Technology that eavesdrops on tweets could warn you of how likely it is to become ill by visiting a restaurant.
The system, dubbed ‘nEmesis’, combines machine-learning and crowdsourcing techniques to analyse millions of tweets posted by people after visiting restaurants.
It then ranks restaurants according to how likely it is for someone to get food poisoning after eating there.
In just four months, the system collected 3.8 million tweets from more than 94,000 unique users in New York City, traced 23,000 restaurant visitors, and found 480 reports of likely food poisoning.
According to scientists at the University of Rochester in New York, the technology could also be used by
authorities to better monitor food safety, by providing more timely restaurant inspections.
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