1. Collect
Public profile metadata and recent posts/replies from supported platforms (X, Bluesky).
Methodology
How BotShark works
A transparent pipeline: collect public data, extract behavioural features, score against published rules, and explain every flag with evidence.
- 01Collect
- 02Extract
- 03Score
- 04Explain
2. Extract
Behavioural features: posting rhythm, engagement asymmetry, content reuse, thread shape.
3. Score
Rule engine combines signals into a 0–100 likelihood score with tier and confidence.
4. Explain
Each flag shows the underlying posts, metrics, and rule rationale in plain language.
Sample report
What a finished analysis looks like
Same report surface as a live scan — score, findings, charts, and plain-language evidence. Synthetic data; try a real handle with a free scan.
Full sample reportSynthetic demo data
BotShark reportScraped 15 Jun 2026, 14:30 UTC
@coordination_watch
Retweet amplifier
Almost nothing they post is original — the account mainly exists to boost other people's content. That's the classic shape of a narrative spreader or political spam network.
Also resembles: Reply farm, 24/7 poster, Grift / promo account
100/ 100
Very high likelihood95% confident (95% of the data we wanted was available).Deep thread pass
We found 40 warning signs, and they fit together: this account posts and engages like a broadcast or farm operation, not someone casually scrolling and tweeting.
The posting habits, the way they engage, and the kind of content they share all tell the same story — this doesn't read like someone using the app for themselves.
Profile snapshot
Coordination Watch
“Breaking narratives | alpha drops | DM for promo rates https://t.co/grift”
Bio reads like a promo funnel
Network & coordination
Very few follow-backs from who they follow
Worth notingLow reciprocity means the follow graph isn't mutual social life — often follow-spam or purchased networks.
Top signals · 8 of 46
The strongest of the 46 signals below.
Posts around the clock with no normal break
Major red flagActive in 22 different hours over the last week with no 4-hour quiet stretch — and the pattern doesn't sit cleanly in any one timezone. That's what we'd expect from automation or someone posting without a real day/night rhythm.
Almost everything is retweets and quotes
Major red flagOnly about 5% of what we sampled is original. That's the shape of an amplifier — little personal voice, mostly boosting other people's posts.
This is the way. Everyone needs to see this. #crypto #alpha This is the way. Everyone needs to see this. #crypto #alphaView post →
Don't sleep on this opportunity #cryptoView post →
Bio smells like a grift or promo funnel
Major red flagThe bio has money-making keywords or dodgy short links — the kind of setup scammers and promo bots use to look legit.
Some replies don't match what they're replying to
Major red flagAbout 60% of replies we could check looked off-topic — common with auto-reply tools and spam bots.
They replied
So true!!
To this post
Our peer-reviewed paper on Arctic ice loss is out — full methodology in the thread.View reply →
They replied
Great post
To this post
City council voted 7–2 to expand the library budget for after-school programs.View reply →
Replies out constantly, gets almost nothing back
Major red flagOne-way megaphones — lots of outbound, almost no inbound — are a hallmark of engagement farms, not social use.
So true!!View post →
Great postView post →
Same spammy templates over and over
Major red flagRepeating spam templates is how low-effort farms scale. Real marketers still vary the pitch.
Facts. Share this everywhere.View post →
Facts. Share this everywhere.View post →
Created after the platform changed hands
Major red flagAccounts created after the platform changed hands arrived in a wave of inauthentic sign-ups. Timing alone is weak — stronger when other flags stack.
Follows many, followed by few
Major red flagAggressive follow-spamming with almost no follow-back is a growth-hack pattern, not mutual discovery.
Engagement is mostly one-way broadcasting
They push content and replies outward far more than they ever come back to conversations on their own posts — more megaphone than participant.
So true!!View post →
Great postView post →
Follower numbers look lopsided
50 followers and 2,500 following. They follow huge numbers of people while far fewer follow back — a common growth-hack pattern.
Posting rhythm
Real people cluster in waking hours. A flat skyline with no quiet stretch often means automation or shift workers running the account.
Quiet for weeks, then a sudden flood, often means the account was switched on for a campaign — not someone casually checking in more.
How they spend posts
Normal users mix originals and replies. Feeds that are almost only replies or reposts often exist to amplify someone else's message.
What they post about
We bucket posts by the words they use most. A feed glued to crypto, promo, or bait language looks different from mixed everyday interests.
Sentiment spread
Real people swing between moods. Feeds stuck at one emotional extreme often exist to provoke, sell, or push a single narrative.
All signals · 39
Full list — items already shown above are collapsed.
Heavy posting over the last month
Major red flagA month of heavy output is a stronger tell than a busy day — real lives rarely sustain that pace without help.
Very new account, huge posting history already
Major red flagFresh accounts usually start quiet. Huge history this early often means scripts, purchased history, or a recycled farm handle.
Posts far more than a normal person would
Worth notingPeople sleep, work, and take breaks. Day-after-day volume at this level is hard to sustain by hand — automation or a farm shift is the usual explanation.
Gaps between posts are oddly regular
Worth notingNatural posting is messy. Near-metronome gaps are a classic timer or scheduler signature.
Hardly anyone replies on their posts
Worth notingGenuine accounts usually get some replies back. Near-zero inbound suggests nobody is treating this as a real person.
So true!!View post →
Great postView post →
Lots of generic one-liner replies
Worth notingEmpty praise ('great post', 'so true') is cheap to template. Lots of it usually means engagement farming, not a point of view.
So true!!View post →
Great postView post →
Sustained heavy posting for months
Worth notingThree months of sustained firehose activity is rarely casual use; it usually needs tooling or a team.
Lots of obvious engagement bait
Worth notingEngagement bait exists to farm likes and replies. Heavy use is a growth tactic, not conversation.
↑ Already covered above — Replies out constantly, gets almost nothing back
↑ Already covered above — Content matches crypto or affiliate spam patterns
↑ Already covered above — Some replies don't match what they're replying to
↑ Already covered above — Shows up to post at almost all hours
↑ Already covered above — No normal overnight break in posting
↑ Already covered above — Follows many, followed by few
↑ Already covered above — Same spammy templates over and over
↑ Already covered above — Bio reads like a promo or scam
↑ Already covered above — Almost nothing is original — mostly retweets
↑ Already covered above — Multiple off-topic or copy-pasted replies
↑ Already covered above — Some days were nothing but retweets
Account history
↑ Already covered above — Created after the platform changed hands
What looks normal
Too few accounts scanned to spot coordination
Only 0 tweets stored locally. The more profiles you run, the better copy-paste detection gets.
First scan — no growth history yet
We haven't tracked this account before. Run it again in a week or two to see if followers spike unnaturally.
Key numbers
Followers
50
Following
2,500
Total tweets (profile count)
12,840
Average posts per day (lifetime)
35
Posts per day (last week)
45
Replies they sent to others
80
Replies others left on their posts
2
Outbound vs inbound replies
40
Posts that are their own words
5%
Engagement per follower
0%
What this analysis can't tell you
- Sample data for demonstration only — not a live scrape.
- First time we've stored this account — run it again in a week to see whether followers jumped unnaturally.
- Copy-paste detection only compares accounts you've already scanned on this install.
- We couldn't pin down posting hours — common when someone posts around the clock.
Prefer a dedicated page? Open the full sample report →
BotShark is not a black box. Every report is built from observable public behaviour — posting cadence, who an account engages with, how replies cluster, whether phrasing repeats across threads, and whether activity fits human sleep/wake patterns.
We deliberately separate the score from a verdict. A high tier means multiple independent signals align with automation or coordination heuristics — not that an account is guilty of anything. You get the evidence; you decide what it means in context.
Deep mode optionally expands thread analysis for reply-network sampling. Follower audits sample public follower cohorts for creation-cluster and coordination cues. Both modes show their work in the report.
Scoring thresholds are not guesses. We test them against a labelled set of known bot and human accounts, measure precision and recall at each score cutoff, and revise the rules when the data says a threshold is wrong — the same discipline you would expect from a published research method, not a vendor black box.
That evaluation runs continuously as the rule set changes. Current methodology and calibration results are published on the methodology page.