Detect bots, purchased followers, and fake engagement on any Facebook Page — from live growth data, in seconds.
After the audience check
A bought audience wastes a campaign's budget. What a creator has already posted can cost a great deal more, and no follower count will show it to you. A Social Background Check reads their whole history — captions, images, video frame by frame, speech transcribed from the audio, and posts they have already deleted — across 18 risk categories, with the evidence behind every finding.
Facebook fraud is Page-centric. A Page shows two public numbers — likes and followers — and both can be bought in bulk from like-farms, which is why a Page with hundreds of thousands of followers can post to near-silence. The other common pattern is not fraud but decay: audiences built with paid “Page like” campaigns years ago that never came back once the boosting stopped. Either way, the follower count no longer describes a real audience, and the Page’s public follower history is where that shows first.
Every platform has its own fraud signature. These are the three patterns the checker screens for on Facebook.
Like-farms deliver followers in bursts, so the public growth history shows single-day steps with no viral post, press mention, or ad campaign behind them. Organic Page growth is gradual; bought growth arrives in blocks.
Reactions and comments from accounts that never otherwise interact with the Page’s niche — generic one-word comments, tag-spam, and reactions arriving within minutes of posting then stopping dead. The numbers look alive; the conversation is not.
Followers acquired through paid Page-like ads who never returned. The tell is a large follower count paired with flat growth and engagement far below the roughly 0.9% follower-based rate the checker treats as the Facebook norm.
Facebook numbers are one slice of what brands vet. CreatorScore blends 7 agents — authenticity, engagement quality, content risk, sentiment, and more — into the 1–100 trust rating brands check before they sign.
Vetting creators for a brand? See how brands screen influencers at scale
Enter the Page’s username — the part after facebook.com/ in its URL — and pick Facebook. The checker pulls the Page’s public follower history and runs three tests: single-day follower spikes with no event behind them, how choppy day-to-day growth is compared with an organic Page, and engagement relative to the approximate 0.9% Facebook norm where an engagement figure is available. You get an authenticity percentage and the reasoning behind each signal.
Three shapes recur. Bought likes arrive as step-jumps in the growth history with nothing to explain them. Click-farm engagement shows as generic comments and reactions from accounts with no connection to the Page’s topic. And dormant audiences — often left over from old paid like-campaigns — show as a big follower number with flat growth and very little reaction to new posts. None of these is proof on its own; together they are what brands screen for.
Two usual reasons. First, the tool reads public Pages, not personal profiles — a personal profile with a large friend list will not be found. Second, our data source indexes Pages it has encountered before, so a small or very new Page may not be on file yet. Use the exact username from the Page URL (not the display name), and if the Page still is not found, that is a coverage gap, not a verdict on the audience.
Meta removes fake accounts continuously and reports on it in its quarterly Community Standards Enforcement Reports, and purchased likes violate Facebook’s terms. In practice removals are gradual and incomplete — a Page that bought followers often shows follower drops weeks later, which is a second tell the growth-variance signal picks up. Relying on the platform to clean a bought audience is slow; stopping the source and rebuilding organically is faster.
It reads the Page’s public follower history from a third-party analytics index and scores three signals — spike anomaly, growth variance, and engagement versus the platform norm — into an authenticity percentage. It is honest about gaps: Facebook rarely exposes an engagement series, so that signal will often read “no engagement rate available” rather than guess. It does not read individual followers, comments, or ad spend, so it is a screening tool, not an audit of every account that follows the Page.