  Informatics around public health are increasingly shifting from the
professional to the public spheres. In this work, we apply linguistic analytics
to restaurant reviews, from Yelp, in order to automatically predict official
health inspection reports. We consider two types of feature sets, i.e., keyword
detection and topic model features, and use these in several classification
methods. Our empirical analysis shows that these extracted features can predict
public health inspection reports with over 90% accuracy using simple support
vector machines.
