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Channel

吃瓜抖音热门曝光

@JPZDY2

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

44,929subscribers

+8,330 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002865581414
TypeChannel
Username@JPZDY2
CreatedBetween 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 November 2026
Measurements held63
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/JPZDY2

Topic

Memes & entertainment — 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 96% 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 12 other registered channels. This entry also sits inside a group of 17 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@neihanduanzi1/7240812 Aug 2026, 04:23 UTC@JPZDY2/31256 · this entry12 Aug 2026, 04:23 UTC1.00under a minute
@neihanduanzi1/7248013 Aug 2026, 04:52 UTC@JPZDY2/31341 · this entry13 Aug 2026, 04:52 UTC1.00under a minute
@neihanduanzi1/7418429 Aug 2026, 12:49 UTC@JPZDY2/32864 · this entry29 Aug 2026, 12:49 UTC1.00under a minute
@neihanduanzi1/7448831 Aug 2026, 13:51 UTC@JPZDY2/33193 · this entry31 Aug 2026, 13:51 UTC1.00under a minute
@neihanduanzi1/8119717 Oct 2026, 03:53 UTC@JPZDY2/37659 · this entry17 Oct 2026, 03:53 UTC1.00under a minute
@neihanduanzi1/8132518 Oct 2026, 11:13 UTC@JPZDY2/37775 · this entry18 Oct 2026, 11:13 UTC1.00under a minute
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@neihanduanzi140 (6/8 hand-verifiable sample passed)1.00under a minute@neihanduanzi1 (40–0)
@freechinese25 (6/8 hand-verifiable sample passed)1.0075 minutes@freechinese (25–0)
@DNYXW88022 (6/8 hand-verifiable sample passed)1.002.4 hoursthis entry (22–0)
@wuklan14 (7/8 hand-verifiable sample passed)1.003 daysthis entry (14–0)
@tuigsc13 (8/8 hand-verifiable sample passed)1.0016 hoursthis entry (13–0)
@qiqubk13 (6/8 hand-verifiable sample passed)1.0028 minutesthis entry (8–5)
@aichiguaba12 (5/8 hand-verifiable sample passed)1.001.5 hoursthis entry (12–0)
@DNYQWCG12 (6/8 hand-verifiable sample passed)1.0032 minutesthis entry (7–5)
@chigua_e11 (6/8 hand-verifiable sample passed)1.002.6 hoursthis entry (9–2)
@cctvzb11 (8/8 hand-verifiable sample passed)1.0019 minutes@cctvzb (7–4)
@CG8878 (8/8 hand-verifiable sample passed)1.0049 minutes@CG887 (6–2)
@baguabox7 (6/7 hand-verifiable sample passed)0.992.6 hours@baguabox (4–3)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 94 of the 94 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 137 comparable posts for this entry, running 7 August 2026 to 18 October 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 17 channels, the one whose matching posts we hold earliest is @freechinese. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 12 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Channels linked by matching posts

This channel is in a group of 17 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

36,59944,92940,7647 August 202611 November 2026
63 measurements spanning 96 days, net +8,330. 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 35,350–46,179 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 63
Measured (UTC)SubscribersChange
11 Nov 2026, 11:2044,929+81
9 Nov 2026, 15:3744,848+38
8 Nov 2026, 05:5144,810+59
7 Nov 2026, 02:2144,751+72
6 Nov 2026, 01:0144,679+55
4 Nov 2026, 21:4644,624+60
3 Nov 2026, 19:3944,564+34
2 Nov 2026, 22:0544,530+30
2 Nov 2026, 01:0144,500+44
31 Oct 2026, 21:3844,456+54
30 Oct 2026, 19:2644,402+14
29 Oct 2026, 19:3144,388+48
28 Oct 2026, 21:1544,340+85
27 Oct 2026, 21:4844,255+89
26 Oct 2026, 19:2144,166+88
25 Oct 2026, 19:0744,078+110
24 Oct 2026, 21:3743,968+164
23 Oct 2026, 23:3943,804+129
22 Oct 2026, 23:2843,675+100
22 Oct 2026, 00:3443,575first reading

Engagement

1,279 posts held, back to 7 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 186 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.26%
avg views ÷ 44,929 subscribers
Avg views / post
564
148 posts measured
Reaction rate
1.42%
reactions ÷ views · ER floor
Posts in window
148
of 1,279 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 147 of 148 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 18 October 2026
Posts held1,279 (7 August 2026 – 18 October 2026)
Views total83,517
Reactions total1,189
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Nov 2026, 09:50 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
≈10,100
Videos
≈15,700
Links
≈655

Lifetime counters from Telegram’s own channel header, read 12 November 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
14h 18m
Average length
1m 08s

Measured directly from 761 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

4,616 reactions across 932 posts, in 12 distinct kinds. The most used accounts for 95.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍4,42795.9%
❤621.34%
😱430.932%
🥰220.477%
🖕210.455%
😍190.412%
😡90.195%
🤪50.108%
🌚40.087%
😁20.043%
👎10.022%
👻10.022%

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 950 of the 1,000 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 4,616 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 22 August 2026 to 18 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

Telegram’s own ‘edited’ marker: 8 of 148 posts held from the last 30 days (5.41%) 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).

18 Oct 2026, 11:14 UTC≈4,790 views5 reactionsread 12 November 2026
Video

重庆,真的是张老板的机车。

👍5

18 Oct 2026, 11:13 UTC≈4,040 views5 reactionsread 12 November 2026
Video

黑人在台湾地铁里当众掏出鸡鸡小便 18 日上午,台湾高雄冈山车站捷运站有3个黑人男性到了终点站还在睡觉,旁人好心叫醒他们,结果先醒来的那个人看起来不是很高兴,竟走到整条座位上只有一个女性的隔壁,直接掏出下体开始尿尿。 有其他旅客将整个过程拍下,分享到网路上,只见画面中的黑人男子看到有人在拍,仍不以为然地对着椅子小解,坐在2个座位外的妇人见状也立刻起身逃开,而座椅上则积满男子的尿液。 影片曝光让所有网友看傻了眼,没想到搭捷运会遇到这种事,高雄捷运公司也立刻说明表示:「本案经过了解,为外籍旅客酒醉后脱序行为,高雄捷运公司当下经过旅客通报,立即指派人员上车处理,已经针对违规旅客开立告发单,依照大众捷运法可处$1500以上,$7500以下之罚锾,并可拒绝载运,后续列车并已进行紧急清洁完毕,后续已收车再进行完整清洁消毒。」 台湾网友直呼「罚太轻了」「7500!!有刑责吗?」「罚太轻了吧?工作人员来处理根本是罚到工作人员」,认为应该…

👍4❤1

18 Oct 2026, 11:13 UTC≈3,550 views4 reactionsread 12 November 2026
Photo

工作是工作,生活是生活 窝瓜又黑华为了 !

👍3❤1

18 Oct 2026, 11:13 UTC≈3,400 views8 reactionsread 12 November 2026
Photo

18岁那年第一次踏进麦当劳工作的少年,竟然在同一份工作上坚持了整整32年,最后迎来了退休的日子!他的名字叫做罗素・奥格雷迪(Russell O’Grady)。🍟❤️ 1986年,患有唐氏症的罗素,开始在澳洲的一间麦当劳工作。当时,对身心障碍者来说,想要长期稳定地工作并不容易,但罗素却一天又一天,认真地守着自己的岗位。 就这样,一年、十年、二十年过去了,不知不觉竟然累积了整整32年! 罗素总是带着灿烂的笑容迎接客人,因为长年在同一间店工作,他也渐渐成为当地居民再熟悉不过的面孔。 甚至有些熟客来麦当劳,不只是为了吃汉堡,更是特地想来看看罗素、跟他打声招呼! 从18岁的年轻小伙子,一路工作到50岁,这段时间里,他接待了无数客人,也用自己的认真与亲切,在当地社区留下了许多温暖的回忆。 2018年,罗素终于结束了长达32年的麦当劳职涯,正式退休。 对某些人来说,他或许只是一名普通的麦当劳员工,但对那些认识他多年的居民而言,他…

👍6❤2

18 Oct 2026, 11:13 UTC≈3,090 views7 reactionsread 12 November 2026
Photo

失业来得就是这么突然,一点思考的机会都没有 10月17日,一网友发帖称,四川成都多家房企突然召开全体员工大会,宣布停工待岗。 现场屏幕上打着“成都区域公司停工待岗全体员工大会”的字样,涉及成都多家企业。发帖员工表示:“在一个平静的下午,突然召开员工大会,通知第二天就可以不用来了,失业来得就是这么突然”。 作者随后在评论区补充表示,目前已收到待岗通知书,且“不是国企也不是央企”。 评论区网友热议“这一下停了4个项目公司,成都区域全部凉凉了”、“我们才是垮杆了要,工资硬拖一声不吭”、“成都找工作比找男朋友都难”、“网约车司机又要增加了吗”。

👍4❤3

18 Oct 2026, 11:12 UTC≈2,880 views6 reactionsread 12 November 2026
Photo

胡锡进目前仍然是X平台影响最大的代表中共利益的声音。昨天胡锡进的贴文受到广泛关注。他嘲笑泽连斯基与川普「决裂」,挖苦欧洲要与乌克兰一起打「独立战争」。很多西方媒体认为胡锡进代表中共立场,故意挑拨、激化美乌矛盾,并幸灾乐祸。

👍6

18 Oct 2026, 11:12 UTC≈2,700 views7 reactionsread 12 November 2026
Photo

经济日报发文拷问懂车帝 经济日报的这篇文章讲了几件事: 1、我国处在汽车强国发展关键期。 2、懂车帝测的尊界三台车刹车有问题不代表所有车刹车有问题。 3、汽车工业特别复杂,零件特别多。 4、懂车帝又是裁判员、又是运动员。 5、应该以大局为重。 这种老套路应该升级更新了,没有逻辑没有说服力

👍5❤2

Showing the 12 most recent of 1,279 posts we hold for @JPZDY2. 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

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 11 November 2026 — this entry's latest reading, not the date you are reading this.

“吃瓜抖音热门曝光” (@JPZDY2), 44,929 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/JPZDY2.

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.