Where Not to Eat? Improving Public Policy by Predicting Hygiene Inspections Using Online Reviews

Empirical Methods in Natural Language Processing (Forthcoming)

Posted: 13 Jul 2013 Last revised: 26 Sep 2013

See all articles by Jun Seok Kang

Jun Seok Kang

Stony Brook University

Polina Kuznetsova

Stony Brook University

Yejin Choi

Stony Brook University

Michael Luca

Harvard University - Business School (HBS)

Date Written: September 26, 2013

Abstract

This paper offers an approach for governments to harness the information contained in social media in order to make public inspections and disclosure more efficient. As a case study, we turn to restaurant hygiene inspections – which are done for restaurants throughout the United States and in most of the world and are a frequently cited example of public inspections and disclosure. We present the first empirical study that shows the viability of statistical models that learn the mapping between textual signals in restaurant reviews and the hygiene inspection records from the Department of Public Health. The learned model achieves over 82% accuracy in discriminating severe offenders from places with no violation, and provides insights into salient cues in reviews that are indicative of the restaurant’s sanitary conditions. Our study suggests that public disclosure policy can be improved by mining public opinions from social media to target inspections and to provide alternative forms of disclosure to customers.

Suggested Citation

Kang, Jun Seok and Kuznetsova, Polina and Choi, Yejin and Luca, Michael, Where Not to Eat? Improving Public Policy by Predicting Hygiene Inspections Using Online Reviews (September 26, 2013). Empirical Methods in Natural Language Processing (Forthcoming), Available at SSRN: https://ssrn.com/abstract=2293165 or http://dx.doi.org/10.2139/ssrn.2293165

Jun Seok Kang

Stony Brook University ( email )

Health Science Center

Polina Kuznetsova

Stony Brook University ( email )

Health Science Center

Yejin Choi

Stony Brook University ( email )

Health Science Center

Michael Luca (Contact Author)

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Boston, MA 02163
United States

HOME PAGE: http://drfd.hbs.edu/fit/public/facultyInfo.do?facInfo=ovr&facId=602417

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