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Channel

奇闻百科猎奇AI短剧科普

@qw149

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry

25,384subscribers

+7,507 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-1001634740631
TypeChannel
Username@qw149
Description管理联系: @feiyu199 双向联系: @zuanqian2026_bot
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 live11 November 2026
Measurements held62
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/qw149

Topic

Gambling & betting — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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 4 other registered channels. This entry also sits inside a group of 6 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
@lsd62/99148 Aug 2026, 04:21 UTC@qw149/8728 · this entry3 Sept 2026, 03:40 UTC1.0026 days
@lsd62/106131 Oct 2026, 13:02 UTC@qw149/9062 · this entry1 Oct 2026, 13:02 UTC1.00under a minute
@lsd62/106151 Oct 2026, 13:06 UTC@qw149/9064 · this entry1 Oct 2026, 13:06 UTC1.00under a minute
@lsd62/1077010 Oct 2026, 16:07 UTC@qw149/9215 · this entry10 Oct 2026, 16:08 UTC1.00under a minute
@qw149/9024 · this entry29 Sept 2026, 05:49 UTC@lsd62/1077511 Oct 2026, 04:24 UTC1.0012 days
@lsd62/1078912 Oct 2026, 03:18 UTC@qw149/9234 · this entry12 Oct 2026, 03:18 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
@lsd6211 (8/8 hand-verifiable sample passed)1.0072 seconds@lsd62 (7–4)
@qsf6669 (8/8 hand-verifiable sample passed)1.0022 hoursthis entry (6–3)
@duanjutianju9 (8/8 hand-verifiable sample passed)1.00under a minute@duanjutianju (7–2)
@yewaiTQ8 (8/8 hand-verifiable sample passed)1.0024 hours@yewaiTQ (5–3)

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. 22 of the 22 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 109 comparable posts for this entry, running 23 August 2026 to 10 November 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 6 channels, the one whose matching posts we hold earliest is @yewaiTQ. 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 11 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 6 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

17,87725,38421,630.57 August 202611 November 2026
62 measurements spanning 96 days, net +7,507. 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 16,751–26,510 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)SubscribersChange
11 Nov 2026, 02:0825,384+37
9 Nov 2026, 12:1125,347+7
8 Nov 2026, 02:2025,340+16
7 Nov 2026, 00:5625,324+16
6 Nov 2026, 03:3925,308+26
5 Nov 2026, 06:4825,282+9
4 Nov 2026, 06:5125,273+10
3 Nov 2026, 07:0425,263+2
2 Nov 2026, 03:4925,261+79
1 Nov 2026, 00:4025,182+76
30 Oct 2026, 22:2925,106+63
29 Oct 2026, 21:0125,043+81
28 Oct 2026, 23:3024,962+78
27 Oct 2026, 19:1024,884+575
26 Oct 2026, 16:0624,309+87
25 Oct 2026, 18:5624,222+85
24 Oct 2026, 18:1724,137+64
23 Oct 2026, 17:1624,073+89
22 Oct 2026, 15:4623,984+83
21 Oct 2026, 11:5923,901first reading

Engagement

576 posts held, back to 5 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 187 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.69%
avg views ÷ 25,384 subscribers
Avg views / post
683
217 posts measured
Reaction rate
0.108%
reactions ÷ views · ER floor
Posts in window
217
of 576 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 11 of 217 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 11 November 2026
Posts held576 (5 August 2026 – 11 November 2026)
Views total148,107
Reactions total11
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 15:22 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
≈643
Videos
≈4,610
Links
≈73

Lifetime counters from Telegram’s own channel header, read 11 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
10h 28m
Average length
1m 25s

Measured directly from 443 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

18 reactions across 17 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍950.0%
❤844.4%
👎15.56%

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 21 of the 576 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 18 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 576 most recent posts we hold, published 5 August 2026 to 11 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 217 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).

11 Nov 2026, 13:59 UTC787 viewsread 11 November 2026
Video

🤩🤩🤩🤩 🤩🤩🤩🤩🤩 0审核|包出款🤩🤩🤩 东南亚大事件联合担保🤩🤩🤩🤩🤩(电子) 🤩亿级域名|78.COM 🤩官方飞投|充提自由 🔝实力派:78.COM 数字够短 品牌够大 🔥香港六合彩 · 独家盈利无上限! 🤩所有的特码🤩🤩倍 🤩连码三中三🤩🤩🤩倍 🤩百家乐全网最高起步返水🤩% 🤩电子|棋牌|捕鱼起步返水🤩.🤩% 🤩十三水|德州自主组队,无抽佣; 🏆PG电子单注🤩🤩🤩🤩U一拉; ⭐️百家乐真人视讯台红🤩🤩万U; 🚩 诚招代理合作: 1.打码返佣,限指定平台; 2.可叠加占成,自选占成比例及游戏平台; 🤩🤩🤩🤩:@DL78 💥高额战绩,巅峰记录持续刷新: 🥇PP电子|极速糖果1000 玩家游戏中购买30000u超级免费旋转,高倍爆奖,最终拿下378万U,已出款; 🥈PG电子|麻将胡了 又又又欧气爆棚,5000U一拉,连番触发,单局斩获193万U; 🥉香港六合彩|特码49倍 爱拼才会赢,大佬单码下注18万U,一注直接拿下本期…

11 Nov 2026, 12:54 UTC787 viewsread 11 November 2026
Video

沈老板教你,怎么把蓝莓包装成高端货! 这个 AI 视频讽刺了将普通蓝莓包装成高端限量奢侈品的营销套路。 片中 “沈老板” 将低价收购的蓝莓,换名 “北欧高地蓝莓”,用黑丝绒礼盒和虚假溯源,以1888 元一盒限量卖给贵妇,狂赚 820% 的利润。 #奸商 #饥饿营销 #AI视频 #蓝莓 #AI短剧

11 Nov 2026, 10:51 UTC810 viewsread 11 November 2026
Video

《宝宝专用湿巾》二十抽卖三十九,宝宝用的就是讲究。 该视频通过剧情演绎,讽刺了商家利用 “宝宝专用” 概念将湿巾溢价数倍的营销套路。 视频中,商家将原本便宜的湿巾改小包装并贴上 “宝宝专用” 标签,便能高价售卖。这引发评论区强烈共鸣,网友纷纷吐槽 “宝宝盐”、“宝宝酱油” 等都是收割家长的“智商税”。 其实,婴儿湿巾与普通湿巾确有区别,前者通常配方更温和、无酒精。但专家提醒,选购时应重点关注成分表,避免盲目为 “专用” 标签买单,谨防部分产品存在的防腐剂等安全隐患。 #湿巾 #宝宝湿巾 #智商税 #ai短剧 #AI短片

11 Nov 2026, 08:48 UTC821 viewsread 11 November 2026
Video

睡觉高于一切! 睡眠是身体最高级别的系统重装与硬件修复,其重要性远超吃饭、工作和娱乐。 #涨知识 #科普 #AI短剧 #AI短片

11 Nov 2026, 06:44 UTC845 viewsread 11 November 2026
Photo

Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_5773967416

11 Nov 2026, 06:44 UTC843 viewsread 11 November 2026
Video

《宝宝洗衣液》同样是洗衣液,换个卡通小瓶子,凭什么溢价几十倍 这个 AI 剧情视频揭露了“宝宝专用洗衣液”的营销套路:将普通洗衣液换个卡通小瓶,贴上 “温和无刺激” 标签,就能让成本翻几十倍。 #宝宝洗衣液 #智商税 #AI短剧 #AI短片

11 Nov 2026, 04:41 UTC844 viewsread 11 November 2026
Video

陌生人说带你发财,你会防。 可是熟人呢? 这个 AI 短片以古喻今,生动揭露了“熟人引路局”的可怕骗局,警示大家最难防的往往是熟人。 视频中,村民罗有庆回乡谎称带乡亲们跑商发财,实则将人骗卖为奴。这与现实中被亲友以高薪工作、投资分红为由,骗入传销陷阱或境外电诈园区的套路如出一辙。 #骗局揭秘 #AI短剧 #AI短片 #骗术 #邵氏电影

11 Nov 2026, 02:36 UTC832 viewsread 11 November 2026
Video

马航MH370,为什么到现在都没有找到? 这是一条AIGC 科普视频,作者用 “人类提问、AI 形象解答” 的对话形式,把马航 MH370 失联到搜寻的完整线索串了一遍。核心结论是:飞机并非凭空消失,而是应答机被关、转向南飞,最后燃油耗尽坠入南印度洋,主体残骸至今没找到。 #马航MH370 #未解之谜 #涨知识 #科普 #AI短剧 #AI短片

10 Nov 2026, 12:15 UTC957 views0 reactionsread 11 November 2026
Video

古代骗术合集三,古代骗术合集三利用贪婪人 利诱 信任收割 本视频通过生动的 AI 短剧,揭秘了古代三种经典的诈骗套路,分别是利用贪婪哄抬物价的 “抬轿局”、利用信任两头骗取财物的 “假马脱缰” 以及用小恩小惠获取信任收割老人的 “养恩局”,提醒观众提高防范意识。 #AI短剧 #AI短片 #科普 #猎奇

10 Nov 2026, 10:13 UTC952 viewsread 11 November 2026
Video

“超级食物” 该剧情片辛辣讽刺了商家如何将普通水果包装成高价“超级食物”的营销套路。 视频中,老板将半个牛油果贴上 “进口、轻食” 标签,就能把 5 元的早餐卖到 50 元,把产品包装成消费者在买 “自律的人生”,精准拿捏了健康溢价。 #商人思维 #牛油果 #ai短剧 #AI短片 #剧情片

10 Nov 2026, 08:11 UTC963 viewsread 11 November 2026
Video

贫富思维的差异,你学会了吗? 为什么大多数人难以成为富人,你学会了吗? 这个 AI 短剧通过两个虚构的商业故事,生动展示了贫富思维与现金流认知的差异。 视频中,吴总用劳斯莱斯抵押借款来 “省钱停车”,并通过 “29.9 元免费吃一年包子” 的会员模式,成功让一家亏损的早餐店实现了现金流变现。 #贫富思维差异 #AI短片 #AI短剧

10 Nov 2026, 06:09 UTC966 viewsread 11 November 2026
Video

这个 AI 短剧生动揭秘了古代专门针对女性的“白嫖局”,警示大家防范情感与套路陷阱。 视频中,张公子以赠送豪华 “BBA 马车” 为诱饵,与车行掌柜串通设局,骗得女子陪他出游并垫付了大笔银两,随后他携定金潜逃,让受害者 “人财两空” 且难以立案。 #ai短剧 #防骗 #ai #邵氏电影 #ai漫剧

Showing the 12 most recent of 576 posts we hold for @qw149. 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 130 posts on @qw149 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
8 August 2026
Most recent seen missing
11 November 2026
Median time before seen missing
31 hours
Seen missing in the last 30 days
46

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.

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

【吃瓜🍉&搞笑】
@GQSP9 · 57,264
Telegram ranks this channel #45 of 53 here — alongside 52 others — read 14 August 2026

This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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.

“奇闻百科猎奇AI短剧科普” (@qw149), 25,384 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/qw149.

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.