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Scientific Article details

Title Dynamic Restaurants Quality Mapping Using Online User Reviews
ID_Doc 43637
Authors Grimaldi, D; Collins, C; Acosta, SG
Title Dynamic Restaurants Quality Mapping Using Online User Reviews
Year 2021
Published Smart Cities, 4, 3
DOI 10.3390/smartcities4030058
Abstract Millions of users post comments to TripAdvisor daily, together with a numeric evaluation of their experience using a rating scale of between 1 and 5 stars. At the same time, inspectors dispatched by national and local authorities visit restaurant premises regularly to audit hygiene standards, safe food practices, and overall cleanliness. The purpose of our study is to analyze the use of online-generated reviews (OGRs) as a tool to complement official restaurant inspection procedures. Our case study-based approach, with the help of a Python-based scraping library, consists of collecting OGR data from TripAdvisor and comparing them to extant restaurants' health inspection reports. Our findings reveal that a correlation does exist between OGRs and national health system scorings. In other words, OGRs were found to provide valid indicators of restaurant quality based on inspection ratings and can thus contribute to the prevention of foodborne illness among citizens in real time. The originality of the paper resides in the use of big data and social network data as a an easily accessible, zero-cost, and complementary tool in disease prevention systems. Incorporated in restaurant management dashboards, it will aid in determining what action plans are necessary to improve quality and customer experience on the premises.
Author Keywords OGRs; health; smart city; food safety; big data
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:000701074000001
WoS Category Engineering, Electrical & Electronic; Urban Studies
Research Area Engineering; Urban Studies
PDF https://www.mdpi.com/2624-6511/4/3/58/pdf?version=1627893789
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