕厦门湖明小学相关信息进行整理,适合想了解该校基本情况或查找相关内容的用户作为日常参考使用。 🔗:https://pan.quark.cn/s/ff5114f873d9 #厦门湖明小学 #学校信息 #小学教育 #本地资讯 #参考资料 🔔Twitter 👥 频道 💬 群组

26 Sept 2026, 12:44 UTC486 views1 reactionsread 27 September 2026
Photo

2026AI音乐实战课程,零基础从零学Suno编曲、混音优化、声音克隆、版权注册,覆盖多风格歌曲创作与账号变现 围绕Suno的AI音乐实战课,带你从零走通编曲、混音优化、声音克隆与版权注册流程,覆盖多风格歌曲创作,并讲解账号运营变现思路,适合零基础想用AI做歌的人。 🔗:https://pan.quark.cn/s/9380386bb253 #AI音乐 #Suno #编曲混音 #声音克隆 #音乐变现 🔔Twitter 👥 频道 💬 群组

❤1

Showing the 12 most recent of 431 posts we hold for @FLMdongtianfudi. 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“Fang的资源分享群” (@FLMdongtianfudi), 29,167 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/FLMdongtianfudi.

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.