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How Detection Works

The signals behind review-manipulation detection: bursts, throwaway accounts, duplicate text, and the economics of review farms.

What Is a 'Review Drive'? Manipulation Signal Explained — Revdict

Education

What Is a 'Review Drive'? The Manipulation Pattern Where the Customers Are Real

Our scoring model flags a distinct pattern separate from fake or bought reviews: staff prompting real customers, in a compressed burst, to leave five-star reviews naming a specific employee. Here's how it's detected, how often it shows up, and why Google banned the practice in April 2026.

Andrew Keymaster · Aug 31, 2026 · 6 min

The Economics of Review Farms: What Review-Buying Actually Costs — Revdict

Education

The Economics of Review Farms: What Review-Buying Actually Costs

Fake five-star reviews sell for as little as $9 each; fake negative reviews aimed at a competitor cost more. Here's what the review-manipulation market actually charges, who profits, and what a business risks under the FTC's $53,088-per-violation rule.

Andrew Keymaster · Aug 8, 2026 · 5 min

Review Bursts: The Clearest Fake-Review Signal, Explained — Revdict

Education

Review Bursts: The Clearest Fake-Review Signal, Explained

A review burst is a sudden spike of five-star reviews arriving far faster than a business's normal pace — and it's the single strongest signal in our fake-review model. Here's what counts as a burst, why timing matters more than content, and what real burst patterns look like in our data.

Andrew Keymaster · Aug 6, 2026 · 6 min

How Our Fake-Review Score Works (and What It Can't Tell You) — Revdict

Education

How Our Fake-Review Score Works (and What It Can't Tell You)

Our 0-100 manipulation score combines review-burst detection, reviewer-account age and activity, duplicate-text matching, and rating-text consistency into a single number. Here's what goes into it, and the real limits of what any automated score can prove.

Andrew Keymaster · Jul 21, 2026 · 6 min