# Text analysis: classification and topic modeling

## Overview

• Introduce supervised text classification
• Implement a tidymodels workflow using text features
• Define topic modeling
• Explain Latent Dirichlet allocation and how this process works
• Demonstrate how to use LDA to recover topic structure from an unknown set of topics
• Identify methods for selecting the appropriate parameter for $k$