# Text analysis: classification and topic modeling

Date
Event
Location
Room 104, Stuart Hall, Chicago, IL

## Overview

• Define a document-term matrix
• Use text as predictors for classification algorithms
• Define topic modeling
• Explain Latent Dirichlet allocation and how this process works
• Demonstrate how to use LDA to recover topic structure from a known set of topics
• Demonstrate how to use LDA to recover topic structure from an unknown set of topics
• Identify methods for selecting the appropriate parameter for $$k$$