Channel
@GermanyChineseHub
On this record: Growth · Engagement · Posts · Citations · Cite this entry
1,208subscribers
-1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1004308382506 |
|---|---|
| Type | Channel |
| Username | @GermanyChineseHub |
| Created | Between 1 June 2026 and 3 August 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 10 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 10 August 2026 |
| On Telegram | t.me/GermanyChineseHub |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 10 Aug 2026, 13:07 | 1,208 | -1 |
| 6 Aug 2026, 20:01 | 1,209 | no change |
| 6 Aug 2026, 19:52 | 1,209 | first reading |
20 posts held, back to 3 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 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 6 August 2026 |
|---|---|
| Posts held | 20 (3 August 2026 – 6 August 2026) |
| Views total | 55 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 20:01 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.
德国图书统一定价：为何线上线下同价 在德国购书时，无论线上平台、大型零售商还是社区书店，新书价格往往一致。这源于德国实行的图书统一定价制度（Buchpreisbindung）。 该制度依据《图书定价法》（Buchpreisbindungsgesetz，简称BuchPrG），强制要求零售商以固定价格销售新书。法律禁止零售商擅自降价或提价，确保同一本书在任何销售渠道售价相同。 这一政策旨在保护小型书店的生存空间，避免大型连锁和电商通过价格战挤压市场，同时维护出版生态的多样性。对消费者而言，购书价格透明，无需比价，但促销折扣空间受限。 @GermanyChineseHub
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柏林新应用实时共享查票位置 柏林一款名为FreiFahren的社区驱动应用，允许公共交通用户实时分享和查看全市火车及有轨电车线路上的查票信息。该服务由公民倡议组织FreiFahren e.V.开发，将用户报告的查票地点显示在地图上，并根据近期报告标注可能更常查票的路线。 应用创始人表示，该项目旨在帮助乘客规避查票。目前该应用已覆盖柏林大部分公共交通网络，用户可随时提交或查看查票员所在位置。 #德国华人 #德国 #柏林 #公共交通 #查票 #FreiFahren #应用 @GermanyChineseHub
巴伐利亚2027年推行公共交通刷卡进出计费 巴伐利亚州计划自2027年初起，在全州公共交通网络逐步推广基于智能手机的“刷卡进出”（tap in/tap out）票务系统。乘客可通过移动应用在乘坐公交、地铁（U-Bahn）或火车前完成进站登记，到达目的地后再出站结算，系统将自动计算票价。 州交通部门表示，此举旨在简化购票流程，减少乘客手动选择票种的麻烦。该系统将分阶段引入，覆盖全州范围的公共交通网络。 对在德华人而言，新系统上线后乘坐公共交通将无需提前购买单程票或日票，直接手机扫码进出即可，但需留意手机电量及网络连接，确保进出站记录完整，避免因未正确刷卡产生额外费用。 @GermanyChineseHub
莱比锡机场发现载弹无人机 内政部长称威胁升级 德国联邦内政部长多布林特将莱比锡-哈勒机场发现载有爆炸物无人机一事定性为“专业混合威胁场景”，称其代表“新的危险级别”。事件发生于本周一夜间，机场方面在发现后采取应对措施。 柏林举行柏林墙修建65周年纪念活动。联邦议院将审议一份反对加密货币税收改革的请愿书。 涉事无人机在莱比锡-哈勒机场被发现，该机场为货运枢纽，事件引发对关键基础设施安全的关注。目前相关调查仍在进行中。 #德国华人 #德国 #莱比锡 #无人机 #机场安全 #内政部 #柏林墙 #加密货币 @GermanyChineseHub
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德国非营业时间就医指南 在德国，若晚间或周末需要医疗帮助，并非必须前往医院急诊室。德国医疗体系设有专门的非营业时间值班服务，可帮助患者获得及时治疗。 非营业时间值班医生服务 德国各联邦州均设有统一的医疗值班热线116117。拨打此号码，可接通当地非营业时间医疗服务中心，接线员会评估病情并安排合适的就诊方式，包括值班诊所、上门诊疗或紧急转诊。该服务适用于晚间、周末及公共假日。 何时应直接拨打112 116117主要处理非紧急但需及时处理的医疗问题。若出现严重胸痛、呼吸困难、大量出血、意识丧失等危及生命的症状，应立即拨打112急救电话，而非等待值班医生服务。 前往值班诊所的注意事项 通过116117预约后，患者可前往就近的值班诊所（Bereitschaftspraxis）。此类诊所通常设在医院内或市区中心，营业时间集中在晚间和周末。就诊时需携带医保卡，费用由保险公司承担。建议提前电话确认具体位置和开放时间，避免白跑一趟…
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Showing the 12 most recent of 20 posts we hold for @GermanyChineseHub. 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 — 86,846 of 1,151,006entries 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.
Named by 39 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 24 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.
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 10 August 2026 — this entry's latest reading, not the date you are reading this.
“德国新闻（柏林 慕尼黑）” (@GermanyChineseHub), 1,208 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/GermanyChineseHub.
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.