As a part of the library at Iliff School of Theology, Experimental Humanities @Iliff is a collaborative effort to provide spaces for students, staff, and faculty to explore and experiment with emerging research methodologies in the humanities, focused particularly in the areas of religious and theological studies. In line with our library’s emphasis on collaboratively cultivating media capacities, we support projects such as learning basic programming capacities, using Natural Language Processing tools to explore and visualize religious texts and identities, and building interfaces for engaging artifacts beyond text.
Please feel free to contact us with questions or comments at firstname.lastname@example.org.
Best Practices for Topic Models
Topic modeling is a text mining technique in which an algorithm is applied to a large corpus of documents that identifies patterns of word co-occurrence. These patterns of word co-occurrence are conceptualized as “topics” which can be used to discover latent structures in the corpus, to group similar documents together, or to serve as the basis of information retrieval. This project takes the Journal of Biblical Literature as test corpus and experiments with parameters to find the best practices for constructing topic models.
Using a Google Search Algorithm to make sense of the Bible
Human beings have a difficult time making sense of large corpora such as the Bible. No one can possibly maintain in their awareness at a single point in time all the different themes and points of view expressed therein. How should a reader make sense of it all? Which texts or statements are most important? What should a reader do when conflicting viewpoints arise? An algorithm used by Google may help answer these questions (and simultaneously provide a sort of CliffsNotes to this sometimes daunting corpus!).
KJVBot is an exploration of the nature of biblical prophetic utterance using the King James Version of the Bible and Markov chains. Can a robot be a prophet? Are these utterances bible?