Machine learning system detects 10 outbreaks of foodborne illness from Yelp reviews

Columbia University and the New York City Department of Health and Mental Hygiene (DOHMH) have developed a machine learning computer system that uses keywords found on Yelp reviews to identify foodborne illnesses and outbreaks. Findings are published in the Journal of the American Medical Informatics Association. Introduced in 2012, a prototype text classifier of the system was developed to determine if a review showed a person experiencing a foodborne illness and to determine if the review indicated multiple foodborne illnesses based on the keywords used in the review. "Effective information extraction regarding foodborne illness from social media is of high importance--online restaurant review sites are popular, and many people are more likely to discuss food poisoning incidents in such sites than on official government channels," said Luis Gravano and Daniel Hsu, coauthors of the study and professors of Computer Science at Columbia Engineering. "Using machine learning has already had a significant impact on the detection of outbreaks of foodborne illnesses."