Discovering foodborne illness in online restaurant reviews.

ABSTRACT: Objective:We developed a system for the discovery of foodborne illness mentioned in online Yelp restaurant reviews using text classification. The system is used by the New York City Department of Health and Mental Hygiene (DOHMH) to monitor Yelp for foodborne illness complaints. Materials and Methods:We built classifiers for 2 tasks: (1) determining if a review indicated a person experiencing foodborne illness and (2) determining if a review indicated multiple people experiencing foodborne illness. We first developed a prototype classifier in 2012 for both tasks using a small labeled dataset. Over years of system deployment, DOHMH epidemiologists labeled 13 526 reviews selected by this classifier. We used these biased data and a sample of complementary reviews in a principled bias-adjusted

SUBMITTER: Effland T 

PROVIDER: S-EPMC7647154 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature