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Channel
野寻 · 深圳活动公告
@chasesz_hdgg
On this record: Topic · Growth · Engagement · Reactions · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
12,319subscribers
+6,905 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 | -1002354913323 |
|---|---|
| Type | Channel |
| Username | @chasesz_hdgg |
| Created | 17 December 2024 — measured — dated from the channel’s first post |
| First recorded | 6 August 2026 |
| Last confirmed live | 8 November 2026 |
| Measurements held | 47 |
| Confirmed unchanged | 1 time, most recently 8 November 2026 |
| On Telegram | t.me/chasesz_hdgg |
Topic
Giveaways & airdrops — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 56% 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
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Nov 2026, 08:08 | 12,319 | -165 |
| 7 Nov 2026, 03:01 | 12,484 | +451 |
| 6 Nov 2026, 02:40 | 12,033 | -83 |
| 4 Nov 2026, 23:48 | 12,116 | -62 |
| 3 Nov 2026, 20:50 | 12,178 | -28 |
| 2 Nov 2026, 22:29 | 12,206 | -21 |
| 1 Nov 2026, 22:50 | 12,227 | +431 |
| 31 Oct 2026, 23:29 | 11,796 | -50 |
| 31 Oct 2026, 02:56 | 11,846 | +408 |
| 30 Oct 2026, 03:16 | 11,438 | -46 |
| 29 Oct 2026, 04:10 | 11,484 | -124 |
| 28 Oct 2026, 04:31 | 11,608 | -44 |
| 27 Oct 2026, 04:47 | 11,652 | -153 |
| 26 Oct 2026, 03:49 | 11,805 | -42 |
| 25 Oct 2026, 07:00 | 11,847 | +535 |
| 24 Oct 2026, 09:58 | 11,312 | -135 |
| 23 Oct 2026, 09:39 | 11,447 | -45 |
| 22 Oct 2026, 12:11 | 11,492 | -143 |
| 21 Oct 2026, 08:26 | 11,635 | -119 |
| 20 Oct 2026, 09:21 | 11,754 | first reading |
Engagement
45 posts held, back to 17 December 2024 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 23 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.09%
- avg views ÷ 12,319 subscribers
- Avg views / post
- 258
- 25 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 25
- of 45 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.
| Window | Rolling 30 days · latest post in window 7 November 2026 |
|---|---|
| Posts held | 45 (17 December 2024 – 7 November 2026) |
| Views total | 6,452 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Nov 2026, 07:44 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
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 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 2 of the 45 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 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 45 most recent posts we hold, published 17 December 2024 to 7 November 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: 0 of 25 posts held from the last 30 days (0%) 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).
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Showing the 12 most recent of 45 posts we hold for @chasesz_hdgg. 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 recorded as deleted after publishing
We recorded 5 posts on @chasesz_hdgg as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 7 August 2026
- Most recent seen missing
- 3 November 2026
- Median time before seen missing
- 4 days
- Seen missing in the last 30 days
- 2
Mentions
Named by 14 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.
Named by
Channels on the register whose posts name this channel's handle.
@lotterynav · 193,77168 postsLotteryBest精选推荐
@lotterybestnav · 168,77415 posts野寻 · 深圳小喇叭
@chasesz_xlb · 1,2069 posts野寻 · 深圳官方入口
@sz_ooxx · 1,3084 posts野寻 · 深圳商家档案
@chasesz_sjda · 2,0843 posts野寻 · 深圳修车档案
@chasesz_lsda · 13,9852 posts野寻 · 深圳精选档案
@chasesz_lsjx · 10,8872 posts甜玖的朋友圈(开课中)
@baoantianjiu · 1,6261 post坂田 小葡萄🍇
@ipnnlpoo · 2,1281 postCO可可的朋友圈
@kekebb111 · 4451 post💋(柒柒)的好评榜❤️
@mumu258000 · 1961 post羊羊🐑朋友圈
@susuhouhuayuano · 1,9551 post庄庄的朋友圈
@szxzz222 · 5071 post希雅(日常分享)
@zjzjjsneso · 1011 post
Names
Channels on the register whose handles appear in this channel's posts.
@chasesz_jlq · 24,32038 posts野寻 · 深圳打卡通告群
@chasesz_tgq · 24,57033 posts野寻 · 深圳修车档案
@chasesz_lsda · 13,98530 postsLotteryBest抽奖导航
@lotterynav · 193,77128 postsLotteryBest Bot
@LotteryBestBot · 112,0678 posts野寻 · 深圳精选档案
@chasesz_lsjx · 10,8873 posts野寻 · 深圳外围档案
@chasesz_wwda · 2,4593 posts野寻 · 深圳小喇叭
@chasesz_xlb · 1,2063 posts"野寻公告"
@ooxxdh · 6,1223 posts贝贝 休学 (深圳南山)
@beibei77871 · 3,0552 posts婷婷私密后花园💋
@mzn993 · 1,3662 posts甜玖的朋友圈(开课中)
@baoantianjiu · 1,6261 post全国莞式全套会所
@bzbz978 · 21 post野寻 · 深圳榜单导航
@chasesz_bddh · 4,8871 post乐乐的故事
@lelexh1 · 2721 post南山🐱淼淼
@lvMiaomiao456 · 1561 post梦姗传送门
@Mshan8 · 1,0311 post深圳南山小甜(户外野王🉑全国空降火爆营业中)
@ww52880 · 24,5891 post雯雯快乐屋
@WWEN556 · 4541 post深圳【龙华欣欣】36D大🐻
@xiaoyull69 · 1,8241 post上海【喜茶】广播站
@xichash · 12,8531 post福田人瘦大f奶依依(置顶有地址)报告返现活动
@xixi5219 · 4,9481 post乐乐个人小频道💋💋
@zcxg86 · 8451 post希雅(日常分享)
@zjzjjsneso · 1011 post
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 1
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 0
- vacant every time we have ever looked
@chasesz_hdgg named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
named in 2 posts, 4 November 2026 – 5 November 2026 · confirmed gone 7 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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 8 November 2026 — this entry's latest reading, not the date you are reading this.
“野寻 · 深圳活动公告” (@chasesz_hdgg), 12,319 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/chasesz_hdgg.
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.