According to University of Rochester researchers, the cumulative information tweeted from smartphone users could give reports on food safety equal to official government inspections — in fact, even better since reports are in real time.
Rochester researchers say their nEmesis system monitors the tweets from restaurant patrons, and can warn of the possibility of food poisoning at particular restaurants.
The nEmesis program was developed at the University of Rochester by Adam Sadilek, currently a data scientist for Google. Twitter proved an effective way to track the spread of the flu, and analyze how lifestyle factors affect mental and physical health.
According to the research paper, during a four-month-long test in New York City, the system collected 3.8 million tweets from more than 94,000 users, traced 23,000 restaurant visitors, and found 480 reports of likely food poisoning.
Researchers found that when compared to the NY Health Department’s grading of those restaurants, there was a direct correlation between the restaurant’s food safety standards and poor dining experience.
Based on nEmesis data, health grades were assigned to restaurants and matched closely to the grades from the Department of Health.
According to the researchers, roughly one-third of Twitter data reliably predicted the rating of the restaurant.
“The Twitter reports are not an exact indicator ” any individual case could well be due to factors unrelated to the restaurant meal ” but in aggregate the numbers are revealing,” said Henry Kautz, chair of the computer science department at the University of Rochester and co-author of the paper.
In other words, a “seemingly random collection of online rants becomes an actionable alert,” according to Kautz, which can help promptly detect cases of foodborne illness.
The nEmesis program monitors relevant public tweets and detects restaurant visits by matching up where a person tweets from and the known locations of restaurants.
Tweets which are GPS enabled can be “geotagged” so that both the information and location of the user are recorded.
If a user tweets from a location that is determined to be a restaurant, the system will track that person’s tweets for 72 hours, even when they’re not geotagged, or when they are tweeted from a different device.
If a user then tweets about feeling ill, the system captures the information along with the specific restaurant that was visited.
As Motherboard’s Meghan Neal points out, the biggest challenge in preventing food poisoning is how quick information is transmitted to the public.
In New York, for example, Neal notes many restaurants are only inspected once a year, and budget problems aren’t helping that rate.
Researchers say the Twitter tracking model could enhance the health inspection system.
“It would be like a first pass for health officials based on the aggregate of millions of 140-character updates. Officials could decide which venues were suspicious and in need of an inspection.”
Researchers warn that since the system only considers people who tweet, the system is not a representative sample of the whole population or of the population visiting a restaurant.
But they add the Twitter data can be used together with knowledge gained from other sources to detect foodborne illness in a timely manner.
“It provides an extra layer ” a passive level of monitoring ” which is cost-effective. And the information that nEmesis offers can benefit both Twitter and non-Twitter users.”