Next time your restaurant receives a lousy online review, consider the person who wrote it. Perhaps she lives in a crowded apartment complex somewhere in New York, where it's freezing (and expensive). Or perhaps she lives in California, where it's sunny but the rent's just as high. 

It's factors like these--the weather, the size and racial makeup of a city, and the price of a meal--that can sway the quality--and quantity--of online restaurant reviews, according to the first large-scale academic study to analyze how outside factors might affect a review site. 

The study, released Wednesday, used computer models to analyze nearly 1.1 million reviews of 840,000 restaurants over nearly a decade. Among the findings: Restaurants in the Northeast or on the West Coast were more likely to be reviewed than those in the South or Midwest. More reviews were posted in summer months (June and August). 

Also, if the weather was lousy, reviews were as well: The most negative ones were written when it was colder than 40 degrees or warmer than 100 degrees, or raining or snowing. 

Researchers Saeideh Bakshi, a doctoral student at the Georgia Institute of Technology, her husband Partha Kanuparthy, who works for Yahoo Labs, and Eric Gilbert, an assistant professor at the university, told The New York Times they were surprised to learn the weather held so much sway over online reviews. 

However, the type of restaurant might also affect a review, which is important to note. Sushi restaurants consistenly scored higher than hamburger joints, as if to show a heftier cost and upscale ambience can lead to better reviews. People who waited for a table in busier cities also tended to be more forgiving than those who waited and were in a smaller community. 

The analytic computer models used to derive these findings were based on data from several sites, including Citysearch, TripAdvisor, and Foursquare, reports The Times. Yelp, which is perhaps the most popular site with more than 53 million reviews since its launch in 2004, refused to share the amount of data required to participate in the study.