Research Guides: Data Services Class Descriptions: Starting with Computational Text Analysis

An introductory class to Computational Text Analysis in R for primarily the social sciences and humanities.

Software:	R and RStudio
Duration:	120 min
Room description:	Some tutorials are held remotely and require NYU sign on to access, while others are held in person, without a remote component. Please note the correct modality and location of the tutorial when registering.
Prerequisites:	Basic computer literacy for Windows or for Mac Understanding file paths Ability to load data into R from a .csv Ability to load an R package Understanding of the names and uses of different object types in R Some exposure to RStudio and the Tidyverse is preferable
Skills Taught / Learning Outcomes:	What is CTA? Text as Data Text corpus construction Cleaning data Dictionary methods, sorting, and counting Overview of useful R packages
Class Materials:	State of the Union R package Tidyverse R packages Quanteda R packages
Related Classes:	Data Wrangling in R Introduction to R Digital Tools for QDA Introduction to MAXQDA
Additional Training Materials:	Data Services Qualitative Data Analysis and Text Data Mining pages
Feedback:	bit.ly/feedbackds

Data Services Class Descriptions