POST: Submissions to DH2016 (pt. 1)

Scott Weingart (Carnegie Mellon University) has published the first DH2016 post in his ongoing series analyzing submissions and acceptances to the annual Digital Humanities conference. Weingart scraped data from the conference submission tool (ConfTool), which allowed him to compare this year’s number of submissions, type (long paper, short paper, panel, or poster), number of authors per submission, and trends within the topics tagged for each submission. This last metric in particular had some interesting outcomes, when compared to data from prior years:

In a reveal that will shock all species in the known universe, text analysis dominates DH2016 submissions—the proportion even grew from previous years. Text & data mining, archives, and data visualization aren’t far behind, each growing from previous years.

What did actually (pleasantly) surprise me was that, for the first time since I began counting in 2013, history submissions outnumber literary ones. Compare this to 2013, when literary studies were twice as well represented as historical. Other top-level categories experiencing growth include: corpus studies, content analysis, knowledge representation, NLP, and linguistics.

Two areas which I’ve pointed out previously as needing better representation, geography and pedagogy, both grew compared to previous years. I’ve also pointed out a lack of discussion of diversity, but part of that lack was that authors had no “diversity” category to label their research with—that is, the issue I pointed out may have been as much a problem with the topic taxonomy as with the research itself. ADHO added “Diversity” and “Multilinguality” as potential topic labels this year, which were tagged to 9.4% and 6.5% of submissions, respectively. One-in-ten submissions dealing specifically with issues of diversity is encouraging to see.

Author: Caitlin Christian-Lamb

Caitlin is a PhD candidate and instructor of record at the University of Maryland’s iSchool, where she is affiliated with the Ethics and Values in Design Lab (EViD) and the University of Maryland Institute for Advanced Computer Studies (UMIACS).