Telegram RegisterThe public register of Telegram
Telegram profile photo for G7环球|官方福利俱乐部

Supergroup

G7环球|官方福利俱乐部

@wwwG7com

2 usernames

On this record: Topic · Growth · Engagement · Citations · Cite this entry

4,333members

-1,145 since we began measuring on 6 August 2026

769 online right now

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

Register entry

Telegram ID-1003890940987
TypeSupergroup
Usernames@g7345 @wwwG7com
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded3 September 2026
Last confirmed live18 September 2026
Measurements held19
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/wwwG7com

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 55% 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

4,2745,4784,8766 August 2026 — 5,478 members7 August 2026 — 5,433 members9 August 2026 — 5,265 members12 August 2026 — 5,175 members16 August 2026 — 5,024 members19 August 2026 — 4,891 members22 August 2026 — 4,823 members25 August 2026 — 4,753 members28 August 2026 — 4,715 members31 August 2026 — 4,573 members2 September 2026 — 4,492 members3 September 2026 — 4,492 members4 September 2026 — 4,464 members6 September 2026 — 4,399 members10 September 2026 — 4,339 members11 September 2026 — 4,274 members13 September 2026 — 4,506 members15 September 2026 — 4,362 members18 September 2026 — 4,333 members4,3336 August 202618 September 2026
19 measurements spanning 43 days, net -1,145. 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 4,093–5,659 and does not start at zero.
Measurement log — every members count we have recorded
Measured (UTC)MembersChange
18 Sept 2026, 04:004,333-29
15 Sept 2026, 17:204,362-144
13 Sept 2026, 21:194,506+232
11 Sept 2026, 14:584,274-65
10 Sept 2026, 03:554,339-60
6 Sept 2026, 20:004,399-65
4 Sept 2026, 11:174,464-28
3 Sept 2026, 13:004,492no change
2 Sept 2026, 16:574,492-81
31 Aug 2026, 00:034,573-142
28 Aug 2026, 02:374,715-38
25 Aug 2026, 09:324,753-70
22 Aug 2026, 14:224,823-68
19 Aug 2026, 12:254,891-133
16 Aug 2026, 03:275,024-151
12 Aug 2026, 07:545,175-90
9 Aug 2026, 17:515,265-168
7 Aug 2026, 00:175,433-45
6 Aug 2026, 04:065,478first reading

Engagement

Posts not read yet. This entry is on the register from its profile alone; the post reader has not reached it. Engagement figures appear here once posts have actually been measured — we do not publish a rate before we have the readings behind it.

Mentions

Named by 146 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

Named by

Channels on the register whose posts name this channel's handle.

📣东南亚大事件 | 菲律宾新闻
@PH_CCTVV · 102,552
73 posts
东南亚头条
@baoguangchn · 48,901
65 posts
东南亚大事件|华人新闻|热点爆料
@SEAUPD · 26,245
65 posts
菲律宾华人大事件
@ke5689 · 167,871
64 posts
东南亚悬赏曝光
@xnuax · 54,871
63 posts
柬埔寨二手市场|二手市场|手机电脑|公寓出租
@JBRSSC · 61,901
62 posts
东南亚曝光频道
@BG2288 · 81,773
54 posts
柬埔寨租车|西港租车|二手车买卖
@xigangche · 48,685
50 posts
柬埔寨甩人|西港招聘|金边招聘
@JPZSR · 65,641
49 posts
木牌大事件|东南亚新闻
@mpdsj · 123,959
49 posts
木姐新闻|缅甸新闻 |东南亚新闻 吃瓜群
@TGuhuuq · 15,544
48 posts
🌍全球(菲 柬 迪 泰 缅 老挝) 求职频道
@FJD666666 · 93,775
43 posts
东南亚大事件日记/今日头条 曝光-悬赏
@dny26i · 230,001
42 posts
亚太新闻 亚太曝光 亚太吃瓜 亚太茶水间
@zh_cnshk · 96,310
42 posts
东南亚大事件 东南亚新闻 西港日记 亚太新闻
@dny336 · 217,285
41 posts
东南亚大事件 东南亚新闻 柬埔寨新闻
@dny66i · 230,476
41 posts
东南亚大事件-吃瓜中心-曝光悬赏
@dny88i · 230,498
41 posts
东南亚曝光台☎️
@DNYBG234 · 93,361
41 posts
东南亚-奇趣百科.搞笑视频
@svip956 · 32,950
41 posts
西港二手|二手家具|手机电脑|公寓出租
@xigangdsj · 68,997
41 posts
东南亚🌍安危大事件 (💋菲 柬 迪 泰 缅 老挝💋)爆料
@quanqiubaoliao · 186,631
40 posts
灰色东南亚吃瓜曝光
@huisedny · 64,320
39 posts
柬埔寨大事件|新闻曝光|安危头条
@JPZDSJ · 199,537
39 posts
全网大事件吃瓜曝光
@quanwangdsj · 62,934
39 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“G7环球|官方福利俱乐部” (@wwwG7com), 4,333 members as measured 18 September 2026. Telegram Register, tgregister.com/channel/wwwG7com.

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.