Channel
@PD_JB
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
149subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003294505544 |
|---|---|
| Type | Channel |
| Username | @PD_JB |
| Description | 从优质内容，发现优质频道！ 通过我们分享的内容找到喜欢的频道❤️ @PDJB_BOT |
| Created | Between 1 October 2025 and 19 December 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/PD_JB |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 20:16 | 149 | no change |
| 7 Aug 2026, 11:02 | 149 | first reading |
20 posts held, back to 19 December 2025 — 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 22 December 2025. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 8 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.
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
6 reactions across 5 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 6 | 100.0% |
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 5 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 6reactions 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 19 December 2025 to 22 December 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
《躺着赚钱的漫画基金书：人人都能懂的基金入门与实操指南》作者三折人生在国有银行、综合金融集团等多家金融机构有14 余年工作经验。5年间，作者画笔不辍，用13750 张漫画构建了金融体系版图，收获了30 余万名忠实读者。仅是“委托贷款”图解作品的单篇阅读量就超过100 万，得到了业内的高度认可。 ─ 💬 🏷️ #电子书 | 📢 🔥🔥ZBook,|电子书📚| 小说|漫画资源||禁书分享 🔗 https://t.me/ziyuanfeng59
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❤1
大鹏《#长安的荔枝 》观影记录 看完了，感觉李善德比加缪说的西西弗斯荒诞残酷多了，西西弗斯推完石头，最多就是再推一遍，李善德成功了，但间接害了那么多人。他痛苦后悔又如何呢？虽然最后他的朋友家人都没事，也算主角光环的照耀吧。 马伯庸的原著我看过，今天和朋友还说过，虽然好看，但他水平远不止于此，只是写这种东西比较顺手。但这种东西是有上限的，拍到最好也就是大鹏这样了。 #电影 ─ 💬 👍 📢 海龍說 🔗 https://t.me/haotalk
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❤1
名称：夜访吸血鬼 (1994) 1080P 内封简英双语字幕 描述：18世纪的路易斯安娜州，丧失妻女痛不欲生的庄园主路易(布拉德·皮特 饰)遇上了吸血鬼莱斯塔特(汤姆·克鲁斯 饰)，被其施法变成吸血鬼。路易心存人性，不愿意吸血杀人，靠吸食动物的血为生，而莱斯塔特则一心要把路易斯教导成一个真正的吸血同类。 链接：https://www.alipan.com/s/w9se2quAzt8 📁 大小：13.2GB 🏷 标签：#奇幻 #剧情 #惊悚 #夜访吸血鬼 #1080P #内封简英双语字幕 #ali ⚠️ 版权：版权反馈/DMCA 📢 频道 👥 群组 🔍 投稿/搜索 ─ 💬 阿里云盘直链 📢 阿里云盘发布频道 🔗 https://t.me/shareAliyun
❤2
名称：寻秦记 (2001) 1080P 全集 国粤多音轨 简中硬字幕 描述：21世纪特种部队人员项少龙（古天乐 饰）决意要参加穿梭时空的研究，是为了要挽回自己的爱情。但由于时光机的数据出错，把少龙带到了战国时期。当时的嬴政（林峰 饰）还没有登上帝位，更被囚禁于赵国。少龙为了能返回未来，便不惜一切帮助嬴政顺利登上帝位。由于少龙的机智过人与特殊身份，他的能力得到了众人的赏识，因此他也遭到了多方奸狡之人的暗算。 阿里：https://www.alipan.com/s/XDHtM82rEUz 夸克：https://pan.quark.cn/s/e98e28ab3da9 百度：https://pan.baidu.com/s/1wJd1kgF48N_Uu5VtzJXPug?pwd=VA1J 📁 大小：25.3GB 🏷 标签：#剧情 #喜剧 #历史 #寻秦记 #国剧 . 📢国内影视频道：@Aliyun_4K_Movies 📢国外影视频道…
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❤1
从ADHD到超聚焦：多巴胺系统揭示的专注力真相 最近，我偶然了解到了一本书叫《The Dose Effect》。其作者、神经科学家 TJ Power 提出了一个名为 "DOSE" 的核心框架，用以解析驱动人类行为的四种关键大脑化学物质：多巴胺 (Dopamine)、催产素 (Oxytocin)、血清素 (Serotonin) 和内啡肽 (Endorphins)。该理论的核心观点是：当代社会的生活方式（高压、高频数字干扰、低质量人际连接）正在系统性地破坏我们内部的化学平衡，这被认为是现代人普遍焦虑、注意力涣散和动力缺失的根源。 以下是关于这个框架及其应用的几点洞察： 1. 我们经常谈论的“意志力薄弱”、“拖延症”或“情绪低落”，可能并非性格缺陷，而是一种生化层面的失衡。你的感受，在很大程度上是你大脑中 "DOSE" 四种化学物质动态博弈的结果。 2.可以将 "DOSE" 视为你大脑的“内部仪表盘”。多巴胺 (D) 是油门和…
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Showing the 12 most recent of 20 posts we hold for @PD_JB. 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 — 1,108,290 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.
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.
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.
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 8 August 2026 — this entry's latest reading, not the date you are reading this.
“频道推荐&剪报” (@PD_JB), 149 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/PD_JB.
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.