Channel
@chinanewsdc
On this record: Topic · Observations · Growth · Engagement · Posts · Citations · Handles named that no longer answer · Cite this entry
1,156subscribers
-271 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1003103420772 |
|---|---|
| Type | Channel |
| Username | @chinanewsdc |
| Created | Between 1 September 2025 and 30 November 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 17 August 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/chinanewsdc |
National 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 11 August 2026 and assigned it the closest of 31 fixed categories, at 73% 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 why it has no browse page of its own yet.
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.
46,200 average views per post against 1,156 subscribers — an engagement rate of 3995.2%. Across the 2,232 registered channels in the same cohort — 1,000–3,162 subscribers, posting mainly in Chinese — the middle half sit between 5.00% and 36.1%, with a median of 15.6%.
| Window | 30 days (19 July 2026 – 18 August 2026) |
|---|---|
| Posts measured | 20 of 20 published in the window (0 exact, 20 rounded by Telegram) |
| Views totalled | 923,700 |
| Mature posts only | 3996.5% over 19 posts read at least 24h after publication |
| Subscribers | 1,156 measured 17 August 2026 |
| Cohort | b1000:zho · 2,232 channels · p10 1.08% · p25 5.00% · p50 15.6% · p75 36.1% · p90 63.9% |
| Position in cohort | 100.000th percentile · 256.6× the cohort median |
| Uncertainty | ±0.25% of the figure, from Telegram’s rounding |
| Post language | Chinese · 100.0%of the window’s posts |
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 18 August 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 22:03 | 1,156 | -95 |
| 14 Aug 2026, 13:07 | 1,251 | -60 |
| 11 Aug 2026, 06:11 | 1,311 | -58 |
| 8 Aug 2026, 16:13 | 1,369 | -58 |
| 7 Aug 2026, 22:03 | 1,427 | no change |
| 7 Aug 2026, 19:09 | 1,427 | first reading |
20 posts held, back to 19 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 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 7 August 2026 |
|---|---|
| Posts held | 20 (19 July 2026 – 7 August 2026) |
| Views total | 869,200 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 22:03 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.
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💬 每日新闻 #DC国内新闻每日简报 2️⃣0️⃣2️⃣6️⃣年7️⃣月2️⃣9️⃣日，星期三， 农历六月十六 #三分钟知晓天下事 ——————————————— 1.日本7.1级强震已致多人死亡：熊本发生强震，现场传出哭喊声，造成严重人员伤亡。 2.日本熊本坍塌购物中心多人被困：地震导致购物中心坍塌，救援工作仍在进行。 3.日本强震引发超100次余震：专家警告余震风险，民众需提高警惕。 4.基辅无人机展遭导弹突袭11名高官身亡：乌克兰导弹袭击导致多名高官遇难。 5.普京称俄罗斯未来岌岌可危：俄罗斯总统发出警告，暗示国家安全形势严峻。 6. SK海力士财报不及预期：公司公布第二季度财报，投资者反应平淡，业绩显著下滑。 7.韩国监管层紧急出手：针对市场波动，制定新规保护投资者。 8.台风“白海豚”已增强为超强台风级：气象部门发出警告，提醒民众做好防范准备。 9.医院药学部主任帮药商卖超10亿元药：贪污案件引发公众…
💬 每日新闻 #DC国内新闻每日简报 2️⃣0️⃣2️⃣6️⃣年7️⃣月2️⃣8️⃣日，星期二， 农历六月十五 #三分钟知晓天下事 ——————————————— 1.唐山大地震50周年：纪念抗震救灾，探讨如何建设新唐山。 2.美股迎来芯片风暴：半导体公司股价波动，苹果重返市值第一。 3.美枪击事件：15岁嫌疑人造成3死4伤，引发社会关注。 4.女子从18层坠楼幸存：亲属发声，强调心理支持的重要性。 5.长鑫科技上市：行业期望高，周边房屋供不应求。 6.普京分享恢复精力秘诀：引发对健康生活方式的讨论。 7.湖北考生681分考北大奖励：一名考生得到3万助学金，成为媒体焦点。 8.唐山大地震救援珍贵影像：发布珍贵影像，回顾历史教训。 9.美抛200%关税：印度仿制药短缺，影响全球医疗市场。 10.长鑫科技未来发展：分析其在市场中的角色及影响。 11.校园筛查发现“老年病”：引起社会对年轻人健康的关注。 12. 9…
💬 每日新闻 #DC国内新闻每日简报 2️⃣0️⃣2️⃣6️⃣年7️⃣月2️⃣7️⃣日，星期一， 农历六月十四 #三分钟知晓天下事 ——————————————— 1.长鑫科技上市：今日在A股市场正式上市，周边酒店一房难求。 2.甘肃渭源山洪：突发山洪已致10死23伤，救援工作仍在进行中，已营救174人。 3.台风红霞：成为本年度最强台风之一，广东武警迅速展开救援，现场视频曝光。 4.法国西班牙野火：野火肆虐，30万人紧急撤离，情况持续严峻。 5.重庆彭水失联中巴车：在山体崩塌现场发现遗骸，调查仍在进行中。 6.伊朗暂停报复：同美国恢复对话，局势有所缓和。 7.央视曝光有毒养生神药：亳州随后成立调查组，持续关注药品安全。 8.暑假博物馆热度：显著上升，家庭及学生参观人数增加。 9.男子将熊掌赠友被查：此举引发法律问题，涉嫌非法猎捕。 10.甘肃山洪情侣获救：虽被冲走，幸遇货车及时施救。 11.长鑫科技对A股影…
Showing the 12 most recent of 20 posts we hold for @chinanewsdc. 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 — 82,175 of 1,549,376entries 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.
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.
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.
@chinanewsdc named 5 handles 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.
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.
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 17 August 2026 — this entry's latest reading, not the date you are reading this.
“DC国内外新闻每日简报🐲” (@chinanewsdc), 1,156 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/chinanewsdc.
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.