I turn to HathiTrust and its analytics center to model how its tools can be used to study shellshock across 4 corpora: a 100-volume corpus of medical periodicals, a 189-volume corpus of non-medical peridicals, across a small-scale (8-volume) corpus of war poetry, which I compare with another small-scale (7-volume) corpus of novels by Mary Borden.
After experimenting with Bookworm in my prior case study, I delved into HathiTrust’s Analytics Research Center, where I used HathiTrust’s freely available InPho Topic Explorer, along with documentation for its use.
This tool draws upon a topic modeling technique known as Latent Dirichlet Allocation, which allows a researcher to extract and cluster topics from a workset or corpus.
Across this case study, I model some potential means of large-scale reading for shellshock across popular culture and war poetry.