Text Mining YouTube Comment Data with Wordfish in R

This lesson will introduce readers to a method for conducting research on internet discourse by performing data analysis on comments posted under YouTube videos by viewers.

You will learn how to download YouTube video comments and analyze their textual data using the natural language processing algorithm Wordfish. Designed for scaling textual data using unsupervised machine learning, Wordfish brings into relief the salient dimensions of latent meaning within a corpus.

This lesson will guide you through three key phases of 1) data collection, 2) data preparation (cleaning and modeling), and 3) data analysis (including generating visualizations).

#Reviewed by:

• Janna Joceli Omena
• Heather Lang

#Learning outcomes

After completing this lesson, you will be able to:

• Use YouTube Data Tools to download video comments and metadata
• Use R to sort and clean the comment data
• Use Wordfish to analyze and visualize the comment data to search for underlying meaning and ideological positioning within