/Vegas_Foodies

This project was completed by four masters students from New York University's Center for Data Science for our Introduction to Data Science Class. It seeks to answer the question: How can restaurants improve their Yelp profiles for success?

Primary LanguageJupyter Notebook

Food Happens in Vegas: How can restaurants improve their Yelp profiles for success?

Vegas Foodies:

  • Elizabeth Combs
  • Anu-Ujin Gerelt-Od
  • Wendy Hou
  • Emmy Phung

Abstract

The purpose of this data mining project is to examine how restaurants can improve their Yelp profile to become more “successful” on Yelp in Las Vegas, Nevada. Differently from the traditional approaches to this dataset, our methodology defines “success” as a binary variable through an exploratory analysis of the restaurants’ review counts and ratings on Yelp. Feature variables include categories and attributes that Yelp users can use to select which restaurant to visit. For this project, we ran Decision Tree, Random Forest, and Logistic Regression to explore key features associated with “success” and obtain recommendations for restaurants to improve their Yelp profile. Final results indicate that determinants of success vary by cuisine type.

Data Source:

https://www.kaggle.com/yelp-dataset/yelp-dataset#yelp_academic_dataset_business.json