Which Kinds of Restaurants Get Flagged Most? Burgers, Pizza, Breakfast and More

Restaurant type tracks how often our analysis flags a place. Among 309 labeled restaurants in the Revdict catalog, burger, fast-food and pizza places were flagged 5.4% of the time, against 20.6% for every other restaurant type, and breakfast and Brazilian restaurants ran above 50%. The data is as of October 2026, and the smaller groups hold fewer than a dozen places each.

#What did we measure?

We took every place in the Revdict catalog that has a completed analysis, 729 as of October 2026, and kept those whose Google Maps category is a restaurant, diner or steak house: 309 places. For each category we recorded the average manipulation score (0 to 100, higher means more manipulation signals) and the share of places with a verdict other than clean.

The caveats are heavy here. The catalog is not a random sample of restaurants; visitors submit places they are curious about, and most of these are well-known spots in a few US cities. Several categories have fewer than ten places, so one place changes the percentage by more than ten points. Treat the table as a description of our data. It is not a ranking of cuisines, and a score is a statement about review patterns, not about what any owner did.

#Which restaurant types are flagged most often?

Breakfast and Brazilian restaurants top the list, burger and pizza places sit at the bottom.

Across all 309 places, 17.8% were not clean and the average score was 22.8. The two highest groups, breakfast and Brazilian, have 9 and 8 places. That is four or five flagged places each, enough to notice and nowhere near enough to generalize.

#Why do burger, pizza and fast-food places look so clean?

Our reading is that the places in these groups are mostly recognizable names with large, steady review streams. Pizza, burger and fast-food places in the catalog have a combined median of about 5,800 reviews per place and, in the pizza group, not a single flagged place. When a place gets reviews every day from walk-in customers, a coordinated batch has little room to stand out.

Fast food is the odd one out on rating: its average is 3.82 stars against about 4.5 for other restaurants. That fits what we see elsewhere. Our look at ratings and review counts found scores climbing as ratings approach 5.0, and a lower average rating usually means a more honest spread of opinions.

#Why might breakfast and Brazilian spots score higher?

We can only offer hypotheses, and the sample is too small to test them. Brunch spots live on weekend lines and tourist searches, and a long wait invites owners to ask every customer for a review at the table. When many reviews arrive in a short window from accounts with little history, our model reads it as a burst or a solicitation pattern.

That second pattern matters. Of the 17 places in the catalog with a solicitation-campaign verdict, 12 are labeled restaurants. A review drive can involve real customers who were asked in the moment, which is why the verdict is separate from a likely-manipulated one. It is a different thing from buying fake reviews, and the FTC's rules treat asking for reviews and buying them very differently.

#What does a missing cuisine label tell us?

Places labeled simply "Restaurant" are flagged 25% of the time, higher than any specific cuisine except the small groups above. The label comes from Google Maps. Owners choose it, and a generic label often means a listing that has been filled in less carefully, which is common at smaller independents. It does not mean those restaurants are doing anything wrong. It is another way the data points at the same variable: smaller, less established review bases are harder to read.

#How reliable is a table this small?

Not very, and it is worth being concrete about why. With 9 places in a group, one more flagged place moves the share by 11 points, so the gap between 33% and 56% is two places. The larger groups are steadier: the 56 burger, fast-food and pizza places and the 253 other restaurants are big enough that the 5.4% against 20.6% gap is unlikely to be a fluke. The cuisine-by-cuisine ranking below that is not.

We will revisit this as the catalog grows. Each new analysis adds to the sample, and a category that looks unusual at 9 places often drifts toward the average at 40. Until then, use the broad finding (high-volume, familiar places are flagged less) and ignore the ordering of the small groups.

#What should diners and owners do with this?

Do not avoid a cuisine because of a table like this. The spread inside each type is much larger than the gap between types, and the place in front of you is what matters.

• If you are choosing between two similar restaurants, compare the recent reviews of each, not the categories.
• If you own a restaurant, ask for reviews in a way that does not select for happy customers, and avoid incentives. This guide to asking for reviews legally walks through the FTC and Google rules.
• To check a specific restaurant, paste its Google Maps link into Revdict's free analyzer.

#Frequently asked questions

#Which type of restaurant has the most fake reviews?

We cannot say. In our October 2026 data breakfast restaurants had the highest flagged share (5 of 9), but groups that small cannot rank cuisines. Manipulation follows individual businesses.

#Are chain restaurants more trustworthy on Google?

In our sample, burger, fast-food and pizza places were flagged less often (5.4% of 56). Large review volumes make coordinated manipulation harder, but a clean record for a category says nothing about one particular branch.

#Does a solicitation-campaign verdict mean the reviews are fake?

No. It means many reviews arrived in a pattern consistent with a push to collect reviews, often from real customers. It is a pattern in the data, not a finding of fraud.