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Channel

搭建/开发/海胜演示

@dajianr

On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Cite this entry

30,498subscribers

-2,146 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001630155369
TypeChannel
Username@dajianr
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live28 October 2026
Measurements held52
Confirmed unchanged1 time, most recently 28 October 2026
On Telegramt.me/dajianr

Topic

Marketing & affiliate — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 44% 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

20,76435,71028,2377 August 2026 — 32,644 subscribers7 August 2026 — 32,221 subscribers8 August 2026 — 31,681 subscribers9 August 2026 — 31,260 subscribers10 August 2026 — 31,019 subscribers11 August 2026 — 30,226 subscribers13 August 2026 — 29,989 subscribers14 August 2026 — 28,409 subscribers15 August 2026 — 27,931 subscribers17 August 2026 — 26,698 subscribers18 August 2026 — 26,154 subscribers19 August 2026 — 25,543 subscribers20 August 2026 — 24,958 subscribers21 August 2026 — 24,103 subscribers23 August 2026 — 23,284 subscribers24 August 2026 — 22,614 subscribers25 August 2026 — 22,154 subscribers26 August 2026 — 21,775 subscribers27 August 2026 — 21,650 subscribers28 August 2026 — 21,346 subscribers29 August 2026 — 20,764 subscribers30 August 2026 — 22,970 subscribers31 August 2026 — 31,985 subscribers1 September 2026 — 31,822 subscribers1 September 2026 — 31,542 subscribers3 September 2026 — 31,112 subscribers5 September 2026 — 32,790 subscribers8 September 2026 — 32,054 subscribers11 September 2026 — 31,250 subscribers13 September 2026 — 35,033 subscribers14 September 2026 — 34,376 subscribers16 September 2026 — 33,278 subscribers18 September 2026 — 32,259 subscribers24 September 2026 — 35,710 subscribers3 October 2026 — 32,708 subscribers8 October 2026 — 30,441 subscribers12 October 2026 — 28,116 subscribers14 October 2026 — 27,364 subscribers15 October 2026 — 26,723 subscribers16 October 2026 — 26,531 subscribers17 October 2026 — 25,663 subscribers18 October 2026 — 25,326 subscribers19 October 2026 — 24,855 subscribers20 October 2026 — 24,151 subscribers21 October 2026 — 33,839 subscribers22 October 2026 — 33,139 subscribers23 October 2026 — 32,848 subscribers24 October 2026 — 32,148 subscribers25 October 2026 — 31,929 subscribers26 October 2026 — 31,227 subscribers27 October 2026 — 30,849 subscribers28 October 2026 — 30,498 subscribers30,4987 August 202628 October 2026
52 measurements spanning 82 days, net -2,146. 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 18,522–37,952 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 52
Measured (UTC)SubscribersChange
28 Oct 2026, 19:1030,498-351
27 Oct 2026, 19:2630,849-378
26 Oct 2026, 21:4031,227-702
25 Oct 2026, 18:1931,929-219
24 Oct 2026, 16:1532,148-700
23 Oct 2026, 16:0032,848-291
22 Oct 2026, 16:0933,139-700
21 Oct 2026, 14:0133,839+9,688
20 Oct 2026, 10:1724,151-704
19 Oct 2026, 06:5724,855-471
18 Oct 2026, 09:4025,326-337
17 Oct 2026, 07:1525,663-868
16 Oct 2026, 08:1826,531-192
15 Oct 2026, 07:4926,723-641
14 Oct 2026, 08:4427,364-752
12 Oct 2026, 16:4528,116-2,325
8 Oct 2026, 01:1830,441-2,267
3 Oct 2026, 15:2032,708-3,002
24 Sept 2026, 22:0135,710+3,451
18 Sept 2026, 16:4032,259first reading

Engagement

25 posts held, back to 14 July 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 141 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
6.23%
avg views ÷ 30,498 subscribers
Avg views / post
1,900
8 posts measured
Reaction rate
17.6%
reactions ÷ views · ER floor
Posts in window
9
of 25 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 21 October 2026
Posts held25 (14 July 2026 – 21 October 2026)
Views total15,209
Reactions total2,679
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Oct 2026, 05:14 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.

Reaction mix

10,679 reactions across 23 posts, in 15 distinct kinds. The most used accounts for 15.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🎉1,60915.1%
❤1,52014.2%
🔥1,49914.0%
👍1,47813.8%
😁9328.73%
🥰7006.55%
😍5975.59%
🤩5585.23%
❤‍🔥5445.09%
💯5234.90%
👏1801.69%
😘1621.52%
⚡1371.28%
🕊1361.27%
😎1040.974%

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 23 of the 25 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 10,679 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 25 most recent posts we hold, published 14 July 2026 to 21 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

21 Oct 2026, 16:18 UTC287 views312 reactionsread 28 October 2026
Photo

最新最好用的客服系统 官方认证 搭建联系:@haisheng888888

🕊66⚡49😘48🎉41🔥40😎27👍21🤩20

21 Oct 2026, 15:37 UTC250 views313 reactionsread 28 October 2026
Photo

音乐打榜伪商城系统/订单自动匹配/打码/代理后台 介绍 前端uniapp开发,后端vue,代理端vue,api是php的全开源 带代理后台,预设,打码,信用分等功能 搭建联系:@haisheng888888

😍71😘70😎46⚡33👍28🎉25❤21🕊19

21 Oct 2026, 15:24 UTC229 views314 reactionsread 28 October 2026
Photo

海外电影抢单刷单系统/连单卡单/充值返利/重置订单 介绍 新UI多语言电影刷单系统,前端uniapp开发后端php开源 功能支持:重置订单,充值返利,连单卡单,权限代理等 搭建联系:@haisheng888888

⚡55🎉51🕊51😘44🤩36😎31😍30👍16

8 Oct 2026, 06:24 UTC≈13,300 views308 reactionsread 21 October 2026
Photo

海胜开发技术团队 如需演示测试: 前台后台请联系技术 注:《支持担保交易-更安全更放心》 认准技术账号:@haisheng888888 宗旨:责任 诚信 共赢

👏49🎉46🔥46❤44🥰43👍41😁39

8 Oct 2026, 06:23 UTC388 views301 reactionsread 21 October 2026
Photo

海外音乐抢单刷单系统/卡单/重置订单/前端VUE 介绍 多语言音乐刷单系统,前后台VUE开发,api是PHP开源 功能支持卡单,重置订单,签到等功能 搭建联系:@haisheng888888

👍46❤42🥰37🎉36❤‍🔥32🔥28💯23🤩23

8 Oct 2026, 06:21 UTC263 views301 reactionsread 21 October 2026
Photo

海外奢饰品回收/劳力士商城/商品抢购/以旧换新/PC自适应 介绍 多语言奢饰品回收抢购系统,前端VUE后台php开源 支持用户前端提交产品以旧换新,商品抢购支持内定,实名认证,签到等功能 搭建联系:@haisheng888888

🎉47🥰46❤39🔥33👍31❤‍🔥23😍22💯20

1 Oct 2026, 19:32 UTC272 views416 reactionsread 7 October 2026
Photo

海外地图酒店投票系统/房型竞猜下注/酒店房型抢购 介绍 多语言酒店房型投票系统,前端uniapp后台代理VUE,服务端PHP开源 支持:打码,信用分,代理,预设等功能 搭建联系:@haisheng888888

🔥78❤75👍68😁68🎉67🥰31👏29

1 Oct 2026, 19:30 UTC220 views414 reactionsread 7 October 2026
Photo

多语言JAVA交易所/合约/期权/平台币/跟单/行情控制 介绍 新UI海外交易所系统,前端多语言VUE开发后台VUE服务端java开源 功能:合约,现货,期权,闪兑,跟单,理财,新币发售,平台币,行情控制等功能 搭建联系:@haisheng888888

🎉80❤71👍71😁65🔥61🥰39👏22💯2

24 Sept 2026, 14:41 UTC≈13,200 views421 reactionsread 1 October 2026
Photo

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🎉91❤87😁75🔥71👍68👏15🥰14

18 Sept 2026, 17:17 UTC375 views521 reactionsread 1 October 2026
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海外黄金秒合约交易/黄金时间盘/黄金微盘投资交易 介绍 新版UI黄金微盘系统,前端uniapp开发,后台VUE开发,api端php全开源 功能:输赢控制,信用分,实名认证,注册赠送,分享推广等功能 搭建联系:@haisheng888888

❤99👍97🎉86😁85🔥81👏25🥰21❤‍🔥9

18 Sept 2026, 17:16 UTC347 views545 reactionsread 1 October 2026
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海外欧美空降秒合约/同城任务约炮/实名认证/信用分 介绍 新版多语言欧美秒合约空降,前端VUE后端PHP开源 功能支持:秒合约交易,输赢控制,实名认证,信用分等功能 搭建联系:@haisheng888888

❤102🔥96🎉88👍83😁73🥰25❤‍🔥20😍17

Showing the 12 most recent of 25 posts we hold for @dajianr. 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.

Posts edited after publishing

@dajianr edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
6 September 2026
Most recent edit
6 September 2026

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 28 October 2026 — this entry's latest reading, not the date you are reading this.

“搭建/开发/海胜演示” (@dajianr), 30,498 subscribers as measured 28 October 2026. Telegram Register, tgregister.com/channel/dajianr.

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.