Elijah Meeks and Scott Weingart are guest editors for the latest edition of Journal of Digital Humanities, which is devoted entirely to topic modeling (Vol. 2, No. 1 Winter 2012). Topic modeling is a method of textual analysis that has gained popularity in the humanities in the last few years. It uses computer algorithms to find patterns in large corpora of texts, allowing researchers to examine the thematic structure of large sets of documents. As Meeks and Weingart point out in their article introducing the issue, use of topic modeling in the humanities has been increasing since about 2010 but the scholarship around it remains dispersed:
In this additional way topic modeling typifies digital humanities: the work is almost entirely represented in that gray literature. While there is a hefty bibliography for spatial analysis in humanities scholarship, for example, in order to follow research that deploys topic modeling for humanities inquiry you must read blogs and attend conference presentations and workshops. For those not already participating in the conversation, this dispersed discussion can be a circuitous and imposing barrier to entry. In addition to sprawling across blogs, tweets, and comment threads, contributions also span methods and disciplines, employ sophisticated visualizations, sometimes delve into statistics and code, and other times adopt the language of literary critique.
The article goes on to outline the structure of the issue’s contents and provides a useful introduction to concepts and tools along the way.
This post was produced through a cooperation between Caro Pinto and Patrick Williams (Editors-at-Large for the week), Roxanne Shirazi (Editor for the week), and Zach Coble and Sarah Potvin (site editors).