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TRADER MEI engagement report

@ShimizuMei_ - 63K followers on X

Measured over 30 original posts from a 30-day window, last computed on September 25, 2026.

Engagement

Middle of its size range
Per follower
0.419%
of 63K followers
Per impression
2.55%
10K views on a typical post
Reach
16.4%
of its followers see a post
Typical post
265
interactions (median)
Saved
0.01%
1 bookmarks on a typical post
Posting rate
1.93/day
active 80% of days
Peak time
08:00 UTC
Friday

A typical post picks up 265 interactions against 63K followers, an engagement rate of 0.419%. Measured over 30 original posts, its engagement rate beats 72% of 20,445 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 10K times each, and 2.55% of those impressions turn into an interaction. That is about 16.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 08:00 UTC, and Friday is the busiest day of the week. Of the 30 posts sampled, 50% carry an image or video and 13% link out. The account's strongest tracked post pulled 872 interactions, about 3.3x its own typical post.

Measured over 30 original posts from a 30-day window, last computed on September 25, 2026.

Compared with accounts its own size

TRADER MEI's engagement rate beats 72% of the tracked X accounts closest to it in follower count (20,445 accounts, accounts of similar size (decile 5 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 66% 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 0.419%, TRADER MEI sits above the 50th percentile of the 205,676 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.679%.

p100.004%
p250.024%
p50 (median)0.143%
p750.679%
p902.56%
p9982.4%
Engagement rate as a share of followers, across the 205,676 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,897 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.679%
90th percentile2.56%
99th percentile82.4%

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 08:00 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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Friday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Friday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video50% of posts+111%+108% to +115%34K
Outbound link13% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 50% 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.
  • 13% 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 1149 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 22, 20263.3x their median

    The USD.infra Vault Is Now Open 🔓 The Internet runs on digital infrastructure. Now with DAWN, that infrastructure is financeable on-chain. Introducing the USD.infra Vault: A new way to finance digital infrastructure powering AI compute and connectivity. https://t.co/IeLTwDmK07

    5781071068196K viewsView on X
  • Sep 17, 20261.6x their median

    Shielded $ZEC holders: Q3 retroactive grant polling is live through Sep 29, 20:00 UTC. Update before you vote: • @zodl_app 3.14.0+ (needed for the 37-question ballot) • @vizorwallet latest • Zkool latest Each proposal is a separate yes/no. Quorum is ~420k ZEC. https://t.co/9JRQpu6doL

    3153557831K viewsView on X
  • Sep 25, 2026

    Everyone is watching @solana for TPS, memes and token launches. But the more interesting story might be what is happening underneath. Solana’s stablecoin volume has now crossed $5T this year, while tokenized real-world assets on the network have passed $4.5B. And the @Solana Foundation is bringing in veterans from Binance and Polygon to push institutional adoption and payments. That changes the conversation. The question isn’t: “Can Solana handle more transactions?” It’s: “Can @solana become one of the places where actual financial transactions settle?” Because if stablecoins, tokenized equities and RWAs keep moving onchain, blockspace stops being just infrastructure for crypto traders. It becomes financial infrastructure. And that’s a much bigger market to fight for.

    2151154014K viewsView on X
  • Sep 11, 2026

    Devs don’t need another person calling their project “the next big thing.” They need someone who actually takes time to understand what they built. I’ve seen projects with really good technology struggle simply because people don’t understand what the product does or why they should care. A developer can spend months building something useful, fixing bugs, improving the product and solving problems most people will never see. Then the timeline reduces it to: “wen token?” “wen airdrop?” “bullish.” That’s the PROBLEM. A good product deserves more than empty hype. Someone has to take the time to understand the product, break down the complicated parts, point out what actually makes it different, and explain it in a way that both crypto people and normal users can understand. That’s the kind of Web3 work I enjoy. Not blindly shilling a project without due research. Understanding what was built, finding the story inside it, and making people care about it,then see how people jump on that project.

    217113506.5K viewsView on X
  • Sep 16, 2026

    Airdrop hunting is becoming a full time job, but the real question is: are you farming opportunities or just farming disappointment? Every week, a new protocol launches with points, quests, and promises of future rewards. You bridge, swap, provide liquidity, and keep showing up, hoping your wallet makes the list. But here’s the uncomfortable part: points are not tokens, and tokens are not guaranteed money. Some protocols have real products and transparent reward systems. Others have nothing more than a well designed campaign and a community full of hopeful farmers. If I’m farming an airdrop, I want to know three things: Does the protocol solve a real problem? Is there a clear reason to believe users will be rewarded? Am I using the product because it’s useful, or just chasing a promise? The goal shouldn’t be to farm everything. It should be to find opportunities worth your time. Which airdrop are you farming right now, and what makes you believe it’ll be worth it?

    2102133011K viewsView on X
  • Sep 20, 2026

    3 tokens that remind me why crypto is such a crazy market. @pnutsolana , @CHILLGUY and @bonk_inu. Before the market went crazy for them, they weren’t exactly the coins dominating everyone’s timeline. Then something changed. @PNUT caught fire after the Peanut the Squirrel controversy went viral. Elon Musk’s commentary helped push the story into the spotlight, and the token eventually crossed a $2B market cap. @CHILLGUY was already a token, but the meme behind it exploded across TikTok and X. In roughly 48 hours, its market cap reportedly went from around $10M to nearly $500M. Then there’s @bonk_inu. It launched during Solana’s darkest days after FTX collapsed. Instead of chasing complicated narratives, it gave half its supply to Solana’s NFT communities, traders, artists and developers. The result? A reported 3,649% surge from launch to its early January 2023 peak. Different tokens. Different catalysts. Same lesson: The market doesn’t always reward the product people talk about the most. Sometimes, it rewards the product that suddenly finds its audience. Devs, here’s my advice: Stop launching tokens and immediately asking for a pump. Build a product people can actually use. Create a reason for people to talk about you. Make your token distribution transparent. And most importantly, give the market a reason to care beyond your next announcement. Because hype can bring people in. But only genuine demand gives them a reason to stay. Which token caught you off guard the most?

    2091125012K viewsView on X
  • Sep 19, 2026

    Crypto traders are funny. When the market is pumping, everybody is a genius. When the market is bleeding, everybody suddenly becomes a long term investor. Bitcoin just pushed back above $80K despite a Fed rate hike and the CLARITY Act setback. But here’s the question nobody wants to ask: How much of this move is real demand, and how much is traders rushing to buy because they think the bottom is in? A green candle is not proof of a healthy market. Volume, liquidity, open interest, and who is actually buying matter more than the color on your chart. The market can look bullish while quietly setting the stage for another shakeout. Are we in a genuine recovery, or are traders just getting comfortable again? What’s your take?

    203312904.9K viewsView on X
  • Sep 10, 2026

    You don’t need to find a 100x coin to make money here. There are actually different ways money moves around this space, and understanding where it comes from is more important than knowing the name of 100 different tokens. Trading is the obvious one. You buy something because you believe it will be worth more later, then sell when your thesis plays out. Simple in theory. Hard in reality because timing, liquidity and emotions can turn a good idea into a bad trade. Then there’s arbitrage. Maybe ETH is $3,000 on one venue and $3,015 somewhere else. If you can buy at the cheaper price and sell at the higher price, that $15 difference is the opportunity. But you still have to subtract fees, slippage, gas and the time it takes to execute. That $15 can easily become $2. That is the part X usually doesn’t show you. Then you have liquidity providing. You put capital into a pool and other people trade against that liquidity. You earn a share of the fees. Sounds passive. It isn’t. If the asset you’re providing moves heavily in one direction, impermanent loss can eat into those fees. Then there are airdrops and points. You use protocols early, provide liquidity, trade, bridge, lend or simply become an active user. Sometimes the protocol later rewards that activity. But don’t confuse activity with profit. Spending $500 in fees to farm a $100 airdrop isn’t an opportunity. It’s an expensive hobby. And there are newer games too. On-chain data. Liquidations. MEV. Funding rates. Token launches. Referral programs. Early protocol incentives. The deeper you go, the more you realise something: Web3 doesn’t magically create money. Someone is paying somewhere. A trader pays the spread. A borrower pays interest. A protocol pays incentives to attract liquidity. A project pays users to create activity. A liquidity provider earns fees from traders. An arbitrageur earns from price differences. Once you understand that, you stop asking: “What coin should I buy?” You start asking: “Where is the value being created, and what skill do I have that lets me capture a small part of it?” That question will take you much further than chasing the next 100x. WAGMI

    191213406.2K viewsView on X
  • Sep 22, 2026

    $750M just landed on @solana . @tether minted $500M USDT. @circle added another $250M USDC. And I don’t think the interesting part is the number itself. The interesting part is why this liquidity needs @Solana. Stablecoins are slowly becoming the boring infrastructure behind crypto. You don’t need to believe SOL is going to $500 to understand the thesis. Traders need dollar liquidity. DeFi needs dollar liquidity. Tokenized stocks need dollar liquidity. Payments need dollar liquidity. And Solana is positioning itself as one of the places where that liquidity can move quickly and cheaply. The network already has more than $11.5B in USDT + USDC circulating, while daily stablecoin active addresses hit 888K this month. But here’s the part I’m focused on: Does more stablecoin supply actually create more economic activity, or are we just moving dollars around the casino faster? Because $750M of fresh liquidity sounds bullish. What happens AFTER the mint is what matters. If that liquidity starts flowing into payments, lending, RWAs, trading and real users… that’s a much bigger story than another crypto pump. @solana doesn’t just need more stablecoins. It needs those stablecoins to do something.

    180114403.9K viewsView on X
  • Sep 23, 2026

    One of the most expensive mistakes in trading isn’t a bad entry. It’s the trade you take after a bad trade. You lose a position. Then your brain starts negotiating: “Let me just make back what I lost.” So you enter another setup you probably wouldn’t have touched an hour ago. It loses too. Now you increase the size. You’re no longer trading the market. You’re trading against your emotions. This is why a loss should have a stopping point, not just a stop-loss. If you lose 2–3 trades in a row, step away. Not because the market suddenly became impossible to trade. Because your decision making can change without you noticing. A simple rule I’ve found useful: Never increase your risk just because you’re trying to recover a previous loss. Your next trade has no responsibility for your last one. The market doesn’t know you lost money. It doesn’t owe you a comeback. And honestly, sometimes the best trade after a loss is no trade at all. Be honest: What usually gets you after a losing trade? Is it revenge trading, overtrading, or trying to win it back immediately? 👇

    189113107.1K viewsView on X

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 265 interactions against 63K followers, an engagement rate of 0.419%. Measured over 30 original posts, its engagement rate beats 72% of 20,445 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 10K times each, and 2.55% of those impressions turn into an interaction. That is about 16.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 08:00 UTC, and Friday is the busiest day of the week. Of the 30 posts sampled, 50% carry an image or video and 13% link out. The account's strongest tracked post pulled 872 interactions, about 3.3x its own typical post.

What is TRADER MEI's engagement rate on X?
TRADER MEI (@ShimizuMei_) has an engagement rate of 0.419%, based on the median interactions across 30 original posts from the last 30 days against 63,190 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.419%, TRADER MEI sits above the 50th percentile of the 205,676 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 @ShimizuMei_ have real engagement?
Its engagement rate beats 72% of the tracked X accounts closest to it in follower count (20,445 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 @ShimizuMei_ post?
Most posts go out around 08:00 UTC, and Friday is its busiest day, at roughly 1.93 posts per day across the measured window.

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