Introduction to text mining in R workshop

Basics

Days: January 18th, 20th, and 22nd.

Teaching times: 10am to noon, then 2pm to 4pm. We’ll meet on Zoom. You’ll receive an email with my personal meeting room information.

My email address: victor.pena@baruch.cuny.edu.

Office hours: By appointment. Send me an email and we’ll make it work.

Prerequisites

• Some working R knowledge at the level of Introduction to R.

• Some working knowledge of linear regression and machine learning methods.

• Getting access to Datacamp: You can register for Datacamp here. You will have to register with your @baruch.cuny.edu email address to join Datacamp. If you want to use another email address, please let me know.

Logistics

I recommend that you take Introduction to text analysis in R on Datacamp. It’s a nice and gentle introduction to text analysis which uses packages in the tidyverse. After you take that, if you want to learn more text mining with R, I strongly recommend that you take a look at the book Text Mining with R.

Here are some links to datasets we will use

• Roomba reviews
• Tweets
• Animal farm

And here are some links to the code we wrote in our sessions

• Roomba
• Tweets (“solution”)
• Animal farm
• Congress data
• Regular expressions

Here are some slides

Books (all open-access)

• Text Mining with R, by Julia Silge and David Robinson.

• Introduction to Statistical Learning, by James, Witten, Hastie, and Tibshirani.

• ModernDive, by Chester Ismay and Albert Y. Kim.

• R for Data Science, by Hadley Wickham.

• R Programming for Data Science, by Roger Peng.