International news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 2026 and assigned it the closest of 31 fixed categories, at 94% 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 11 other registered channels. This entry also forms a group of 2 channels linked by matching posts. 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)
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
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. 11 of the 11 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 2,004 comparable posts for this entry, running 5 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 2 channels, the one whose matching posts we hold earliest is @insidertracking — which is this entry. 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 2 registered channels linked by matching posts. 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.
65 measurements spanning 98 days, net +5,065. 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 68,295–74,880 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)
Subscribers
Change
12 Nov 2026, 00:20
74,120
+105
10 Nov 2026, 00:01
74,015
+81
8 Nov 2026, 12:01
73,934
+50
7 Nov 2026, 05:27
73,884
+65
6 Nov 2026, 07:26
73,819
+26
5 Nov 2026, 03:35
73,793
+26
4 Nov 2026, 06:40
73,767
+126
3 Nov 2026, 09:09
73,641
+32
2 Nov 2026, 09:46
73,609
+79
1 Nov 2026, 06:24
73,530
+9
31 Oct 2026, 03:29
73,521
+40
30 Oct 2026, 00:56
73,481
+82
28 Oct 2026, 21:21
73,399
+12
27 Oct 2026, 21:16
73,387
+16
26 Oct 2026, 22:48
73,371
+39
25 Oct 2026, 23:36
73,332
+17
24 Oct 2026, 20:37
73,315
-2
23 Oct 2026, 20:25
73,317
+14
22 Oct 2026, 17:26
73,303
+86
21 Oct 2026, 09:48
73,217
first reading
Engagement
3,641 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 196 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.11%
avg views ÷ 74,120 subscribers
Avg views / post
5,270
1,119 posts measured
Reaction rate
0.491%
reactions ÷ views · ER floor
Posts in window
1,119
of 3,641 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 1,118 of 1,119 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 11 November 2026
Posts held
3,641 (5 August 2026 – 11 November 2026)
Views total
5,899,997
Reactions total
28,975
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 20:24 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
Video runtime
1h 40m
Average length
45s
Measured directly from 133 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
25,488 reactions across 999 posts, in 5 distinct kinds. The most used accounts for 31.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5330297883147131611
8,085
31.7%
custom 5334665890656954850
7,334
28.8%
custom 6278200451024297677
5,418
21.3%
custom 5235747687113961359
2,628
10.3%
custom 6276246786365465434
2,023
7.94%
Custom emoji. Every row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 999 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 25,488 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 16 October 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: 85 of 1,119 posts held from the last 30 days (7.60%) 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).
📢 공지사항 안내
Speed matters, Facts matter more
속도도 중요하지만, 정확한 사실이 우선이다
미국 주식, 국제 정세, 속보 및 전쟁 이슈까지
가장 빠르고 정확하게 전달드리겠습니다.
━━━━━━━━━━━━━━
🛍 Trends & Tips 세일 정보 채널 (세컨 채널)
https://t.me/honeylifetip
📚 미주인이 집필한 도서 구매하기
https://t.me/insidertracking/62778
📹미국 주식 인사이더 유튜브 (정상 영업중)
https://www.youtube.com/@insidertracking
✉️ 미주인 무료 뉴스레터 신청하기
https://maily.so/insidertracking
😚 미주인 x 인베스팅닷컴 60% 이상 할인받기!
https://t.me/insidert…
미국 기업 섹터별 소식 정리 (실적 제외)
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🤖 AI · 클라우드 · 소프트웨어
• 에어비앤비 (ABNB) — 자체 AI 여행 에이전트를 2027년 상반기 출시할 계획임. 여행 계획·옵션 비교·예약 관리뿐 아니라 향후 에어비앤비 외부 사업자의 상품까지 예약할 수 있도록 확장할 예정임.
━━━━━━━━━━━━━━
💾 반도체 · 데이터센터 · 광통신
• 엔비디아 (NVDA) — 중국 대학이 미국 블랙리스트에도 불구하고 엔비디아 H200 칩을 구매한 것으로 로이터가 보도함. 별도로 미 의회에서는 첨단 AI 칩의 위치 확인·추적 기능을 요구하는 법안 등 대중국 수출통제 강화 움직임이 확대되고 있는 것으로 전해짐.
• 알리바바 (BABA) — 홍콩거래소로부터 AI 반도체 자회사 T-Head 분사를 추진하기 위한 승…
🌎 글로벌 뉴스 브리핑 - 2026년 11월 11일
오후 3시~오후 9시 기준
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🇺🇸 아메리카
• 칠레 재무장관은 자국 경제가 기술적 경기 하강 국면에 있다고 평가하면서도 2028년 경제성장률이 4%에 도달할 가능성이 있다고 전망.
• 중국 외교부는 캐나다 내정에 개입할 의도가 전혀 없다고 밝혀. 앞서 마크 카니 캐나다 총리의 관련 발언에 대한 입장을 표명.
• 마이크로소프트는 AI 데이터센터 투자 확대 과정에서 기술기업들이 지역 일자리와 경제적 효과 등 현지 사회에 제공하는 실질적 혜택을 입증해야 한다고 강조.
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🇪🇺 유럽
• 러시아·우크라이나·미국 대표단은 아부다비에서 이틀째 3자 평화협상을 진행한 뒤 이번 회담을 종료. 러시아 측은 협상이 건설적인 분위기에서 진행됐으며 추가 …
에어비앤비가 자사 플랫폼을 넘어 외부 서비스에서도 여행 예약이 가능한 인공지능(AI) 여행 에이전트 출시를 추진.
2027년 상반기 출시를 목표로 개발 중이며, 여행 일정 계획, 옵션 비교, 예약 관리, 숙박 기간 중 여행객 지원 등의 기능을 제공할 예정.
해당 AI 에이전트는 향후 에어비앤비 플랫폼뿐 아니라 외부 서비스 제공업체를 통한 예약까지 지원하도록 확대할 계획.
에어비앤비 공동창업자는 현재 AI 에이전트를 통해 유입되는 트래픽이 극히 적은 수준이라며, AI 에이전트가 기존 플랫폼을 우회하는 중개 배제 위협은 당장 크지 않다고 평가.
탈렌에너지가 연간 약 1억 달러 규모의 750MW 장기 전력 용량 계약을 확보.
투자적격 등급의 거래 상대방과 체결한 이번 계약은 2029~2030년부터 2035~2036년까지 PJM 전력시장 공급 기간을 포함하는 7년 계약.
기존 전력 용량 경매 계약과 합산하면 향후 10년간 약 10억 달러의 누적 매출 가시성을 확보.
추가로 건지 발전소에서 588MW, 워터퍼드 발전소에서 702MW 규모의 계약을 체결하면서 2029~2030년 기준 총 계약 전력 용량이 2GW를 초과.
아마존웹서비스(AWS)와의 기존 계약까지 포함하면 2036년까지 전체 매출총이익의 40%가 계약으로 확보된 상황.
제프리스가 코닝에 대해 매수 의견으로 신규 커버리지를 개시. 인공지능(AI) 수요 증가에 따른 광섬유 공급 부족과 하이퍼스케일러 및 통신사업자들과의 다년 계약을 긍정적으로 평가.
데이터센터 간 연결(DC 인터커넥트) 시장이 확대되면서 단기적으로 통신사업자 부문의 실적 개선 여력이 존재하며, 2028년부터는 AI 시스템 내부에도 광섬유가 적용될 것으로 전망.
연습) 트럼프 "젠슨황 후임으로 아주 훌륭한 사람 알고 있다"
젠슨 황은 아주 훌륭한 사람입니다.
하지만 최근 아주 끔찍한 일이 벌어졌습니다. 정말 슬픈 일이죠. 이 이야기 속에서 젠슨 황은 CEO 자리에서 물러날 위기에 처했습니다. 매우 안타까운 일입니다. 정말로요.
엔비디아에는 새로운 지도자가 필요합니다.
강력한 지도자 말입니다. 아주 똑똑하고, 사업을 잘 알고, 무엇보다 중국을 상대할 줄 아는 사람이어야 합니다.
시진핑도 잘 아는 사람이면 더 좋겠죠.
많은 사람들이 저에게 물었습니다.
"도널드, 엔비디아를 구할 사람이 누굽니까?"
"일론 머스크? 리사수입니까?"
천만에요! 일론은 훌륭한 친구지만 트위터에서 싸우느라 바쁩니다
다음 엔비디아 CEO는 바로 도널드 J. 트럼프입니다!
그는 아주 놀라운 사람입니다. 많은 여성들에게…
뉴욕포스트에 따르면 미국 연방수사국(FBI)이 엔비디아 CEO 젠슨 황과 중국계 여성 앨리스 황의 관계를 조사 중. 미 법무부가 첨단 인공지능(AI) 반도체의 중국 밀수 의혹을 조사하는 과정에서 두 사람의 관계가 수사 대상에 포함된 것으로 확인.
앨리스 황은 중국 출신 기술업계 인사들과 긴밀한 관계를 유지해 온 인물로, 젠슨 황과 함께 고급 레스토랑에서 식사하거나 와인을 마시는 모습이 공개된 바 있음. 특히 중국 정보기관과의 연계 가능성이 제기된 인물들과 접촉한 정황도 거론.
수사 당국은 엔비디아의 첨단 AI 반도체가 중국으로 불법 유입되는 과정에 앨리스 황이 관여했는지 조사 중. 앨리스 황의 남편 캉 웨이는 중국 최대 게임업체 텐센트와 연계된 인물로, 미국 반도체 기술에 접근할 수 있는 사업적 관계를 구축해 온 것으로 알려짐.
미국 의…
악시오스에 따르면 스티븐 밀러가 백악관 비서실장이라는 새로운 역할을 활용해 2026년 중간선거에서 민주당으로 이동한 젊은층·노동계층·소수인종 남성 유권자층을 다시 확보할 계획.
주요 의제로는 ‘워크(woke)’ 정책 대응, 처방약 가격 인하, 관료주의 축소, 생활비 부담 완화 등이 포함.
2024년 대선에서 트럼프 대통령이 30세 미만 남성 유권자에서 14%포인트 우위를 기록했으나, 2026년 중간선거에서는 민주당이 같은 유권자층에서 22%포인트 앞서며 36%포인트의 변동 발생.
다만 1월부터 민주당이 상·하원을 모두 장악하게 되면서 밀러의 정책 추진에는 상당한 장애물이 존재할 전망.
Showing the 12 most recent of 3,641 posts we hold for @insidertracking. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republished by 164 registered channels. The 48 listed are the ones that have forwarded the most posts; the rest are counted here but not each listed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 45 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 23 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.
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
@insidertracking 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.
@aetherjapanresearch named in 1 post, 3 September 2026 – 3 September 2026 · confirmed gone 27 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Domains linked from posts
3 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“미국 주식 인사이더 🇺🇸 (US Stocks Insider)” (@insidertracking), 74,120 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/insidertracking.
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.
