Week 8: text analysis
Summary
This week we will learn about imaging and OCR tools for converting images of comics, fanzines, and similar documents to searchable text, and we will learn about and use a few text analysis tools to analyze textual data about comics and comics readers.
Weekly Learning Objectives
- Use Voyant to analyze a corpus of letters of comment.
- Use AntConc to analyze a corpus of letters of comment
- Use Mallet to generate topic models from a corpus of letters of comment.
Before class: Readings, resources, and tasks
Readings
- Webinar on text analysis with Voyant Tools by their developer Professor Geoffrey Rockwell
- Anthony, L. (2022). AncConc 4 Tutorials. Watch all the tutorials; in total they run about 90 minutes.
- Froehlich, H. (2015, 2022). Corpus Analysis with Antconc. Programming Historian.
- Goldstone, G., & Underwood, T. (2012). What can topic models of PMLA teach us about the history of literary scholarship? Retrieved from https://tedunderwood.com/2012/12/14/what-can-topic-models-of-pmla-teach-us-about-the-history-of-literary-scholarship/
- Graham, S., Weingart, S., & Milligan, I. (2012). Getting Started with Topic Modeling and MALLET. Retrieved from http://programminghistorian.org/lessons/topic-modeling-and-mallet
In class
- Brief lecture and demos of Voyant, AntConc, and MALLET, focusing on the kinds of questions each tool supports
- Guided, structured exercises using a shared corpus of Spider-Man fan letters
- Group discussion comparing results and reflecting on how different tools shape interpretation
Comics-related text corpora
Amazing Spider-Man Fan Mail 1963-1995
MALLET Topic Model output files