———————————————— 🔻河北🔻 石家庄1100 https://t.me/shijiazhuang688 唐山770 https://t.me/+iu7_xABp1aozNDk1 秦皇岛300 https://t.me/+CS7-RJo6f5hlYmQ1 邯郸930 https://t.me/+PV2CXmJiH9RhMzU1 邢台700 https://t.me/+aiL15PMq6xszNzQ1 保定920 https://t.me/+jDAOtU8WCFFlOTA0 张家口400 https://t.me/+AfofB9mmaullNDI1 承德330 https://t.me/+f_1QNOys5_I5YjE9 沧州730 https://t.me/+JgRbZRWO8f5lZTI9 廊坊550 https://t.me/+71z05mOLR9A4NjA0 衡水420 h…

Channel
北京-天津-河北-河南资源
@zhongyuan6699
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
20subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1002921833380 |
|---|---|
| Type | Channel |
| Username | @zhongyuan6699 |
| Created | 21 October 2025 — measured — dated from the channel’s first post |
| First recorded | 11 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/zhongyuan6699 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 10:39 | 20 | -1 |
| 1 Sept 2026, 06:35 | 21 | +1 |
| 24 Aug 2026, 08:07 | 20 | +1 |
| 16 Aug 2026, 17:27 | 19 | -1 |
| 11 Aug 2026, 15:45 | 20 | no change |
| 7 Aug 2026, 16:18 | 20 | first reading |
Engagement
5 posts held, back to 21 October 2025 — 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 5 posts for this entry, the most recent from 22 October 2025. An engagement rate over an empty window would be a number about nothing.
Reaction mix
3 reactions across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3 | 100.0% |
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 1 of the 5 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 5 most recent posts we hold, published 21 October 2025 to 22 October 2025, 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
———————————————— 🔻河南🔻 郑州1300 https://t.me/zhengzhou6868 洛阳700 https://t.me/+wgbCoviXqwhhZDBl 南阳960 https://t.me/+FoI8vsnBM29lZTBl 新乡610 https://t.me/+X1fateYRmOs5ZTQ0 周口880 https://t.me/+GsrJ0Dhv6cc3MmM1 商丘770 https://t.me/+P-YfUCYR0MQ0MTY0 信阳960 https://t.me/+H0mlj9YHoLA4M2I1 驻马店690 https://t.me/+N61XffIAQP8yOTNl 安阳550 https://t.me/+lcXM44c_WCU1MGFk 开封480 https://t.me/+9ciUVRN1jD40MmRk 许昌430 https:…
❤3
———————————————— 🔻北京-天津🔻 北京2185:@beijinnng888 天津1360:@tianjinn889 ————————————————
Channel photo updated
Channel created
Showing the 5 most recent of 5 posts we hold for @zhongyuan6699. 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.
Mentions
Named by 1 registered channel — 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.
Named by
Channels on the register whose posts name this channel's handle.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“北京-天津-河北-河南资源” (@zhongyuan6699), 20 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/zhongyuan6699.
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.