Do Fake-Review Signals Vary by Country? What Our Data Shows

#Do fake-review signals vary by country?

Yes, in the places we've analyzed so far, though the size of that difference depends heavily on how many listings we've scored in a given country. Among the seven countries with at least a dozen completed analyses, average manipulation scores range from 22 in the US and UK up to 43 in Spain, and the share of listings flagged Suspicious or worse runs from 18% to 54%. Outside those seven, several countries with only a handful of analyses show much higher averages still, a signal worth watching rather than a conclusion to draw yet.

#What does the data show for countries with enough places to compare?

As of September 2026, our public catalog holds completed analyses for 659 places, spanning more than 20 countries. Seven of them have at least 12 analyses each, enough to look at without one unusual listing swinging the average:

The US and UK sit closest together, both under a 23-point average and under a quarter of listings flagged. The five other countries in this group cluster higher, roughly 33 to 43 points on average, with flagged shares between a third and just over half.

#Why might scores run higher outside the US and UK?

Two explanations fit the pattern, and only one of them is about fraud. The first is what these listings actually are: our US sample leans heavily on chain and franchise restaurants in a handful of major metro areas, businesses with review volume in the thousands and a corporate reputation team watching the listing. The highest-scoring properties in the smaller-sample countries are a different kind of business entirely, a dental clinic in Wrocław, a gold-buying shop near Heidelberg, a home cleaning service in Toulouse, a pizza truck outside Kraków, the sort of small, single-location operator with a few hundred reviews total and nobody dedicated to managing them.

The second explanation is the one our score is actually built to catch: smaller review counts make a burst easier to produce and easier to see. Twenty coordinated five-star reviews barely move a listing with 8,000 reviews; the same twenty reviews can double a listing's rating if it only had forty to begin with. Clean&Fresh, a home cleaning service in Toulouse, scored 70 (Likely Manipulated) on a base of just over a hundred reviews. Milano Vice Pizza Friedrichshain in Berlin scored 68 (Suspicious) the same way. Neither report claims the business paid for reviews; both show a review-count base small enough that a handful of coordinated posts produces exactly the burst pattern our model is designed to flag.

#What about countries with only a handful of analyses so far?

A few countries show striking numbers on samples too small to generalize from, and we're naming that limit directly rather than dressing up four data points as a trend. Four completed analyses in Romania average a score of 74, with three of the four landing Likely Manipulated, including Kidz Sport in Bucharest at 84 and New Era AFI Cotroceni at 83. Eight analyses in India average 56, among them Walk In Woods at 78, a listing carrying more than 9,000 reviews. Six analyses in Turkey and five in Pakistan both average above 50.

None of these samples are large enough to say fraud is more common in any one of these countries. What they do say is where to point the next batch of analyses: a handful of results this far from the US and UK baseline is a reason to analyze more listings in those markets, not a reason to report a national average from four data points.

#Does this mean reviews are less trustworthy outside the US?

Not as a blanket rule, and the data doesn't support reading it that way. The clearest large-sample comparison, the US against the UK, shows almost no difference: 22.6 versus 22.1, and near-identical flagged shares. What actually correlates with a higher score in this dataset is a business with a smaller review base, whatever country it's in, because a small denominator is what turns a modest burst into a large score swing. A single-location dental clinic or cleaning service anywhere is more vulnerable to this than a chain restaurant with an established review history, regardless of where either happens to operate.

Review fraud itself is not a US or UK phenomenon either way. Tripadvisor's own 2024 fraud numbers, drawn from listings across every country in our table and dozens more, put blocked fraudulent reviews at 2.7 million for the year.¹ A number that size doesn't concentrate in one market; it shows up wherever a listing's review count is thin enough, or its incentive to look good is high enough, to make manipulation worth attempting.

#What should this mean for someone checking a listing abroad?

Check the listing itself rather than leaning on a country-level assumption either way. Submit any public Google Maps listing to our free tool, wherever the business operates, and get the same scored breakdown shown for the properties above, whether it's a Manhattan hotel chain or a single-location shop with two hundred reviews. A small business with a thin review history isn't automatically suspect, but it is worth a second look before you rely on its rating the way you'd rely on one built from ten thousand reviews over a decade.

For scale, the average score across every place in our catalog, every country combined, sits at 27.5 as of September 2026. Nearly every country-level average above lands within about 15 points of that overall figure in either direction; Spain's 42.6 is the widest gap among the seven larger samples, and it's still built on 13 analyses, not thousands. Read the table as a map of where to look closer, not as a ranking of which country's reviews to trust.

#Frequently asked questions

#Are fake reviews more common in some countries than others?

Among the countries we have enough data to compare, the US and UK show similar, lower average scores, while several countries with mid-sized samples (Poland, France, Germany, Canada, Spain) run higher. The difference tracks more closely with review-base size than with geography specifically.

#How many places has Revdict analyzed outside the United States?

As of September 2026, roughly 200 of the 659 places in our public catalog are outside the US, spread across more than 20 countries, led by Poland, the UK, France, and Germany.

#Why do small businesses score higher on average in this data?

A burst of coordinated reviews moves a rating far more on a base of a few hundred reviews than on a base of several thousand, so a small, single-location business is more exposed to the same size manipulation attempt than a large chain with years of review history.

#Should I trust a business less just because it's in a country with a higher average score in this table?

No. These are aggregate patterns across small country samples, not a verdict on any individual listing. Check the specific business's own report or run a fresh analysis rather than generalizing from where it's located.