Overview

• Identify the basic workflow for conducting text analysis
• Define sentiment analysis and review its use in academic research
• Define the tidy text format
• Demonstrate how to conduct sentiment analysis using tweets
• Explain how to generate and interpret a wordcloud

Before class

• Read chapters 1-4 in Tidy Text Mining with R
• Read two blog posts by David Robinson (co-author of tidytext) analyzing Donald J. Trump’s twitter account
  • Text analysis of Trump’s tweets confirms he writes only the (angrier) Android half
  • Trump’s Android and iPhone tweets, one year later
  • Regardless of your political affiliations, these are excellent examples demonstrating many of the key principles of reproducible research that we’ve learned in this course
    • R Markdown documents and knitting code with output
    • Retrieving data from APIs
    • Textual analysis with tidytext
    • Visualizations with ggplot2

Slides and links

• Slides
• Text analysis: basic workflow
• Practicing tidytext with song titles
• Practicing sentiment analysis with Harry Potter

What you need to do