The goal of this research project has been to build a generalizable workflow which enables both “close” and “distant reading” and language modeling of a digitized corpus in a field of study. The case study is the field of Near Eastern Studies, and the models we have made thus far lend themselves to both qualitative and quantitative analysis, capable of describing the research landscape over time. While we’ve made good progress toward this goal over the last year with word embeddings and topic modeling, we now hope to include n-gram and deep learning methods, including BERT implementations, which be will incorporated into the resulting network models.

Look at the poster presentation. 

Spring 2020