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Class 5 Notes

Page history last edited by Alan Liu 5 years, 9 months ago

Preliminary Class Business



  • Class 6 on Social Network Analysis:
    • Visit by Mark Algee-Hewitt and Ryan Heuser, co-associate directors of the Stanford Literary LabPlease read in advance France Moretii, "'Operationalizing': Or, The Function of Measurement in Modern Literary Theory" [PDF] (Stanford Lit Lab Pamphlet #6, 2013)
    • Rough agenda for Class 6:
      • 1. Introductions all around
        2. Mark and Ryan talk informally "about our own work and backgrounds, maybe discuss a couple of projects under the rubric of how they operationalize various questions or concepts and then open the floor for some more general discussion."
        3. Alan will note the connections between the Stanford Lit Lab work (and the "Operationalizing" essay) and the social network analysis topic that is the specific subject of this particular class.
        4. Depending on the time remaining, we'll take a look at some of the student beginner practicums in using Gephi and social network visualization as a springboard to discussing larger issues related to network analysis.
    • Preview of readings and practicum for Class 6
      • Using Gephi
      • Note: the practicums for classes 5 and 6 are the most technically advanced in this course, which is designed for beginners.
      • Not covered in this course are more advanced, customized, and specialized DH methods and workflows that require setting up a "development environment" on one's computer, usually operated at the command-line level.  Such a development environment often includes a combination of the following:
        • Python (a programming language/environment used in diverse research disciplines, with many extensible "packages" or "libraries" for a variety of text-processing, statistical, and other purposes).
        •  R  (programming language and software environment for "statistical computing and graphics")
        • Git and Github (version control and repository system for managing project revisions and sharing, collaborating on, or branching from projects).




Intro to Class





1. Our Topic Modeling Practicums (and our questions)





2. Theory, Practice, & Applied Uses of Topic Modeling







4. The Conceptual Challenge of Topic Modeling


  • Phenomena that appear in distant reading:

          (in escalating scale of possible disturbance to humanists)


    • Pattern
    • Scale phenomena / Cyclical phenomena
    • Quantitative phenomena
    • Probabilistic phenomena
    • [Network phenomena]



Matt Burton, probability graph of topic-modeled words                                               Conceptual graph by Matt Burton







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