As a new digital humanities scholar, my project focuses on tracing the development of media narratives related to police brutality against African-Americans over the past fifty years. Now daunted by the sheer amount of sources that could comprise my corpus, I am looking for a way to focus my search for source material. I could, of course, simply search for phrases in digitized newspapers and literature. "Police brutality" and "African-American" would turn up a few--if not an innumerable amount of--responses. But what I am really looking for is a means of zeroing in on the narratives surrounding these two phrases.
Enter topic modeling. From what I've learned thus far, it appears that topic modeling is my best starting point. Stanford and the University of North Texas's Mapping Text project, http://language.mappingtexts.org/, is my working inspiration.
In embarking on this new scholarly journey, I've come across a few resources that I have found helpful thus far; I thought I'd share them with any other burgeoning topic modelers in the HASTAC community. Some of the topic modeling sources I discovered are overlayed with dense computer-science lingo, so I've tried to make this list user friendly for non-computer science researchers like myself. If any more experienced DH scholars can add to this list, I'd appreciate it!
• Scott Weingart, http://www.scottbot.net/HIAL/?p=221
Software tools (for those who eschew command lines)
• Paper Machines, https://github.com/papermachines/papermachines (works as an extension to Zotero; can also incorporate data from JSTOR Data for Research)
• Stanford Topic Modeling Toolbox, http://nlp.stanford.edu/software/tmt/tmt-0.3/ (runs in MS Excel; allows you to track topics over time)
For more info
• Topic Models Mailing List, https://lists.cs.princeton.edu/mailman/listinfo/topic-models (run by David M. Blei of Princeton. For his webpage on topic modeling, see http://www.cs.princeton.edu/~blei/topicmodeling.html)
• David Mimno’s bibliography, http://mimno.infosci.cornell.edu/topics.html
• David Mimno Blog, http://mimno.org/articles/phrases/ (how to catch phrases (no pun intended) in your topic modeling search)
* thestarrynight image, http://journalofdigitalhumanities.org/2-1/topic-modeling-and-figurative-...