Channel
@xinxianshi
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Posts · Citations · Cite this entry
940subscribers
-1 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001950152068 |
|---|---|
| Type | Channel |
| Username | @xinxianshi |
| Created | Between 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 8 August 2026 |
| On Telegram | t.me/xinxianshi |
Technology — 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 89% 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.
Posts published here appear word for word on 2 other registered channels. They sit inside a group of 5 channels that share the same post bodies 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.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @xhqcankao/312877 Aug 2026, 01:31 UTC | @xinxianshi/47914 · this entry7 Aug 2026, 02:51 UTC | 1.00 | 80 minutes |
| @xhqcankao/312887 Aug 2026, 02:01 UTC | @xinxianshi/47915 · this entry7 Aug 2026, 02:51 UTC | 1.00 | 50 minutes |
| @xhqcankao/312897 Aug 2026, 02:31 UTC | @xinxianshi/47916 · this entry7 Aug 2026, 02:51 UTC | 1.00 | 20 minutes |
| @xhqcankao/312927 Aug 2026, 04:03 UTC | @xinxianshi/47919 · this entry7 Aug 2026, 04:18 UTC | 1.00 | 14 minutes |
| @xhqcankao/312937 Aug 2026, 04:30 UTC | @xinxianshi/47920 · this entry7 Aug 2026, 05:45 UTC | 1.00 | 74 minutes |
| @xhqcankao/312947 Aug 2026, 05:03 UTC | @xinxianshi/47921 · this entry7 Aug 2026, 05:45 UTC | 1.00 | 42 minutes |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @xhqcankao | 15 (8/8 hand-verifiable sample passed) | 1.00 | 44 minutes | @xhqcankao (15–0) |
| @NEWSPJAPK | 6 (6/6 hand-verifiable sample passed) | 1.00 | 41 minutes | @NEWSPJAPK (6–0) |
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. 21 of the 21 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 20 comparable posts for this entry, running 6 August 2026 to 7 August 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.
Across the whole group of 5, the earliest publisher we hold is @xhqcankao. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 8 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.
This channel’s posts match, word for word or near enough, posts on 4 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 02:48 | 940 | -1 |
| 7 Aug 2026, 10:47 | 941 | no change |
| 7 Aug 2026, 10:33 | 941 | first reading |
20 posts held, back to 6 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 7 August 2026 |
|---|---|
| Posts held | 20 (6 August 2026 – 7 August 2026) |
| Views total | 175 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 10:47 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.
字节跳动Seedance 2.5视频模型API上线 周五，火山引擎正式上线新一代视频生成模型Seedance 2.5 API服务。相较Seedance 2.0，新模型在指令遵循、长叙事、真人感、声画质感等维度全面升级，原生支持30秒视频直出，单次最多可参考50个全模态素材，精准编辑与多角色一致性表现显著增强。 在实测案例中，Seedance 2.5能够准确执行包含秒级时间戳的长Prompt，完成导演级镜头调度与复杂叙事，稳定保持多角色群戏的外形与身份一致性。面部质感与表演细节更贴近真实演员，皮肤纹理、情绪变化与眼神光等微观表达均有提升。模型同时支持十余种语言，可应用于影视、教育、广告、工业仿真、互动内容等场景。 —— 凤凰网科技
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TikTok裁员250人并关闭其纳什维尔办公室 TikTok正在裁员250人，并关闭其纳什维尔办公室，该办公室曾容纳TikTok内容审核团队的部分成员。TikTok USDS合资企业的发言人Zanna Crowley证实了这一消息，称关闭办公室是为了「精简我们的运营，并更好地调整我们的团队以实现长期增长」。 发言人表示：“我们仍完全致力于为在TikTok上创作、发现并连接他们喜爱内容的两亿美国人提供安全、可靠和积极的体验。”此次裁员正值社媒公司越来越依赖AI监控和删除平台上暴力或露骨内容之际。TikTok于2024年租赁的纳什维尔办公室将于10月5日关闭。 —— Techcrunch
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Showing the 12 most recent of 20 posts we hold for @xinxianshi. 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 — 1,277,395 of 1,345,403entries 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 1 registered channel — 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.
Named by
Channels on the register whose posts name this channel's handle.
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 8 August 2026 — this entry's latest reading, not the date you are reading this.
“新鮮事” (@xinxianshi), 940 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/xinxianshi.
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.