Facebook Fake Engagement Check

Someone flooded your post with comments and you want to know whether they came from real people.

Paste the post URL. You get an evidence-backed answer in about three minutes: which accounts show coordination, which look organic, and which the data cannot judge either way. The first 1,500 comments of every run are analyzed free.

This tool never calls anyone a bot. It shows you the pattern, attaches the evidence, and states plainly what it cannot detect.

How do I know if Facebook comments are fake?

You usually cannot tell by reading them. Coordinated comment campaigns are built to look ordinary one comment at a time. The pattern only appears when you line up when each account posted, how often, and how similar the wording is across supposedly unrelated people.

This tool looks for four things across the whole comment section:

• Timing bursts - clusters of comments arriving in a window far tighter than organic conversation produces.

• Machine-regular cadence - an account posting at intervals so even that the variation is near zero. People are irregular; schedulers are not.

• Duplicate phrasing across accounts - the same distinctive phrases appearing from accounts with no other connection to each other.

• Reply chains - accounts that consistently amplify one another.

Every finding carries its evidence: the timestamps, the intervals, the shared phrases.

What does the answer look like?

Each account in the comment section gets one verdict:

• MULTIPLE SIGNALS - more than one independent pattern points the same way.

• STRONG / WEAK PATTERNS - one pattern, graded by how far it sits from normal.

• NO SIGNALS OBSERVED - nothing anomalous in this data.

• INSUFFICIENT SIGNAL - not enough activity to judge. This is a real answer, not a failure. An account with two comments cannot be assessed, and this tool will not pretend otherwise.

Plus a summary: accounts seen, what share of the comments came from flagged accounts, and the coverage - how much of the data could actually be read.

What this cannot detect

Stated plainly, because the limits matter as much as the findings:

• Professionally run personas. Someone paid to post from a real, aged account with genuine history is indistinguishable from a real customer in engagement data. Any tool claiming otherwise is not being honest with you.

• Motive. Coordination is a pattern, not a confession. Employees, fans and volunteers coordinate too.

• Anything outside the comments. Views, shares and reach are aggregate numbers with no per-event data attached; nobody can audit them from the outside.

Signals describe behaviour in a dataset. They do not describe people.

What you paste in

One or more Facebook post URLs - permalinks, /posts/ links, story.php links, reel and video permalinks. Page links, /watch links and share wrappers are rejected individually with the reason stated, never silently dropped. Duplicate post URLs are deduplicated before anything runs, so you never pay to scrape the same post twice.

Leave the input empty to run the free demo: a synthetic comment section with a planted coordination burst, one account the tool must refuse to judge, and one row it cannot read at all. No scraper is invoked, nothing is charged, and it finishes in about seven seconds.

What it costs

Two lines, on every run:

• scrape: N comments via apify/facebook-comments-scraper - billed to you by that scraper (roughly $2.00-2.50 per 1,000 comments at its published rates).

• analysis: M unique comments, first 1,500 free - the rest at $0.66 per 1,000 unique comments, platform compute included.

This tool conducts the scraper; it does not resell it. Its fee goes to it, ours goes to us, and the receipt shows both. If the scraper fails on some posts, those posts are named in the summary as its failures. If it fails entirely, the run refuses cleanly and we charge nothing.

Permissions, stated plainly

This actor runs with full permissions because it must start the comments scraper in your own account and read the resulting dataset. It reads nothing else. The data stays in your account; we retain nothing after the run.

For AI agents

One call replaces a multi-step pipeline: URL validation, scraper orchestration, field mapping, analysis, report. Inputs and outputs are schema-defined. Failures are explicit - a refusal returns status: refused with a reason string and exits cleanly rather than returning an empty success. Coverage is always reported, so a thin answer is distinguishable from a confident one. There is no LLM anywhere in the analysis: identical input produces identical output, every time.

Measured performance

Live, platform-confirmed (24 July 2026): a real 888-comment job - scrape and analysis end to end - completed in 3m11s at the default 256 MB. The free demo completes in about 7 seconds. Engine ceiling (sandbox-measured): 50,000 comments is roughly 34 s of analysis at a peak of about 131 MB, comfortably inside the default memory.