Week 2 (Aug 29, 31, Sep 2):
Monday: Voyant Project Development
- Decide on two or more texts for Module Project 1 before class. For detailed instructions, check out the “Assignment and Evaluation” page.
Wednesday: “Knowing a Word by the Company It Keeps”: Topic Modeling
- Read:
- Matthew L. Jockers, Macroanalysis: Digital Methods and Literary History, Ch.8(“Theme”)
- Ted Underwood, “Topic modeling made just simple enough” (optional)
- Explore:
- Topical Guide
- Brad Borevitz’s State of the Union site OR SpeechWars
- Recommended:
- Mining the Dispatch (The “Introduction” explains briefly what topic modeling is and the “Topics” page gives examples of how it works)
Study Guide:
- Chapter 8 (“Theme”) of Macroanalysis uses a method called “topic modeling” to analyze a corpus of 3,346 nineteenth-century books from the Stanford Literary Lab’s collection. “Topic modeling” is a sophisticated method of text analysis, which shares some of the basic assumptions underlying the word-frequency approach (as employed in word clouds and Google N-gram Viewer) but also makes significant improvements over it. Chapter 8 offers a brief explanation of how topic modeling works (pp.122-4), gives a few examples of its application on the corpus (pp.124-53), and discusses its advantages (pp.118-22). Read Chapter 8 and consider: How does topic modeling work? What assumptions do topic modeling and word-frequency-based analyses share? What advantages does topic modeling have over the word-frequency approach to text analysis? If you’d like to know a little bit more, consult Ted Underwood’s short blog post “Topic modeling made just simple enough” (optional).
- Comparing the following websites, which take different approaches to the State of the Union addresses in U.S. history: Brad Borevitz’s State of the Union and SpeechWars take the word-frequency approach, while Topical Guide takes the topic modeling approach.
Friday: Oral Presentation Workshop: How to Give a Brilliant Presentation
- Give Your Module Project 1 (Voyant Project) Presentation Today!
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