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Channel

douView × 银幕🐷🐷🍿

@douView

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

779subscribers

+0 since we began measuring on 10 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002306738667
TypeChannel
Username@douView
Description分享最新银幕资讯 X 接影评投稿 投稿机器人⼁ @douView_bot 联名公益服⼁ @doubon 这里是doubon的旗下频道 「银幕猪猪报 @GGBond_b」主理
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded10 August 2026
Last confirmed live10 August 2026
Measurements held2
On Telegramt.me/douView

Growth

77910 Aug 2026, 00:47 — 779 subscribers10 Aug 2026, 01:00 — 779 subscribers10 Aug 2026, 00:4710 Aug 2026, 01:00
2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 778–780 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 01:00779no change
10 Aug 2026, 00:47779first reading

Engagement

20 posts held, back to 6 June 2026the 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 · 30 days
51.5%
avg views ÷ 779 subscribers
Avg views / post
401
2 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
2
of 20 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 22 July 2026
Posts held20 (6 June 202622 July 2026)
Views total802
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Aug 2026, 01:00 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.

What this channel posts

Photos
3,200
Videos
276
Links
1,570

Lifetime counters from Telegram’s own channel header, read 10 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Reaction mix

6 reactions across 5 posts, in 3 distinct kinds. The most used accounts for 66.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
466.7%
👍116.7%
🥰116.7%

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 6 June 2026 to 22 July 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

22 Jul 2026, 11:00 UTC394 viewsread 10 August 2026

#互推 【音声&涩涩】永不消逝的音声 【炒币资讯】币圈快讯 【医学期刊】来一点医学科学前沿🤯🤯🥹🥹 【资源分享】小声逼逼 【苹果限免】 App Store 限免应用 & ... 【科技分享】折腾啥 【网络分享】书墨资源 【书籍分享】全能搜书|频道 【影视分享】douView × 银幕🐷🐷🍿 Powered by @Summer_Clear_Sky_Bot

19 Jul 2026, 22:30 UTC408 viewsread 10 August 2026

#迷影漫谈 (转载)2.39:1是诺兰最好的归宿 诺兰的摄影和调度还是那么普信。我并没有看1.43:1的IMAX GT,看的是1.9:1中国巨幕,但画面观感已经足够拉垮,摄影和调度完全没有针对大画幅的视觉系统做相应的设计。 1.灾难的剪辑 电影前半段在台词信息量已经很多的情况下,对话戏使用了非常频繁的正反打对剪,几乎是一句一剪,谁开口就给谁镜头,观众的眼睛要在巨幕上一会儿看这边一会儿看另一边,还要低头看字幕,更别提对话中还要剪进另一条故事线的插叙,银幕越大只会看得越累。在马达和海瑟薇的对话戏里甚至还出现了同机位的跳切… 2.疲软的调度 诺兰烘托情绪一向是依赖 多场戏交叉剪辑>单场戏调度,他最有名的几部片子都是如此,所以你不会在他的电影里找到任何一场值得说道的单场戏,甚至他从影至今也没有拍出过一个精彩的长镜头。场面调度是导演最核心的工作,大画幅则是这项工作最好的舞台,而诺兰完全浪费了这个舞台。大家都知道他不会拍动作戏,正是因为拍

2 Jul 2026, 15:15 UTC446 views1 reactionsread 10 August 2026

《挽救计划》 好看好看好看。是阔别多年的太空科幻片,比起太空歌剧般的《星际穿越》,《挽救计划》更像是太空童话,不够梦幻但很温暖(最后对前者的致敬很惊喜)。不愧是我最喜欢的《蜘蛛侠:平行宇宙》导演,拍摄手法和镜头转换还是那么戳中我,配乐也很赞。作为当代科幻小说,作者对外星人的构想是超脱的,有别于以往的形象,但在整个剧情设定下既有想象力又合理,很有新意,很喜欢。也没有美式套路,男女主没有激情戏,一步步回忆起上船的原因,和最终不返航的结局非常自洽👎👎👎。 via 匿名

👍1

27 Jun 2026, 05:30 UTC449 views1 reactionsread 10 August 2026

《红色康拜因》​ 在中国电影资料馆江南分馆。康拜因原来是combine的英译,红色的收割机驶在麦田中,麦子似乎没有那般饱和的金黄,暗藏着父子的矛盾。喜欢画面讲究的构图,而结局带来的失落感,是现实压垮幻想的最后一穗。​ 《日掛中天》​ 在电影资料馆江南分馆路演场,正如导演所说不用戏剧冲突来推动情节,而是依靠人物心境的变化推动,乍一眼看起来有些许枯燥,而后半段特别是结局以及演技使得电影又有了代入感和别样的冲击。​ 《浩劫》​ 观于中国电影资料馆江南分馆,9.5小时的观影伴着昏迷再看,看了再昏迷,算是啃了下来。在采访对话中展开,没有历史的纪实影像,通过对话文字、被采访者的神情和遗址,在想象中去追忆那段历史。印象深刻的是关于毒气室中关于尸体的分布景象,上半场最后改装卡车的描述,日记中关于有人拿最后的钱交房租,也不愿意买食物,只是不想死在街上而要更有尊严的逝去……脑海里是挣扎与沉痛。最后只是觉得自身对于历史的了解还远远不够。​ 《气球》​

1

21 Jun 2026, 07:10 UTC347 views2 reactionsread 10 August 2026

《你的名字》 第一次看《你的名字》的时候根本没想到会哭。买票的时候还在想,就看个动画片而已。但到了最后那个转身的镜头,眼泪就出来了。不是特别夸张的那种哭,就是眼眶有点酸,视线有点模糊。 印象最深的是两个人一直在找彼此但又互相看不见的那种感觉。我走出影院的时候在想,生活中也有这样的时刻吧,某个人其实就在你身边,但你们就是错过了。最后他们总算找到对方了,那句"你的名字是"的时候,感觉整个故事才真的完整起来。 画面特别美,特别是东京那些场景。但坦白说,最打动我的不是画面,而是那种终于找到答案的感觉。 《秒速5厘米》 这部电影看得我有点难受。看完之后的很长时间我都没什么精神,脑子里就想着樱花和列车那些画面。 故事很简单啊,两个人就是错过了。没有什么神奇的时空转换,也没有什么大的转折,就是一步步地离开彼此。最后在街上擦肩而过那段,我有点绷不住。不是号啕大哭,就是感觉特别空,像心里被挖了一个洞。 看完这部电影有点后悔,因为它真的会让你想起自

2

21 Jun 2026, 06:34 UTC226 views1 reactionsread 10 August 2026

《七宗罪》 这片子我拖了很久才看,因为听说是讲连环杀手的,以为是那种血呼刺啦的虐杀片。看完才知道,真正吓人的不是那些死法,而是那种绝望的氛围和结局的无力感。老侦探萨默塞特和年轻但是易怒的米尔斯(皮特年轻的时候感觉很适合演这种角色)搭档追一个用七宗罪作案的凶手。"暴食""贪婪""懒惰""淫欲""傲慢"——每个人死法都不一样,但都很渗人。最绝的倒不是凶手的手法,而是这个叫约翰·杜的混蛋居然自己去自首,然后把警察引到荒野,来了个最后两桩罪:"嫉妒"和"愤怒"。 "What's in the box?"——这句台词真的让人汗毛倒立。但真正看到那个画面的时候,根本没有心思玩梗。米尔斯知道盒子里是妻子的头,而且她已经怀孕了,凶手就在眼前笑。你明知道开枪就中了连环套,但换你你也开。芬奇把你逼到那个情绪顶点,让你自己做出跟米尔斯一样的选择。凯文·史派西只出场了最后二十分钟,但那个表演让我记到现在。 《看不见的客人》 西班牙悬疑片一直挺能打的,这

1

21 Jun 2026, 06:05 UTC170 viewsread 10 August 2026

如果说一部电影能改变一个人对某种艺术形式的轨迹,那《倒数时刻》绝对是我的那个转折点。因为这部作品,让我喜欢上了音乐电影,也因为这部电影,让我从大银幕走向了线下剧场,去真实地感受舞台和追光灯下的心跳。 起初会看这部电影,完全是因为他的主演是加菲,作为我一直偏爱的演员,从《社交网络》《超凡蜘蛛侠》到《血战钢锯岭》,他的表演永远都能击中我。所以我在不了解这部电影的背景下点开了《倒数时刻》,可能对于有些人来说剧情有些肤浅老套,中年危机,理想与面包种种套路皆备,但是对于当时从没听过西区,百老汇的我来说一切又都是那么的新奇,最后jon的作品大获成功但是他却没有机会看到。 因为这部电影,我曾有一段时间迷上了剧场,去追寻那种无可替代的现场共振。尽管最近因为工作连轴转,那些线下演出的计划暂时被搁置,但每次在个人的年度观影系统里归档、回看观影记录时,《倒数时刻》始终占据着一个极其特别的位置。现在,在偶尔闲暇的周末,我依然会选择走进电影院去享受片刻的

21 Jun 2026, 06:05 UTC151 viewsread 10 August 2026

《给阿嬷的情书》 这部电影我是在上映第二周和女朋友去看的,本来没抱太大期望,结果在影院哭得稀里哗啦。故事讲的是潮汕阿嬷叶淑柔守了大半辈子,跟"下南洋"的丈夫靠侨批通信。孙子晓伟因为欠债跑去泰国找传闻中发财的阿公,结果发现阿公早就死了——这些年一直跟阿嬷写信寄钱的,居然是个素不相识的女人谢南枝。 说实话剧情听起来有点像狗血家庭剧,但导演拍得很克制,没有刻意煽情。潮汕话对白听着特别亲切,那些侨批上的字句、阿嬷等信的日常,都有种实实在在的烟火气。我尤其喜欢老年阿嬷知道真相后那场戏——她没有大哭大闹,只是坐在那里,慢慢翻着那些信,脸上的表情说不上是悲伤还是释然。片尾曲《月下煮茶》也很搭,听完能发呆好一会儿。 《星际穿越》 这片子我刷了三遍,第一遍是在家用老台式看的,后来IMAX重映又去了两次。诺兰这次搭上了物理学家基普·索恩的理论,从枯萎病肆虐的地球讲起,库珀带着人类最后的希望穿越虫洞去找新家园。最让我震撼的还是"米勒星一小时等于地球七

17 Jun 2026, 06:43 UTC168 viewsread 10 August 2026

德国科幻《寂静的朋友》 看完《寂静的朋友》,我脑子里第一个蹦出来的词是“温柔”。这大概是史上最不像科幻片的科幻片了。没有飞船,没有机器人,没有宇宙战争,只有一棵在德国大学植物园里站了上百年的银杏树,静静地看着三个时代的人,如何笨拙又执着地试图与它对话。 电影用三种不同的胶片质感,把1908年、1972年、2020年切割成三个独立又互相映照的梦。黑白影像里的女学生用镜头探索植物的秘密,像在显微镜里寻找整个宇宙的秩序;彩色胶片下的年轻人,失恋后蹲在天竺葵前,仿佛能听见另一个生命的呼吸;而数字时代里的梁朝伟,给古树连上脑电波设备,想“听”懂它的沉默。三段故事,讲的其实是同一件事:我们如何确认自己不是孤岛。 导演茵叶蒂的厉害之处,是把这么“玄”的主题拍得一点不闷。科学的严谨和诗意的想象,在她手里像两股拧在一起的藤蔓。你以为在看一部关于植物学的纪录片,转眼就被拉进一个关于存在与感知的哲学命题里。这种“软科幻”的魅力,恰恰在于它离我们并不遥

12 Jun 2026, 09:51 UTC196 viewsread 10 August 2026

《凶器》 《野蛮人》导演的新作,这次他通过多线叙事,像几个互不相干的故事,可最后收网的时候,你会发现每一段都暗藏杀机。全片弥漫着一种无法预料的恶意,冷冽又荒诞,看完后背发凉。说实话,虽然网上有人嫌节奏慢,但作为恐怖片,能有这个完成度,已经很难得了。 《首尔之春》 如果说贾樟柯拍时代是“温水煮青蛙”,那金成洙就是把历史塞进了高压锅,还顺手把阀门焊死了。即便你早已知晓结局,那九小时的权力洗牌和人性背叛,依然能把你逼得当场窒息。最后独裁者在厕所狂笑的镜头,简直是神来之笔——时代的车轮碾过去,普通人连声响都发不出来,只剩满银幕的荒凉。 《落叶归根》 国产公路片的无冕之王。本山大叔背着工友的尸体往家走,一路上遇到的牛鬼蛇神,就是一幅活生生的底层众生相。这片子粗糙、土气,甚至有点荒诞,但它偏偏用这种最笨拙的方式,把中国人骨子里对“入土为安”的执念和活下去的坚韧,拍得让人又哭又笑。很多微表情至今难忘,仿佛下一秒你就能在生活中遇到这样的人。中国

9 Jun 2026, 08:59 UTC189 viewsread 10 August 2026
Photo

从世俗到超脱,一缕禅机后的寂寥 评胡金铨《侠女》 蒲松龄笔下的侠女,“艳如桃李,冷如霜雪”生子报恩,手刃仇雠,然后“一闪如电”消失于茫茫人世。这是世俗间的侠——恩怨分明,来去如风。 胡金铨却把这则故事拍成了另一重境界。 电影改动最妙的一笔,是将那无名无姓的寡女,赋以具体身份——东林党人杨涟之女杨慧贞。这一改,侠女便不再是深山野岭的孤绝剑客,而成了党争倾轧的遗孤。她的剑,不再只因个人的仇,更因家国天下的恨。 但胡金铨的野心远远不止于此。 看那场名垂影史的竹林大战,杨慧贞借石将军之力跃上竹枝,从空中俯冲而下刺死东厂番役。翻阅当时的报导,胡金铨将短短五分钟的戏切成一百多个镜头,演员在不借助吊钢丝的情况下,只通过蹦床完成跳跃动作,再通过每镜四画格的剪辑,竟制造出飞升的视觉效果。这不仅仅是技法的革命,更是那一缕禅机——侠的极致,恰是侠的虚幻。 真正点题的,是慧圆法师。聊斋原文蒲松龄文末借异史氏之口说:“人必室有侠女,而后可以畜娈童也”这

Showing the 12 most recent of 20 posts we hold for @douView. 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

Citation-graph rank — 446,432 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.

Forward network

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.

Mentions

Named by 3 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.

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 10 August 2026 — this entry's latest reading, not the date you are reading this.

“douView × 银幕🐷🐷🍿” (@douView), 779 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/douView.

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.