楊錦麟 engagement report
@m_wo8y - 195K followers on X
Measured over 10 original posts from a 30-day window, last computed on October 10, 2026.
Engagement
A typical post picks up 901 interactions against 195K followers, an engagement rate of 0.461%. Measured over 10 original posts, its engagement rate beats 84% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 45K times each, and 1.98% of those impressions turn into an interaction. That is about 23.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 15:00 UTC, and Friday is the busiest day of the week. Of the 10 posts sampled, 80% carry an image or video and 30% link out. The account's strongest tracked post pulled 13K interactions, about 14x its own typical post.
Measured over 10 original posts from a 30-day window, last computed on October 10, 2026.
Compared with accounts its own size
楊錦麟's engagement rate beats 84% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 62% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.461%, 楊錦麟 sits above the 50th percentile of the 204,956 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 15:00 UTC, and Friday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 80% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 30% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 80% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 30% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 571 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 24, 202614x their median
Paul Laurenzi https://t.co/JZYIKAK7vU
- Jul 30, 202610x their median
Un señor muy amable, alto y guapo llamado Pedro se fue al campo y le compró un burro a un viejo campesino por 500€. El anciano acordó entregarle el animal al día siguiente. Pero al día siguiente el campesino le dijo: - Lo siento Don Pedro pero el burro murió. - Bueno, entonces devuélvame mi dinero. Dijo Pedro. - No puedo. Lo gasté todo. - Pues entrégueme el burro. - ¿Y para qué? ¿Qué vas a hacer con un burro muerto? - Lo voy a rifar. - ¿Cómo vas a rifar un burro muerto? - No le diré a nadie que está muerto. Tiempo después, el campesino se encontró con Pedro. - ¿Qué pasó con el burro? - Lo rifé, vendí 500 números a 20€ cada uno y gané 10,000€. - ¿Y nadie se quejó? - Solo el ganador y le devolví sus 20€. Pedro se hizo político. Llegó a ser Asesor, Concejal, Diputado, Secretario general de su partido y después Presidente y enchufó a familiares y amigos y se hizo rico y poderoso. ¿Por qué? Porque encontró muchos burros en su camino y los fue rifando a mucha gente ingenua y vió que habiendo ingenuos podía llegar a Presidente. Y ahí estamos. Y como dijo George Orwell: "Un pueblo que vota por corruptos, ladrones y prófugos, no es víctima, sino cómplice."
- Oct 1, 20265.4x their median
"The Embrace" By Nick Alm. 🖌️🌹 Swedish painter. Oil on canvas. https://t.co/PwxnUPizH0
- Aug 24, 20263.4x their median
人民日报与中央电视台，是如何掩盖恒大金融骗局，为许家印犯罪保驾护航： 一、2015年5月7日，国际评级机构标准普尔把恒大的长期企业信用评级由“BB-”下调至“B+”，展望为负面。 中共官方媒体立马炸了锅，指责标准普尔造谣，已经沦为美国的政治工具，毫无公信力。大骂美帝诋毁中国资本市场，“亡我之心不死”。 为了反击西方“造谣”，2015年6月16日，国内三大评级机构中诚信证评、大公国际、联合评级竟然同时给予恒大以AAA的主体最高信用等级，评级展望为稳定。 这个评级意味着恒大的信誉极高，还债能力极强。 相关官方/主流媒体报道包括： 人民网（2015年6月16日）：《国内首家！三大机构同时给予恒大3A评级》（图1-2） 明确报道三大机构齐授AAA，并引用资深评级人士称“创造了中国企业信用评级的个案”，同时暗示这是对境外评级的话语权争夺。 中国证券报·中证网（2015年6月16日）：《国内三机构齐亮AAA 恒大创国内企业首例》 详细说明三大机构评级理由（成本控制、布局均衡、销售增长等），并强调AAA罕见且多为大型央企才有。 中国新闻网、中国网、光明网等也同步转载或报道，口径高度一致：强调国内机构更了解中国企业、评级更客观，并对比境外机构偏低评级。 人民日报这样评论： “同一家企业，在国内机构与国外机构的评级结果中南辕北辙究竟是什么原因？资深分析人士称，境外机构对中国企业评级偏低，客观上有不了解企业和评级标准僵化等因素。而另一方面，主观上也有夸大中国经济和中国企业潜在风险的西方惯性思维，不排除成为海外做空机构帮凶的可能。” 二、2016年4月12日，标准普尔再次将恒大的长期企业信用等级由“B+”下调至“B-”，评级展望为负面，同时将恒大地税优先无抵押票据的长期债务评级由“B”下调至“CCC+”。 标普对恒大的评级下调再次惹恼了官媒，2018年8月7日，央视用一组耀眼的数字来为恒大护航：2018年上半年净利润超520亿，核心业务利润超546亿，净负债率从去年末的184%大幅下降至130%以下，实现高质量增长。 央视（CCTV-2《交易时间》栏目，2015年8月7日）： 节目《热点扫描 各大房企发布中报业绩预告 恒大半年盈利大增》专门报道了恒大发布正面盈利预告。(图3） 中国新闻网（2018年8月7日）：《半年净利520亿稳坐“利润王” 恒大获大行看多大涨27%》）（图4） 详细引用上述数字，并强调投行看好、销售强劲等。 证券日报（2018年8月8日）：《恒大或成首家利润千亿元级房企 预告一出公司股价应声大涨逾21%》 同样突出净利润超520亿、核心利润超546亿、净负债率大幅下降。 中国网、中证网、海外网等也发布了类似正面稿件，称恒大稳坐“利润王”、实现高质量发展。 这些报道在2018年8月6日恒大发布盈利预告后集中出现，正值标普此前多次下调评级之后，媒体用业绩数据强化“恒大财务健康”的叙事。 虽然西方评级机构早在2015年就发现出恒大可能有巨大财务风险，但在中共官方媒体保护下，恒大的系统性金额诈骗未能被揭穿，反而越演越烈，给中国经济和中国投资者，购房者造成了更大的损失。
- Sep 23, 20263.0x their median
Jean-André Rixens, French. Painting- The death of Cleopatra. 1874. https://t.co/oOLFtrwS5L
- Oct 2, 20262.4x their median
"Inquisicion" (ca. 1900) By Victor Schivert. 🖌️🌹 Romanian painter. https://t.co/myP7EYdLZC
- Aug 20, 20261.8x their median
群友挖出来的视频，这是恒大 20 周年年会的时候吗？ https://t.co/Qma5GEpJNx
- Sep 29, 2026
Slavery and concubinage (including sexual slavery) were recognized and legally regulated institutions in the traditional history of the Islamic world and classical Sharia jurisprudence for over a millennium. Under classical Islamic jurisprudence, chattel slavery was generally restricted to non-Muslim captives acquired through lawful warfare (jihad) in the dar al-harb (House of War) or their descendants. Free Muslims and protected non-Muslim minorities (dhimmis) living under Islamic rule were legally exempt from enslavement. Islamic law permitted a master to have sexual relations with his female slaves, referred to as ma malakat aymanukum ("that which your right hand possesses"). This was distinct from standard marriage (nikah); female slaves served as domestic laborers or as sexual concubines. Jurisprudence provided certain rights, such as prohibiting the separation of mothers from young children, requiring basic provisions, and encouraging manumission (freeing of slaves) as an act of piety or expiation for sins. An umm walad—a concubine who bore her master a child—could not be sold and was automatically freed upon the master's death. Historical data shows that Arab and Ottoman traders focused heavily on capturing women and girls. Buyers used female slaves for domestic work and sexual concubinage inside harems. Traders castrated many male slaves to create eunuchs. Masters viewed castrated guards and soldiers as more reliable and unable to reproduce. Beginning in the 9th century and intensifying throughout the Middle Ages, the Muslim slave raids into Europe became a grim and persistent reality. Mediterranean transformed into a battlefield of human plunder as North African corsairs—pirates and slavers sanctioned by the Muslim states of Algiers, Tunis, and Tripoli—turned the coasts of Europe into hunting grounds. From the shores of Italy and Spain to distant villages in Ireland and Iceland, these raids, which reached their peak between the 16th and 18th centuries, terrorized Christendom. Entire communities were swept away into the darkness of captivity. Historical estimates suggest that between one and one-and-a-half million Europeans were enslaved by Muslim raiders during this period, feeding the insatiable slave markets of North Africa. The raids were calculated acts of economic and social devastation. Armed with scimitars and matchlocks, the corsairs descended with terrifying speed, capturing men to row their galleys, women to fill harems, and children to sell in the bustling markets of Algiers or Constantinople. In 1627, a fleet of Barbary ships reached as far as Iceland, abducting 400 villagers in a single night, while closer to home, entire swathes of the Italian and Spanish coasts were depopulated. In 1540, the Corsican town of Bonifacio lost half its population to enslavement. Even great cities like Valencia and Naples lived in fear of these predatory fleets. European captives, bound and beaten, were paraded in North African slave markets, described by horrified Christian travelers as “infernos of human misery.” But Christendom was not idle in the face of these atrocities. Spain, at the forefront of the Reconquista and hardened by centuries of conflict with Islamic forces, took the lead in fighting back. Spanish fleets, bolstered by Catholic alliances, waged relentless campaigns against the corsairs, culminating in decisive victories such as the 1571 Battle of Lepanto, where the Holy League shattered the Ottoman navy. Spain’s coastal fortresses and counter-raids on North African ports became symbols of defiance, and by the 18th century, the balance of power began to shift. Though the scars of these centuries-long raids remained, Europe’s resolve to push back turned the tide, eventually breaking the corsairs’ dominance over the Mediterranean. 📷 : Scene at a slave market by Swiss artist Otto Pilny (1866-1936) painted in 1919. #archaeohistories
- Aug 22, 2026
今天在浙江看到一群学生，举着标语大喊： “结束一党专制，把人民的权利交给人民！ 另一人喊：“以稳定为由拒绝民主， 充分暴露了独裁者的本质！ 谁搞专制独裁， 谁就不得人心，谁就会被人民打倒！” 我心情澎湃又激动，好家伙，立功的时候到了！ 我打电话报警，问清情况后， 女警告诉我：“这是横店在拍民国时期电影！”
- Aug 23, 2026
20260823唐师曾：唐师曾，已于2026年8月23日12:03分，驾鹤西归！ 伟大的战地记者， 永垂不朽！ 新华社记者退休，不是通稿，一个人的自媒体！戦地记者，扶助三农！走哪吃哪，有啥说啥！只到场、没立场！ 戦地记者，亲临现场，光天化日，实证分享！独家深入，诸神附体。35mm不剪裁、一镜到底不剪辑！ https://t.co/mFUISduhuc
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 901 interactions against 195K followers, an engagement rate of 0.461%. Measured over 10 original posts, its engagement rate beats 84% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 45K times each, and 1.98% of those impressions turn into an interaction. That is about 23.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 15:00 UTC, and Friday is the busiest day of the week. Of the 10 posts sampled, 80% carry an image or video and 30% link out. The account's strongest tracked post pulled 13K interactions, about 14x its own typical post.
- What is 楊錦麟's engagement rate on X?
- 楊錦麟 (@m_wo8y) has an engagement rate of 0.461%, based on the median interactions across 10 original posts from the last 30 days against 195,023 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.461%, 楊錦麟 sits above the 50th percentile of the 204,956 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @m_wo8y have real engagement?
- Its engagement rate beats 84% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the top quarter for its size group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @m_wo8y post?
- Most posts go out around 15:00 UTC, and Friday is its busiest day, at roughly 0.73 posts per day across the measured window.