scholarly journals Dynamic Restaurants Quality Mapping Using Online User Reviews

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1104-1112
Author(s):  
Didier Grimaldi ◽  
Carly Collins ◽  
Sebastian Garcia Acosta
Keyword(s):  
Rating Scale ◽  
National Health System ◽  
Foodborne Illness ◽  
Network Data ◽  
Social Network Data ◽  
Food Practices ◽  
Restaurant Management ◽  
Online User Reviews ◽  
Safe Food

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.

scholarly journals Online Data Preprocessing: A Case Study Approach

2019 ◽  
Vol 9 (4) ◽  
pp. 2620
Author(s):  
Mohammed Zuhair Al-Taie ◽  
Seifedine Kadry ◽  
Joel Pinho Lucas
Keyword(s):  
Social Network ◽  
Data Preprocessing ◽  
Quality Data ◽  
The Internet ◽  
Network Data ◽  
Quality Of Data ◽  
Standard Format ◽  
Social Network Data

<span lang="EN-US">Besides the Internet search facility and e-mails, social networking is now one of the three best uses of the Internet. A tremendous number of volunteers every day write articles, share photos, videos and links at a scope and scale never imagined before. However, because social network data are huge and come from heterogeneous sources, the data are highly susceptible to inconsistency, redundancy, noise, and loss. For data scientists, preparing the data and getting it into a standard format is critical because the quality of data is going to directly affect the performance of mining algorithms that are going to be applied next. Low-quality data will certainly limit the analysis and lower the quality of mining results. To this end, the goal of this study is to provide an overview of the different phases involved in data preprocessing, with a focus on social network data. As a case study, we will show how we applied preprocessing to the data that we collected for the Malaysian Flight MH370 that disappeared in 2014.</span>

Food Safety Tips for the Holiday Season

EDIS ◽  
2017 ◽  
Vol 2017 (6) ◽  
Author(s):  
Soohyoun Ahn ◽  
Jessica A. Lepper ◽  
Keith R. Schneider
Keyword(s):  
Food Safety ◽  
Meat Products ◽  
Foodborne Illness ◽  
Good News ◽  
Safety Measures ◽  
Food Practices ◽  
Holiday Season ◽  
Safe Food

Food is always an important part of holiday festivities, but holiday meals can take a turn for the worse if food safety is not properly practiced when preparing and cooking the food. The food you serve your family and friends can make them ill if your turkey, ham, or home-prepared meat products are not properly handled. The good news is that, by practicing basic food safety measures, you can help prevent foodborne illness over the holiday season. This factsheet provides information about safe food practices for the holidays.

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