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 \(k\)

Before class

Class materials

To do for Monday

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Benjamin Soltoff
Assistant Instructional Professor in Computational Social Science