You must complete one out of homeworks #4, #5, and #6.

The invitation link for this week is:

https://classroom.github.com/a/E5aA08Cm

In this assignment, we'll explore restaurant review data available through the Yelp Dataset Challenge. The dataset includes Yelp data for user reviews and business information for 10 metropolitan areas. The data directory in this repository includes data files for reviews and restaurants in 3 of these cities: Cleveland, Pittsburgh, and Charlotte. These cities were chosen since the data is not too large — the data for the other cities can be downloaded from the Yelp download page. For this assignment, you are welcome to analyze data any of the three cities.

This assignment is broken into two parts:

Because Yelp reviews include the number of stars given by the user, the Yelp data set provides a unique opportunity to test how well our sentiment analysis works by comparing the number of stars to the polarity of reviews.

Analyzing the frequencies of different sets of words in Yelp reviews can offer insight into urban culture. Specifically, we'll test the correlation between household income (using census data) and different types of restaurants, extracted from review data.

• Does sentiment analysis work?
• The Geography of Taste: Using Yelp to Study Urban Culture

A skeleton Jupyter notebook is available in this repository that will walk you through the steps of the assignment. The completed notebook should be submitted as your assignment.

We'll be using GitHub for assignment submission again. You can set up your own private repository on GitHub for this assignment using the link below.

The invitation link for this week is:

https://classroom.github.com/a/E5aA08Cm