Shawn engagement report
@ShawnCT_ - 316K followers on X
Measured over 21 original posts from a 30-day window, last computed on September 4, 2026.
Engagement
A typical post picks up 139 interactions against 316K followers, an engagement rate of 0.044%. Measured over 21 original posts, its engagement rate beats 47% of 6,874 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 52K times each, and 0.266% of those impressions turn into an interaction. That is about 16.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.2 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 07:00 UTC, and Wednesday is the busiest day of the week. Of the 21 posts sampled, 100% carry an image or video and 14% link out. The account's strongest tracked post pulled 1.3K interactions, about 9.2x its own typical post.
Measured over 21 original posts from a 30-day window, last computed on September 4, 2026.
Compared with accounts its own size
Shawn's engagement rate beats 47% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 7 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 18% 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 0.044%, Shawn sits above the 25th percentile of the 66,128 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.016% |
| 50th percentile | 0.1% |
| 75th percentile | 0.499% |
| 90th percentile | 2.09% |
| 99th percentile | 119.9% |
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 07:00 UTC, and Wednesday 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 | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 14% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 100% 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.
- 14% 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 456 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
- Jan 31, 20269.2x their median
$BTC is about to crash another 66% to $28k and wipe out all longs. Every cycle ends the same: • 2017: $19k peak → -84% • 2021: $69k peak → -78% • 2025: $126k peak → -77% Big cycle says the top is in. Liquidation comes next. #BTC #Bitcoin #Crypto https://t.co/UFWvwcG0Kh
- Sep 3, 2026
Two simple steps to check whether an RH Meme pool is actually using an official U.S. Stock Token. Take the trending $JINQIAN and leading $AI as examples: 1. Open @dexscreener, find the pool, and copy the CA of the paired U.S. Stock Token. 2. Go directly to Robinhood’s official explorer to verify it. Paste the Stock Token CA from Dexscreener into the search bar. Direct link:https://t.co/66G0XKuHU3 Results: -Found, and the name includes “• Robinhood Token” = Real -Not found, or no official suffix = Fake Don’t get fooled by claims that a Meme pool is “backed by U.S. stocks.”
- Sep 4, 2026
Looking back at $JINQIAN, I found a new playbook that could completely change how Stock Memes work. Traditionally, the stock gets hot first, then the Meme rides the narrative. But $JINQIAN flipped the script. After $JINQIAN exploded, the Nasdaq microcap tied closely to its narrative, $FAMI, suddenly caught massive attention. FAMI jumped from around $0.12 to $0.50, while trading volume exploded from roughly 5.76M shares to 867M. This could create a very interesting loop: The Meme generates massive Crypto attention and brings it to a tiny public stock. Once the stock starts pumping, that move feeds straight back into the Meme narrative. That’s why FAMI is much more interesting for this model than NVDA. A Meme is unlikely to move a trillion-dollar company like NVDA. But what if a $50M–$100M Meme is tied to a Nasdaq company worth only a few million dollars? And if this model eventually combines with official Robinhood Stock Tokens + Nasdaq microcaps, things could get even crazier. Stocks used to create Memes. Now Memes might start creating stock rallies.
- Sep 2, 2026
This scam playbook, commonly seen on Solana, is starting to show up on Robinhood Chain. Be careful with new tokens that pump like crazy overnight. They can dump just as fast, and a lot of traders are already getting burned I’d suggest sticking with established Memes that have real communities, strong narratives, and solid momentum. The upside can be much better than chasing every new launch.
- Aug 28, 2026
BREAKING: “TRUMP INSIDER” JUST OPENED AN $18.6M bitcoin:native SHORT HE SHORTED 233.6 BTC AT $80,999 WITH 40X LEVERAGE LIQUIDATION PRICE: $83,465 HE OPENED THE POSITION AHEAD OF FED CHAIR KEVIN WARSH’S SPEECH HE MIGHT KNOW SOMETHING https://t.co/vbspTWp6WV
- Sep 1, 2026
Want to find the next 100x Meme? Scrolling X all day probably isn’t enough. A better approach is to find consistently profitable traders and Smart Money wallets, then see what they’re buying before everyone else notices. Here are the Meme tools I use: 1. Find Smart Money: @fomo / @gmgnai / @nansen_ai FOMO lets you track top PnL traders, leaderboards, and the Memes they’re holding. GMGN is great for finding early buyers, profitable wallets, and recent trades. Nansen is better for tracking Smart Money and capital flows across multiple chains. 2. Research Wallets: @arkham / @DeBankDeFi Once you find a strong wallet, dig into its funding sources, connected addresses, holdings, and trading history. One winning trade could be luck. Consistent winners are the ones worth tracking. 3. Real-Time Monitoring: @CieloFinance Add your best wallets to a watchlist and get alerts whenever they buy something new. Instead of checking wallets manually every day, the trades come to you. 4. Check Token Distribution: @bubblemaps A must before buying Memes. Check holder concentration, connected wallets, and wallet clusters to avoid tokens controlled by a small group of insiders. 5. Check Market Data: @dexscreener / @birdeye_so Finally, check volume, liquidity, price action, and trading activity to see whether real money is actually flowing in. You can also use @Debot_Official/ GMGN Bot for onchain scanning and additional early signals. The whole strategy is simple: Find past winners → Find their wallets → Filter out bots → See what they’re buying → Look for Memes appearing across multiple Smart Money wallets → Check distribution and liquidity. One Smart Money wallet buying a Meme could be luck. But when several consistently profitable wallets start buying the same Meme, that’s when it deserves your attention. Any other underrated Meme tools worth using?
- Aug 31, 2026
let’s make a bold guess: could they have a behind-the-scenes deal with FOMO? they get followers, while fomo gets users https://t.co/CbQYjC1Pvj
- Aug 13, 2026
Genuinely impressed by Grok 4.6 Test it with different prompts. Put it next to other models. The results keep coming out strong. And this was just one simple prompt: Create a 3d Queen Anne's Revenge shipusing three.js in white themebackground so ship is properly visible https://t.co/OMhhUqbAMU
- Aug 28, 2026
You only need to miss 10 days to ruin your entire year in crypto. Tom Lee explained in a recent interview why trying to perfectly time the crypto market can be a huge mistake. If you’re always waiting for the perfect bottom and trying to catch only the middle of the move, you could end up missing most of the upside. Over the past decade, most of Bitcoin’s annual gains have been concentrated in its 10 best trading days. Miss those 10 days, and your overall return can turn negative.
- Aug 31, 2026
BTC may be facing an underrated short-term bearish catalyst. Part of BTC’s recent rally was driven by markets front-running a more dovish Fed. The bet was that mounting debt pressure would eventually force the Fed to cut rates faster and bring liquidity back. But that expectation is now being repriced. The Fed’s message remains clear: no rush to cut rates, and no easy compromise because of debt pressure. The longer rates stay high, the more attractive the dollar and Treasuries become, pulling liquidity away from speculative assets. Capital that front-ran monetary easing may now face profit-taking, stop-losses, and a broader repricing. This could become an important catalyst for BTC’s next pullback.
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.
Buy or sell X accounts - escrow-protected
PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 139 interactions against 316K followers, an engagement rate of 0.044%. Measured over 21 original posts, its engagement rate beats 47% of 6,874 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 52K times each, and 0.266% of those impressions turn into an interaction. That is about 16.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.2 post a day over the last 30 days, with activity on roughly 60% of days. Most posts go out around 07:00 UTC, and Wednesday is the busiest day of the week. Of the 21 posts sampled, 100% carry an image or video and 14% link out. The account's strongest tracked post pulled 1.3K interactions, about 9.2x its own typical post.
- What is Shawn's engagement rate on X?
- Shawn (@ShawnCT_) has an engagement rate of 0.044%, based on the median interactions across 21 original posts from the last 30 days against 316,494 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.044%, Shawn sits above the 25th percentile of the 66,128 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 @ShawnCT_ have real engagement?
- Its engagement rate beats 47% of the tracked X accounts closest to it in follower count (6,874 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 @ShawnCT_ post?
- Most posts go out around 07:00 UTC, and Wednesday is its busiest day, at roughly 1.23 posts per day across the measured window.