勃勃OC engagement report
@bboczeng - 227K followers on X
Measured over 62 original posts from a 30-day window, last computed on October 2, 2026.
Engagement
A typical post picks up 73 interactions against 227K followers, an engagement rate of 0.033%. Measured over 62 original posts, its engagement rate beats 39% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 15K times each, and 0.492% of those impressions turn into an interaction. That is about 6.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.3 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 00:00 UTC, and Thursday is the busiest day of the week. Of the 62 posts sampled, 37% carry an image or video and 10% are part of a thread. The account's strongest tracked post pulled 3.6K interactions, about 49x its own typical post. Recurring topics include #外国人雇用, #行情.
Measured over 62 original posts from a 30-day window, last computed on October 2, 2026. Recurring tags: #外国人雇用, #行情.
Compared with accounts its own size
勃勃OC's engagement rate beats 39% of the tracked X accounts closest to it in follower count (21,185 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 26% 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 0.033%, 勃勃OC sits above the 25th percentile of the 212,825 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.697% |
| 90th percentile | 2.61% |
| 99th percentile | 83.0% |
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 00:00 UTC, and Thursday 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 | 37% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 5% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | -3% | -3% to -2% | 54K |
- 37% 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.
- 5% 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 160 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 3% below 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 10, 202649x their median
BREAKING🚨: U.S. home sellers outnumber buyers by 563,000, a record 58% gap. https://t.co/QdqUXwu5zG
- Sep 10, 202620x their median
BREAKING 🚨: Treasury Bonds $TLT has now collapsed to its lowest price since May 13, 2004 📉 📉 https://t.co/adqFs8IDoI
- Oct 1, 202617x their median
查理·芒格当时31岁。他离婚了,身无分文,眼睁睁看着自己9岁的儿子死于白血病。他于99岁去世时,身家26亿美元。 1953年,他29岁时经历了离婚。他的妻子得到了房子和他拥有的几乎所有东西。他搬进一个房间,开着一辆破旧的黄色庞蒂亚克车。有人问他为什么还开这辆车,他说这是为了阻止那些拜金女。 他当时在洛杉矶的Wright & Garrett律师事务所做律师,每月收入275美元。然后,他的儿子泰迪被诊断出患有白血病。没有治疗方法。存活率几乎为零。芒格没有医疗保险。 他的朋友里克·盖林说,芒格会去医院,抱着儿子待一会儿,然后在帕萨迪纳的街头走着哭泣。 泰迪于1955年去世。芒格当时31岁。 他从未让这件事摧毁自己。他说,嫉妒、怨恨、报复和自怜是灾难性的思维模式。自怜几乎接近偏执狂。他说,每当你觉得某种境况或某个人毁了你的生活时,其实是你自己在毁自己的生活。 他重建了一切。他做了一些房地产交易,赚了140万美元。他创办了一个投资合伙企业,13年来每年回报率达19.8%。他于1978年成为伯克希尔·哈撒韦的副主席。 他对年轻人的建议是三条规则。不要卖任何你自己不会买的东西。不要为任何你不尊重和钦佩的人工作。只与你喜欢的人一起工作。 还有一句话将一切串联起来。获得你想要东西的最安全方式,就是努力让自己配得上你想要的东西。 他捐赠了如此多的伯克希尔股份,以至于他的财富本可以超过100亿美元。他留下了26亿美元。他不需要其余的。 这个31岁时在街头哭泣的男人,用接下来的68年证明了这样一个道理:你无法克服悲剧。你只能熬过它。
- Sep 10, 202616x their median
川普总统在德州大会演讲时承诺,如果共和党同时赢得众议院和参议院,鉴于美国取得的巨大经济成功,他将向每一位成年美国公民发放5000美元的“川普分红”。左媒马上一窝蜂说,川普要向每个美国成年人发红包,说有2.7亿成年人,要发放1.35万亿美元。这是偷换概念,川普说的是“美国公民”,不是每个美国人。 美国现有约2.45亿成年美国公民,每人发5000美元,约$1.225万亿。 这笔庞大资金从哪里来?一是关税收入(去年美国关税收入是3000亿美元);发行国债;削减联邦政府开支;经济增长带来的新增税收。万斯副总统说,富裕人士可能不包括在5000美元红包计划之列。总之可能是多种方式组合。 川普总统说,美利坚合众国就像一个大公司,每一个美国公民都是股东。美国取得巨大经济收益,要给每一个股东分红。 川普讲这番话时,坐在台下的财政部长贝森特鼓掌,说明他对这笔庞大资金来源胸有成竹。
- Sep 10, 202614x their median
CPI comes in cooler than expect The Iran War ends $SPY rallies A bald eagle screeches And thus concludes my prediction for 9/11
- Oct 1, 202612x their median
Broadcom $AVGO has agreed to provide Anthropic with up to $42B in financing tied to its AI infrastructure buildout. The facility could cover roughly one-third of Anthropic’s $125.2B five-year TPU compute commitment, and the debt may be convertible into Anthropic shares. Anthropic is also expected to become Broadcom’s largest compute customer in 2027. The filing says Broadcom’s combined role as hardware supplier and financing partner creates potential conflicts around pricing and access to compute. Source: Anthropic’s IPO prospectus seen by Reuters
- Oct 1, 20267.2x their median
"Here We Go Again": Fed's "Original Sin" Means 10Y Yields Are Going To 8%, TS Lombard Warns https://t.co/sqAqBuydWt
- Sep 10, 20265.7x their median
Sometimes maybe good, sometimes maybe shit https://t.co/s7Rmw6vAvV
- Sep 11, 20265.2x their median
一个冷知识: 在币圈赚到2000万,就可以彻底躺平了。 每天在ATM上取1000块,花光这1000,第二天继续取1000,这辈子都取不完,而且卡里的钱一直在复利,越花越多,想想都烦死了! https://t.co/fUMhmvtgrI
- Sep 11, 20265.0x their median
I want to be the greatest trader of all time Might be insane I’m still going for it https://t.co/8Xw7PF55Bb
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 73 interactions against 227K followers, an engagement rate of 0.033%. Measured over 62 original posts, its engagement rate beats 39% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 15K times each, and 0.492% of those impressions turn into an interaction. That is about 6.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.3 posts a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 00:00 UTC, and Thursday is the busiest day of the week. Of the 62 posts sampled, 37% carry an image or video and 10% are part of a thread. The account's strongest tracked post pulled 3.6K interactions, about 49x its own typical post. Recurring topics include #外国人雇用, #行情.
- What is 勃勃OC's engagement rate on X?
- 勃勃OC (@bboczeng) has an engagement rate of 0.033%, based on the median interactions across 62 original posts from the last 30 days against 226,587 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.033%, 勃勃OC sits above the 25th percentile of the 212,825 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 @bboczeng have real engagement?
- Its engagement rate beats 39% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range 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 @bboczeng post?
- Most posts go out around 00:00 UTC, and Thursday is its busiest day, at roughly 4.33 posts per day across the measured window.