Channel
@democracyresist
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
20subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001631639098 |
|---|---|
| Type | Channel |
| Username | @democracyresist |
| Created | Between 1 December 2021 and 8 January 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/democracyresist |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 16:01 | 20 | no change |
| 7 Aug 2026, 07:00 | 20 | first reading |
20 posts held, back to 8 January 2023 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 1 August 2026 |
|---|---|
| Posts held | 20 (8 January 2023 – 1 August 2026) |
| Views total | 3 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Aug 2026, 16:01 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.
Lifetime counters from Telegram’s own channel header, read 11 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
3 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 2 | 66.7% | |
| ❤ | 1 | 33.3% |
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 2 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 3reactions 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 January 2023 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.
胡錦濤一家中毒身亡？「秦楓爆料文」瘋傳 學者：若屬實恐掀政治風暴 近日，網路上傳出，鳳凰衛視總監秦楓爆料，「中共前領導人胡錦濤、妻子劉永清及兒子胡海峰，3人因食物中毒死亡」，相關消息一出立刻引發熱議。對此，加拿大約克大學副教授沈榮欽指出，這則爆料為何令人震驚，背後可能引發包括習近平在內的中共高層政治鬥爭聯想，更直言「如果爆料屬實，可能會掀起政治風暴」。 網路上瘋傳一張截圖，從畫面中可以看到，鳳凰衛視總監秦楓於7月31日在微博發文爆料，稱「前領導人，包括夫人LYQ，HHF晚餐時，食物中毒，盡力搶救，4點的時候走了」，該圖曝光後，立刻引起各界關注，質疑是否屬實。 沈榮欽在臉書發文表示，秦楓爆料在中國與海外引發極大的關注，秦楓是官三代，家中長輩很多都在中國外交部工作，祖父是前外交部領事司司長、劉少奇秘書秦力真，外公為前外交部總務司司長楊琪良，姑父為前中國外交部長李肇星，父親則為曾任《中國財經報》社長兼總編輯的秦曉鷹。 沈榮欽說…
繼于朦朧後, 再有中國男星 金澤死亡, 前女友及編劇爆料生前曾遭到 潛規則 33歲大陸男星金澤（本名張家瑋）在橫店猝逝，一度傳出因高強度工作導致心肌梗塞，不料其前女友公開金澤生前對話記錄，驚爆他曾遭經理人公司男性高管強制性騷擾與職場霸凌，引發外界震驚和熱議。大陸編劇汪海林隨後在微博發文爆出黑幕。 據金澤前女友釋出的對話截圖與語音內容可知，金澤生前長期承受超長工時，甚至在「華誼兄弟」拍戲期間遭到男性高層侵害。他在對話中痛苦控訴：「陪那些gay的時候」「他把我拖到床上去」，充滿絕望與無助。關鍵詞「曝金澤聊天記錄」迅速登上微博熱搜。 上述對話記錄曝光後，外界推測金澤長期遭權勢逼迫，身心飽受煎熬，最終在工作壓力與心理創傷的雙重打擊下驟然離世。前東家「華誼兄弟」至今未予回應。 【突發】姜濤澳門演唱會請咗炎明熹做嘉賓 2026 香港人生存消息報導
特朗普訪華｜據報元首會面將落實中方購買美國農產品，特朗普稱將與習近平商討對台軍售等 美國總統特朗普在5 月 13 日至 15 日訪問北京，期間與中國國家主席習近平會面。預計雙方將落實中國購買美國農產品，並商討對台軍售、延長貿易戰休戰協議等議題。中方重申反對對台軍售。多間美國企業高層亦隨行。 特朗普抵北京展開訪華行程，將晤習近平談經貿與 AI 外界關注中美雙方將就經貿、人工智能、台灣及國際局勢等議題交換意見 Donald Trump to hold high-stakes meeting with Xi Jinping in China - live updates - BBC News https://www.bbc.com/news/live/cvgz8qverzqt 2026 香港人生存消息報導
今年開始隨住美國統統上台，就會見到中國經濟將會更差 https://t.me/democracyresist
#願粹我命、捍衛我城、全民自救、 打破宿命 #抗爭到底，至死不渝 @A202001020 https://t.me/+UR_G9n75Xohr8bNX
台灣提升大陸、香港、澳門旅遊警示 至第二高「橙色」 建議民眾如非必要避免前往 https://t.me/democracyresist
https://twvalues.github.io/TW-Values/ https://t.me/democracyresist
上海警方破獲網絡騙案，騙徒以普通石頭冒充翡翠原石，誘使受害人在直播平台「賭石」趁機騙錢。案發至今共35人被捕，涉款超過200萬元人民幣。 上海早前有市民在直播平台上「賭石」，豈料轉帳付款後忽遭對方踢出平台，於是報警。警方起初以為是經濟糾紛，調查後才發現是新型騙案。 騙徒利用噴漆為石英石上色，冒充翡翠原石，並誘騙受害人在平台上「賭石」。為了讓受害人信以為真，騙徒更會假扮其他買家下單。實際上，直播間內只有受害人一個是真正買家。 上海市公安局臨港新片區公安處副處長：「直播間裏面一般有三個角色。一個是主播或者說主持人；還有一個是所謂的玉石商人；其他的所謂觀眾，或者說是下單的這些人，一個人可以冒充十個，甚至二十個這樣的一個身份。然後再烘托氣氛，然後就是把這個價格抬上去。」 受害人付款後主播便會解石，並由玉石商人即場回收，賺蝕全由騙徒操控。騙徒更會事先準備好假的翡翠吊墜，一旦受害人起疑，便寄給受害人。 上海市公安局臨港新片區公安處民警康明明…
【民怨沸騰】中國2024全國兩會召開之際，江蘇省公安廳及張家港市政府，分別遭炸彈襲擊，事發後已有人公開承認襲擊，「是我炸」，並要求「懲戒貪官，還我工廠」，甚至留下實名與身分證號碼。現時消息已被中國全網封鎖。 7日下午，南京市樓高19層的江蘇省公安廳大樓，頂部數層冒出濃煙。南京警方立刻封閉街道，多輛消防車抵達，引發民眾圍觀。許多中國網友在社群發布片段和相片，但很快遭當局刪除，「江蘇省公安廳著火」相關話題被封鎖。 同日上午，江蘇省市政府大樓入口亦遭襲擊，冒出大片白煙，玻璃和門框嚴重損壞，門外留下一個變形的石油氣罐。 其後流出的傳單，疑似是襲擊現場留下，清楚寫上「張家港市政府是我炸，我要求懲戒貪官，還我工廠，私宅等不平等待遇。正在等待自首」，署名「袁劍虹」和他的身分證號碼。不少中國網民留言讚揚袁劍虹，「敢於向政府討說法才算是好漢！」 https://t.me/democracyresist
中共政協、人大「兩會」召開之際，江蘇省週四（7日）在一天之內有2個政府機關大樓發生事故，一處是江蘇省張家港市政府大樓爆炸，另一處是江蘇省公安廳大樓發生大火，相關消息目前在中國境內完全被封鎖，但在「牆外」引發關注。 旅義華僑作家李穎7日在X平台表示，週四上午江蘇張家港市政府大樓發生爆炸事件，現場流出的畫面可以看到政府建築冒出陣陣濃煙，大樓入口處可見玻璃和門框嚴重毀損，玻璃碎屑和殘骸散落一地，不遠處還能發現一個被炸到變形的煤氣罐。 另外，江蘇省公安廳7日下午因不明原因發生大火，中國微博一度瘋傳公安廳大樓竄出陣陣濃煙的影像畫面，但沒多久後相關話題在微博上幾乎完全消失，輸入「江蘇省公安廳著火」等關鍵字也只會跳出「根據相關法律法規和政策，該話題內容未予顯示」的通知。 目前都未有中媒報導上述兩起重大事故，後續發展和事發原因都不得而知。不過針對張家港市政府大樓爆炸，李穎分享一張攝於7日上午6點44分的網傳照片，照片中可見一份署名為「袁劍虹」的…
昨（1）日發出長文，坦言自己認為台灣最缺少的就是國際觀：「我剛來台灣的時候，就發現許多台灣人離國際事實很遠」，隨後提到自己曾遇過好幾個實際案例，分別是「以為所有的外國人都是美國人，外語只有英文一種！」、「知道土耳其之後，也會問我土耳其人可以娶四個老婆嗎？」、「有時候跟台灣朋友聊到歐盟時，也發現台灣人不太在意別的國家」、「打開看新聞也會發現！很多美食新聞、八卦新聞」、「想要看國際新聞幾乎要靠自己去搜尋資訊」。 吳鳳提到，在不同國家的人互相交流時，外國人很喜歡互相分享不同的國際消息，從政治到科技許多可以聊的議題，所以大多外國人有一個基本的國際觀。事實上是擁有國際觀也能改變台灣人出國遇到各國來的人時的互動，「沒有國際觀怎麼跟外國人進行完整的對話呢？不可能永遠聊台灣的美食多好吃吧？」 「國際事實跟我沒什麼關係！」也許有人會這樣覺得，但吳鳳也覺得：「每一位台灣人多少都需要接觸國際新聞跟這方面的資訊。因為台灣在國際舞台上能發揮的空間非…
https://www.cna.com.tw/news/acn/202402230044.aspx?utm_medium=app&utm_source=cna.app&utm_campaign=inapp_share https://t.me/democracyresist
Showing the 12 most recent of 20 posts we hold for @democracyresist. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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.
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 August 2026 — this entry's latest reading, not the date you are reading this.
“民主革命” (@democracyresist), 20 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/democracyresist.
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.