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Channel

BRILLER

@BRILLER_Research

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

17,974subscribers

-136 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-1001970745689
TypeChannel
Username@BRILLER_Research
Description"나는 날마다 모든 면에서 점점 더 좋아지고 있다!"
CreatedBetween 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 November 2026
Measurements held63
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/BRILLER_Research

Topic

Health & wellness — 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 79% 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 2 other registered channels. This entry also sits inside a group of 12 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
@BRILLER_Research/4712 · this entry28 Oct 2026, 15:09 UTC@Jquent/6629 Oct 2026, 03:08 UTC1.0012 hours
@BRILLER_Research/4713 · this entry28 Oct 2026, 15:27 UTC@Jquent/6729 Oct 2026, 03:08 UTC1.0012 hours
@BRILLER_Research/4716 · this entry30 Oct 2026, 00:38 UTC@Jquent/6930 Oct 2026, 00:51 UTC1.0013 minutes
@BRILLER_Research/4717 · this entry30 Oct 2026, 00:40 UTC@Jquent/7030 Oct 2026, 00:52 UTC1.0012 minutes
@BRILLER_Research/4720 · this entry30 Oct 2026, 01:14 UTC@Jquent/7330 Oct 2026, 01:23 UTC1.008 minutes
@BRILLER_Research/4721 · this entry30 Oct 2026, 01:19 UTC@Jquent/7430 Oct 2026, 01:23 UTC1.004 minutes
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
@Jquent6 (6/6 hand-verifiable sample passed)1.0013 minutesthis entry (6–0)
@pharmbiohana5 (5/5 hand-verifiable sample passed)0.9955 minutesthis entry (3–2)

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. 1 of the 1 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 31 comparable posts for this entry, running 29 July 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 12 channels, the one whose matching posts we hold earliest is @alteogenIR. That channel is not among the channels listed above, so this entry may share no posts with it and this does not say where this entry’s content came from. It is a statement about our reading window, not a claim of authorship.

Recorded under the keys 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 12 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

17,97418,30818,1416 August 202610 November 2026
63 measurements spanning 96 days, net -136. 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 17,924–18,358 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 63
Measured (UTC)SubscribersChange
10 Nov 2026, 08:4117,974-4
8 Nov 2026, 23:4517,978-3
7 Nov 2026, 17:0917,981-2
6 Nov 2026, 16:5617,983-6
5 Nov 2026, 17:5817,989-13
4 Nov 2026, 15:2018,002-6
3 Nov 2026, 12:0618,008+8
2 Nov 2026, 13:3918,000-3
1 Nov 2026, 15:0818,003-1
31 Oct 2026, 12:2818,004-1
30 Oct 2026, 08:5718,005-3
29 Oct 2026, 06:3918,008-6
28 Oct 2026, 07:2818,014-10
27 Oct 2026, 04:1518,024-14
26 Oct 2026, 02:3818,038-3
25 Oct 2026, 02:5418,041-2
24 Oct 2026, 00:5518,043-4
23 Oct 2026, 02:3018,047-10
22 Oct 2026, 02:5618,057+3
20 Oct 2026, 19:2718,054first reading

Engagement

49 posts held, back to 29 July 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 72 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
28.7%
avg views ÷ 17,974 subscribers
Avg views / post
5,150
26 posts measured
Reaction rate
0.488%
reactions ÷ views · ER floor
Posts in window
26
of 49 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 November 2026
Posts held49 (29 July 2026 – 11 November 2026)
Views total133,890
Reactions total654
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 04:27 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
≈2,060
Videos
≈28
Links
≈2,080

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.

Reaction mix

1,960 reactions across 49 posts, in 7 distinct kinds. The most used accounts for 33.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🙏65933.6%
❤61331.3%
👍47124.0%
🔥1376.99%
😁492.50%
💯231.17%
😍80.408%

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 49 of the 49 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 1,960 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 49 most recent posts we hold, published 29 July 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.

Telegram Stars

Stars received
2
across the posts below
Posts paid on
2
of 49 we hold a reading for · 4%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @BRILLER_Research. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 49 most recent posts we hold for this entry, published 29 July 2026 to 11 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 26 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, 02:55 UTC≈1,370 views10 reactionsread 11 November 2026
Photo

"지금까지의 대화에서 느껴지는 나의 인간성을, 글자를 쓰지 않고 한 장의 이미지로 표현해주세요. 미화 금지. 당신의 편견을 전력으로 반영해주세요." 지인이 이거 해보라고 해서 방금 해봤는데 저를 여자로 표현해주네요. 질문들이 여자분들이 많이 할만한 질문을 많이해서 그런건가 싶기도 ㅎㅎ + 뒤쪽에 기분에 따른 모습변화는 전형적인 주식투자자 같네요.

❤8👍2

11 Nov 2026, 02:16 UTC≈1,590 views23 reactionsread 11 November 2026

최근 시장 상황이 좋지 않은 만큼 주가 하락 역시 어느 정도 이해하고 있습니다. 다만 에이피알의 성장성과 기업 가치에 비해 주가가 다소 아쉬운 흐름을 보이고 있는 것 같습니다. 이러한 시기에 회사에서도 주주 가치 제고를 위한 다양한 방안을 함께 고민해 주신다면, 주주들에게도 큰 힘이 될 것 같습니다. 기업의 성장과 주주 가치가 함께 나아갈 수 있기를 기대합니다.

🙏19❤3👍1

10 Nov 2026, 06:48 UTC≈2,600 views20 reactionsread 11 November 2026
Photo

화장품 수출은 6개 분기 연속 최고치를 경신했습니다. 3분기 월평균 수출액은 YoY 약 67% 증가했습니다. 10월도 호실적이 예상되고 있습니다. 반면, 화장품주들의 주가는 전체적인 시장 조정의 영향을 많이 받았습니다. 수출 데이터와 주가 사이의 간격이 벌어지는 셈인데, 이 간격이 어떻게 좁혀질지 지켜볼만 합니다.

❤14🔥6

9 Nov 2026, 05:46 UTC≈3,860 views18 reactionsread 11 November 2026
Photo

[261109 엘앤씨바이오 상승VI🔥] ECM 리투오 화이팅!

❤13👍3🔥2

9 Nov 2026, 05:37 UTC≈3,130 views10 reactionsread 11 November 2026
Forwarded from @darthacking

2026.11.09 14:34:14 기업명: 엘앤씨바이오(시가총액: 6,809억) A290650 보고서명: 영업(잠정)실적(공정공시) 매출액 : 313억(예상치 : 417억/ -25%) 영업익 : 104억(예상치 : 100억/ +4%) 순이익 : 52억(예상치 : -) **최근 실적 추이** 2026.3Q 313억/ 104억/ 52억 2026.2Q 388억/ 86억/ -281억 2026.1Q 303억/ 60억/ 27억 2025.4Q 247억/ 20억/ -720억 2025.3Q 226억/ 29억/ -513억 공시링크: https://dart.fss.or.kr/dsaf001/main.do?rcpNo=20261109900321 종목공시 : https://www.awakeplus.co.kr/disclosure/290650

👍8❤2

6 Nov 2026, 06:46 UTC≈6,720 views100 reactionsread 11 November 2026

험난한 11월 첫째주 모두 고생많으셨습니다. 지인분이 "어떤 말이나 글도 누군가에게 상처가 될 수 있는 한 주인 것 같습니다."라는 말씀을 하셨는데 정말 맞는말이라고 생각합니다. 이런 시기에 굳이 안해도 될 말들 특히 상대방에게 상처가 될 수 있는 말을 하면 투자뿐만 아니라 사람 또한 잃을 수 있는 시기라고 생각합니다. 이럴때 산책이나 러닝을 하면 저는 스트레스가 해소가 되는 편인데 지금은 둘 다 할 수가 없는 무릎 상태라서 안장 높인 실내 자전거로 대체해서 스트레스를 좀 풀어 볼려고 합니다. 모쪼록 힘든시기이지만 모두 화이팅입니다.

❤85🙏8👍4🔥3

5 Nov 2026, 15:34 UTC≈6,030 views12 reactionsread 11 November 2026
Photo

[261106 하이닉스 ADR 상장 후 최저가 갱신]

🔥9❤2🙏1

5 Nov 2026, 12:21 UTC≈4,760 views5 reactionsread 11 November 2026
Forwarded from @pharmbiohana

민주당 압승, 중간선거 이후 봐야할 바이오 내 섹터와 기업 총정리 https://youtu.be/FNvbykJZf2M

❤3🔥2

5 Nov 2026, 08:42 UTC≈4,920 views25 reactionsread 11 November 2026
Photo

요즘 핫한 게임인 디아2 서바이버 몇일간 하다가 오늘 유니크 아이템을 하나 주웠는데요. 아이템 이름이 "뇌절단기 그레이트 액스"네요... 마치 지금장에 주식하는 저를 보고 게임이 뇌절 했다고 놀리는 느낌...ㅠㅠ

😁20❤3🔥2

5 Nov 2026, 00:03 UTC≈5,380 views28 reactionsread 11 November 2026
Photo

[261105 시장근황] 미국 민주당 압승 후 국장도 장 색깔이 좀 바뀌는 분위기네요. 피부미용, 화장품 섹터가 급등중이고 바이오섹터도 함께 급등중이네요.

👍21🔥7

2 Nov 2026, 14:25 UTC≈7,900 views43 reactionsread 11 November 2026
Photo

[재야의 고수들(주식 투자로 인생을 바꾼 14인의 분투기)책 정식 출간] by BRILLER(t.me/BRILLER_Research) 안녕하세요. 제가 3년전인 24년01월12일 와이스트릿 유튜브에 출연하여 인터뷰한 내용과 올해 01월05일 촬영한 인터뷰 내용중 핵심내용들이 들어간 [재야의 고수들] 책이 26년 11월 02일 금일자로 정식 출간되었습니다. [재야의 고수들] 책에 참여하신 투자자분들은 사실 저랑은 비교가 안 될 정도로 자산이나 인품이나 모두 훌륭하신 고수분들이십니다. 저는 그냥 중간에 꼽사리만 꼈습니다. (=거인의 어깨에 올라타기 전략) 이 책에 같이 참여하신 남산주성님과 피터케이님은 에스트레뉴에서 함께 몇년간 사무실 생활을 했었던지라(당시에 저는 사무실 막내ㅎㅎ) 큰 형님들과 함께 책표지에 사진이 올라가니 부끄럽기도…

❤39🔥4

2 Nov 2026, 13:42 UTC≈4,120 views18 reactionsread 11 November 2026
Forwarded from @knowledge_to_wealthPhoto

집 판 돈으로 투자했다가 다 날리고 3번 연속 하한가를 맞아 멘탈 털리고 마포대교 위에서 '다시는 주식 하지 않겠다'고 다짐하던 사람들... 지금은 어마어마한 부를 쌓은 분들이지만, 처음은 초라했습니다. 안녕하세요? 이대호 와이스트릿 대표입니다. 제가 5년간 인터뷰 한 14명 투자 고수들의 이야기 <재야의 고수들> 신간이 나왔습니다. 이 책을 읽는다고 슈퍼개미가 되는 건 아닐 겁니다. 그렇다면 제가 제일 먼저 됐어야죠 ㅋ 어떻게 성공했느냐가 아니라, 어떻게 살아남았느냐에 초점을 두면 분명히 어제보다 더 나아진 내일을 누구나 만들어 갈 수 있을 겁니다. 먼저 정상에 오른 사람들을 보면서 14개의 루트를 확인할 수 있을 것이고, 그 중에 분명 나의 길이 있을 겁니다. 이 책의 인세는 100% 기부할 예정입니다. 14명의 출연진이 아무…

❤17🔥1

Showing the 12 most recent of 49 posts we hold for @BRILLER_Research. 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

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 10 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.

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.

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.

조기주식회 공부방
@EarlyStock1 · 24,379
Telegram ranks this channel #60 of 91 here — alongside 90 others — read 16 September 2026
피카츄 아저씨⚡️
@pikachu_aje · 24,923
Telegram ranks this channel #85 of 91 here — alongside 90 others — read 14 September 2026

This channel appears in 2 seed channels' Telegram-generated recommendation lists 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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“BRILLER” (@BRILLER_Research), 17,974 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/BRILLER_Research.

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.