名称:尚公主(2026)4K 60FPS S01E01 - E11 杜比全景声 HIFI声 描述:不甘命运的天家嫡女暮晚摇与智谋无双的寒门才俊言尚在岭南相逢、于盛安入局,携手步步破局,共筑清平天下的故事。一群少年各怀心事、各有所求,在乱世惊涛中搅动风云,奔赴理想。 该剧改编自伊人睽睽的同名小说。 百度:https://pan.baidu.com/s/1ZvCxwKUEpK85D15WeaA_dQ?pwd=rkq3 📁 大小:6GB 🏷 标签:#剧情 #尚公主

Channel
百度网盘综合频道
@bdwpzhpd
On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
52,316subscribers
+3,485 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002110524172 |
|---|---|
| Type | Channel |
| Username | @bdwpzhpd |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 27 October 2026 |
| Measurements held | 50 |
| Confirmed unchanged | 1 time, most recently 27 October 2026 |
| On Telegram | t.me/bdwpzhpd |
Topic
Film & TV — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 96% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 27 Oct 2026, 14:31 | 52,316 | +21 |
| 26 Oct 2026, 14:27 | 52,295 | +29 |
| 25 Oct 2026, 13:30 | 52,266 | +36 |
| 24 Oct 2026, 15:10 | 52,230 | +27 |
| 23 Oct 2026, 16:01 | 52,203 | +26 |
| 22 Oct 2026, 16:56 | 52,177 | +41 |
| 21 Oct 2026, 11:45 | 52,136 | +45 |
| 20 Oct 2026, 05:47 | 52,091 | +25 |
| 19 Oct 2026, 05:45 | 52,066 | +36 |
| 18 Oct 2026, 07:17 | 52,030 | +47 |
| 17 Oct 2026, 06:26 | 51,983 | +31 |
| 16 Oct 2026, 05:38 | 51,952 | +45 |
| 15 Oct 2026, 02:56 | 51,907 | +50 |
| 13 Oct 2026, 20:06 | 51,857 | +139 |
| 10 Oct 2026, 07:19 | 51,718 | +119 |
| 6 Oct 2026, 02:42 | 51,599 | +241 |
| 30 Sept 2026, 20:20 | 51,358 | +549 |
| 18 Sept 2026, 09:01 | 50,809 | +91 |
| 16 Sept 2026, 05:01 | 50,718 | +71 |
| 14 Sept 2026, 13:38 | 50,647 | first reading |
Engagement
2,488 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 164 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.515%
- avg views ÷ 52,316 subscribers
- Avg views / post
- 270
- 1,098 posts measured
- Reaction rate
- 0.392%
- reactions ÷ views · ER floor
- Posts in window
- 1,099
- of 2,488 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 345 of 1,098 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 27 October 2026 |
|---|---|
| Posts held | 2,488 (6 August 2026 – 27 October 2026) |
| Views total | 296,067 |
| Reactions total | 402 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 27 Oct 2026, 10:27 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
360 reactions across 286 posts, in 5 distinct kinds. The most used accounts for 73.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 263 | 73.1% | |
| ❤ | 85 | 23.6% | |
| 🔥 | 9 | 2.50% | |
| 🤡 | 2 | 0.556% | |
| 👎 | 1 | 0.278% |
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 311 of the 1,000 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 360 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 1 October 2026 to 27 October 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
名称:予苍龙(2026)4K S01E01 - E14 描述:将门之女岳望舒被献祭龙渊,意外解封龙君离止,二人从敌对到相知,以“压制离火”为交易结盟。她借龙君之力反击岳家与齐王阴谋,他因她学会人间情爱。最终,离止留驻人间,成就一段旷世之恋。 链接:https://pan.baidu.com/s/1Y9O7MbiJRArfoxlRTm40OA?pwd=a1z4 📁 大小:4GB 🏷 标签:#剧情 #予苍龙
❤1
名称:与狼共眠(2026)4K S01E01 - E16 描述:该剧改编自阅文集团旗下QQ阅读作家傅九的同名小说。聚焦新时代青年成长与法治正义,讲述犯罪心理学专家顾言(李艺彤 饰)与伙伴沈聿(张集骏 饰)坚守初心正义,携手侦破疑案、探寻真相的故事。以悬疑博弈融合人性思辨,聚焦人性底线、自我保护等现实议题,紧扣时代脉搏,叙事手法新,节奏紧凑。 链接:https://pan.baidu.com/s/1HOopRJ7TBJF4r_sEJkzCpA?pwd=eawt 📁 大小:3GB 🏷 标签:#剧情 #与狼同眠
名称:她的局(2026)4K S01E01 - E17 HIFI声 描述:余颂(加奈那 饰)为替父讨回公道,以助理身份进入宋家。她用真诚打动宋澄(谭晓凡 饰),与司机阿靖(周大为 饰)结盟,一起搜集证据,将宋家罪行公之于众。但她未被仇恨吞噬,而是挣脱枷锁,领悟到真正的胜利是掌控自己的人生,最终活成向阳而生的自己。 链接:https://pan.baidu.com/s/1gZ0pftrO409wpW2lagc_hg?pwd=2ec2 📁 大小:2GB 🏷 标签:#剧情 #她的局
名称:莫语者(2026)4K S01E01 - E18 描述:卫天在一次行动中救下柏拉图国际酒店的副经理安达,两人在保护与被保护中走到一起。莫语者团队的沙兰、曲胜利、叶婉也在一次次任务中与各自的过往经历和解。最终,莫语者在卫天的带领下加入中安,成功保卫了一带一路经济区上的企业和民众安全。 链接:https://pan.baidu.com/s/1uCIkEtSBE_FRMlNNZAb4dQ?pwd=kqgj 📁 大小:8GB 🏷 标签:#剧情 #莫语者
名称:华灯起(2026)4K S01E01 - E08 描述:1936年上海,女裁缝梅予和携手高利贷债主丁兆,抽丝剥茧,挖出霓虹灯影下的黑暗秘密。 链接:https://pan.baidu.com/s/1mI84NKYDOO0BCzSWdYwn6Q?pwd=p3uw 📁 大小:4GB 🏷 标签:#剧情 #华灯起
名称:好一个乖乖女(2026)4K 臻彩 S01E01 - E26 描述:被养在深闺中备受伯父全家折磨的鹿家二小姐鹿鸣于(徐梦洁 饰)设计逃离了鹿家,却在逃跑过程中意外邂逅了来自香江的段家继承人段休冥(任世豪 饰)。鹿鸣于的聪明、智慧与美丽,深深吸引着段休冥,而从段休冥身上鹿鸣于也敏锐地感受到了自己反击伯父一家并完成复仇的机会。 于是她临时改变计划,回到那个她一心想逃离的家,并将他一步步拉入自己的复仇计划中。然而在这过程中她逐渐发现,自己原本冰冷,只剩下仇恨的内心,却在慢慢相处中逐渐融化…… 链接:https://pan.baidu.com/s/1iin0VlLAiv0OobOSECfCsg?pwd=636u 📁 大小:2.3GB 🏷 标签:#剧情 #好一个乖乖女
名称:富闺可期(2026)4K S01E01 - E20 描述:现代闺蜜田郁圆、林舒迢意外穿进宅斗小说,成了新婚夜便要遭花船构陷、双双惨死的炮灰妯娌。二人联手拆穿大嫂、养女沈宛宛连环毒计与陷阱,一路搞钱求生。冷面世子沈呈身中奇毒,需女主血续命,纨绔三少沈禾暗藏仵作之志,两对情愫渐生。重生原女主宋璋、谋逆三皇子接连发难,四人携手追查岐云关旧案,找出冤屈证人,揭穿皇子滔天罪证,洗刷沈家满门污名,最终挣脱原定悲剧命运,相守安稳度日。 链接:https://pan.baidu.com/s/1naRVdAjgxaZQ4XeAqKfvlg?pwd=s46r 📁 大小:3GB 🏷 标签:#剧情 #富闺可期
名称:仿生迷踪(2026)4K S01E01 - E12 描述:2035年,AI高材生宋扬被诬陷杀害女友母女,逃亡中与觉醒自我意识的仿生人艾达结盟。二人接连破解离奇案件,深挖Cedar集团的黑幕。最终真相揭开,宋扬洗清罪名,艾达为保护宋杨而牺牲,但人类与仿生人迎来了共存的新未来。 链接:https://pan.baidu.com/s/1H42Ehg_522A5ec5COACdJw?pwd=uca4 📁 大小:3GB 🏷 标签:#剧情 #仿生迷踪
名称:大哥请赐教(2026)4K 60FPS S01E01 - E04 杜比音效 描述:重获新生的陈浩来到兄弟坟前醉酒入梦,重回1998年。为改变亲人兄弟悲剧命运,他决心弃恶从善,带领兄弟们正道谋生。几经波折,他得到资助创业,经营小灵通店、涉足地产,期间遭遇犯罪集团王天龙屡次刁难报复。陈浩联合警方,粉碎黑恶势力阴谋,守护身边亲友,与发小郝爱妮收获爱情。他看淡财富,过上平淡生活。陈浩放下过往悔恨,接纳现实,和郝爱妮相伴,决心余生踏实走正途完成自我救赎。 链接:https://pan.baidu.com/s/1-Hwd71F9WiYWxDboZSIkdg?pwd=qard 📁 大小:5GB 🏷 标签:#剧情 #大哥请赐教
名称:谜林(2026)4K 60FPS S01E01 - E08 杜比音效 描述:外来商人汪泓来到辛椿小城,借收购木材调查家中多年前爆炸案真相。木材生意牵动当地多方势力利益,寻找失踪母亲的黎雪菲意外卷入事件。刑警曹进查办本地案件时,逐步窥见旧案隐秘。多方线索交错,众人拨开迷雾,揭开陈年旧事真相,涉案人员受到法律惩处,历经苦难的幸存者开启新生活。 链接:https://pan.baidu.com/s/1kL20nVFd2vYtZZKtyMy2Ng?pwd=6kfv 🏷 标签:#剧情 #谜林
名称:嫁金钗(2026)4K 10bit 60FPS S01E01 - E20 描述:阿丑原是街上倒夜香的低贱少女,人人皆可践踏欺凌,只因一张酷似侯府千金魏娆的面容,意外成为国公府世子陆濯的冲喜新娘。阿丑野心勃勃,一心借机上位,然而濒死的新婚丈夫忽然苏醒,鸠占鹊巢引来连绵灾祸。魏娆(君黛)恨她鸠占鹊巢,急欲除之后快;陆濯以她为蛇蝎妇人,百般提防谋算。国公府明面一团和气,实则陷阱重重、步步杀机。阿丑稳扎稳打精心谋划,手段百出获得丈夫痴爱,更查出了自己身世的秘密,与至亲最终团圆,从底层夜香妇一路逆袭上位,过出光芒万丈的锦绣人生。 百度:https://pan.baidu.com/s/1R2LF_H_K2zMysoWZCzRGRA?pwd=esxf 📁 大小:5GB 🏷 标签:#剧情 #嫁金钗
Showing the 12 most recent of 2,488 posts we hold for @bdwpzhpd. 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.
Posts edited after publishing
@bdwpzhpd edited 4 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 18 August 2026
- Most recent edit
- 12 September 2026
Mentions
Named by 4 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.
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.
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 27 October 2026 — this entry's latest reading, not the date you are reading this.
“百度网盘综合频道” (@bdwpzhpd), 52,316 subscribers as measured 27 October 2026. Telegram Register, tgregister.com/channel/bdwpzhpd.
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.