Telegram RegisterThe public register of Telegram

Channel

정보를 DAO (공지)

@informationdao

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

4,250subscribers

-13 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001549749423
TypeChannel
Username@informationdao
CreatedBetween 1 August 2021 and 31 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged2 times, most recently 12 August 2026
On Telegramt.me/informationdao

Growth

4,2504,2634,256.56 August 2026 — 4,263 subscribers6 August 2026 — 4,263 subscribers6 August 2026 — 4,261 subscribers10 August 2026 — 4,250 subscribers6 August 202610 August 2026
4 measurements spanning 4 days, net -13. 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 4,248–4,265 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 00:514,250-11
6 Aug 2026, 19:334,261-2
6 Aug 2026, 04:064,263no change
6 Aug 2026, 03:064,263first reading

Engagement

20 posts held, back to 8 May 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 5 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
8.81%
avg views ÷ 4,250 subscribers
Avg views / post
375
5 posts measured
Reaction rate
0.906%
reactions ÷ views · ER floor
Posts in window
5
of 20 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 4 of 5 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 1 August 2026
Posts held20 (8 May 20261 August 2026)
Views total1,873
Reactions total14
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 12:00 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

65 reactions across 18 posts, in 2 distinct kinds. The most used accounts for 80.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
5280.0%
👍1320.0%

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 18 of the 20 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 65reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 8 May 2026 to 1 August 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

1 Aug 2026, 09:24 UTC161 views2 reactionsread 8 August 2026
Forwarded from @zamboyakPhoto

7월 월말기록 https://blog.naver.com/sanoulzig/224364877659

2

Signed 정보를DAO

1 Aug 2026, 02:01 UTC983 views9 reactionsread 8 August 2026
Photo

8월을 시작하며, 투자 생각 정리 https://blog.naver.com/changstockman/224364669841

👍63

Signed 정보를DAO

31 Jul 2026, 13:17 UTC221 views2 reactionsread 8 August 2026
Forwarded from @iwontloseitPhoto

저도 의견하나 남깁니다 (전적으로 트레이딩 관점입니다) 일단 어제 레오폴드 청산뉴스를 기점으로 강한상승이 나왔습니다. 이 시장은 5월4일부터 시작된 상승채널을 돌파하는 분출파형에서 고각으로 뽑아내는 상승에서 시작되었고, 시장의 유동성이 받쳐주지 못하는 지점까지 시장은 열심히 상승해왔습니다. 때 마침 전국민의 거대한 레버리지와 풍부한 유동성으로 일명 풍차돌리기하며 거대한 꿈을 키웠나갔던 한국시장은 이 ETF, 레버리지, 유동성 3가지의 요소에 가장 치명적으로 노출되어 있었다고 생각됩니다. 증권사에서는 각종ETF를 신설하며 신규회원을 모집했고, 정부에서도 ISA, IRP, 연저펀 등에서 증권사상품을 투자하기 좋은 환경을 만들어 주었습니다. 게다가 심지어 개인들마저 개별종목으로는 대응이 어렵다고 생각했던것인지 코반레, 타반레, 솔탑투 등 E

2

Signed 정보를DAO

31 Jul 2026, 11:54 UTC328 viewsread 8 August 2026
Forwarded from @economicrypto

7월 수고 많으셨습니다 https://blog.naver.com/economicrypto/224364206083

Signed 정보를DAO

31 Jul 2026, 11:09 UTC180 views1 reactionsread 8 August 2026
Forwarded from @dolchanchain

7월 '상황 인식' https://blog.naver.com/dolchanchain/224364165209

1

Signed 정보를DAO

23 Jun 2026, 13:07 UTC≈4,990 views2 reactionsread 8 August 2026
Photo

코살남 → '코스피에 살림차린 남자' 의 친절한 설명 글.. https://blog.naver.com/dream_350/224324997842 <밥충이가 해석한 요약> 1. 최근 마켓 변동성의 주요 원인 중 하나는 레버리지 상품 수급 최근에는 국내 2배 레버리지 ETF와 홍콩 2배 레버리지 ETF의 규모가 커지면서 장 마감 직전 리밸런싱 수급이 시장 변동성에 큰 영향을 주고 있음. 2. 거대한 NAV의 홍콩 2배 레버리지 + 국내 2배 레버리지 수급 (1) NAV = Net Asset Value (순자산가치) 3. 금일과 같은 급락 발생 (6/23 : 지수 -9.99%) 현물 동시호가 진행 중 선물에서는 추가 매도 수요가 발생할 수 있음. 이로 인해 베이시스가 +에서 -로 전환될 수 있음. (1) 베이시스 = 선물가격 - 현물가격 (2

1👍1

Signed 정보를DAO

21 Jun 2026, 13:30 UTC604 views2 reactionsread 8 August 2026
Forwarded from @zamboyak

글썼어여 제목으로 어그로좀 끌었음 https://blog.naver.com/sanoulzig/224322786715

2

Signed 정보를DAO

1 Jun 2026, 22:25 UTC911 views4 reactionsread 8 August 2026

2019년 12월, 300만 원으로 시작해 2026년 6월 마침내 100억 원을 달성했습니다. 코인으로 시작해 결국 주식으로 목표를 이뤘네요. 지난 7년이라는 시간 동안, 참 글로 다 적기 힘들 정도로 다사다난했습니다. 어제 샀던 코인이 하루 만에 100배가 뛰기도 했고, 얼굴도 모르는 사람에게 20억 사기를 당하기도 했습니다. 믿고 아꼈던 동생에게 배신을 당한 적도, 반대로 제가 누군가에게 상처를 준 적도 있었습니다. (시간이 많이 흘렀지만, 이제야 진심으로 사과드립니다.) 또, 이 판에 들어오지 않았다면 절대 만나지 못했을 소중하고 엄청난 인연들도 얻었습니다. 막상 목표를 달성하고 나니 그저 덤덤한 마음뿐입니다. 사람은 그릇에 맞게 살아야 한다고들 하는데, 제 그릇은 이제 가득 찬 것 같습니다. 주변에 수백억, 수천억 대 자산가분들이

3👍1

Signed 정보를DAO

1 Jun 2026, 09:36 UTC893 views2 reactionsread 8 August 2026
Forwarded from @pgyinfoPhoto

해외 금융 계좌 신고 관련 정보 ✅신고의무자 - 24년 12월 31일 기준 국내 거주자 또는 국내법인 ✅ 신고기한 - 25년 6월 30일 ✅신고기준금액 - 24년 매월 말일 중 하루라도 모든 해외계좌 (가상자산 포함) 잔액 합계가 5억원 초과 ✅신고대상 - 해외금융회사 등에 개설한 모든 해외금융계좌 내 현금, 주식, 채권, 집합투자증권, 보험상품, 파생상품, 가상자산 등 * 개인지갑은 이번엔 신고대상이 아니라 함 ※ 해외금융계좌 신고 의무 위반. 미(과소) 신고 → 과태료 10% 부과 미(과소) 신고 금액 50억 원 초과 시 → 50억 초과분은 20% 과태료 부과. 형사처벌 및 명단공개 대상. ✅신고방법 홈택스 (www.hometax.go.kr) 또는 손택스 (모바일) 을 이용하여 전자신고 ✅주요 해외거래소 계좌 잔액 확

2

Signed 정보를DAO

1 Jun 2026, 01:42 UTC763 views3 reactionsread 8 August 2026
Photo

저처럼 테더 역프 물리신 분들은 트레디파이에서 롱이나.. ㅠㅠ

3

Signed 정보를DAO

30 May 2026, 02:27 UTC478 views1 reactionsread 8 August 2026
Forwarded from @dolchanchain

자기 전 생각 마무리 : 우리 코인러들은 ai 주식 투자하기에 꽤 좋은 환경에 놓여 있다. Opus 4.8 같은 새 모델이 나오면 바로 써보고, 그걸 돈 버는 수단에 연결해보는 텔레그램 커뮤니티가 있다. 서로의 노하우와 경험도 가감 없이 공유된다. 정확한 타임라인은 기억나지 않지만, 올 2월쯤 오픈클로가 엄청난 바이럴을 타면서 “오픈클로-오케스트레이션”이라는 개념을 텔레그램에서 처음 봤다. 적당히 바이브 코딩에 관심만 있었다면, 그때 오케스트레이션이 뭔지 검색이라도 해봤을 것이다. 그리고 결국 오케스트레이션은 결국 하나의 새로운 투자 컨센서스를 만들어냈다. AI 추론 과정에서 시스템 성능을 극대화하려면 CPU와 GPU 간의 매끄러운 오케스트레이션이 필수. AI 시대에 마치 구시대의 유물처럼 느껴졌던 CPU 기업들(인텔/암드)의 투자 의

1

Signed 정보를DAO

30 May 2026, 02:27 UTC427 viewsread 8 August 2026
Forwarded from @zamboyakPhoto

강세장엔 벌어도 여전히 아쉽다. 6월엔 포모 덜 느끼며 더 잘해봅시다! https://blog.naver.com/sanoulzig/224300771378

Signed 정보를DAO

Showing the 12 most recent of 20 posts we hold for @informationdao. 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.

Citation-graph rank

Citation-graph rank — 894,076 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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

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.

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

“정보를 DAO (공지)” (@informationdao), 4,250 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/informationdao.

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.