https://github.com/diyclassics/exploratory-philology-trinity
This repo contains notebooks for an workshop at Trinity University on 10.27.2022 on learning to explore Latin text with Python
https://github.com/diyclassics/exploratory-philology-trinity
Last synced: about 1 year ago
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This repo contains notebooks for an workshop at Trinity University on 10.27.2022 on learning to explore Latin text with Python
- Host: GitHub
- URL: https://github.com/diyclassics/exploratory-philology-trinity
- Owner: diyclassics
- Created: 2022-10-26T01:18:40.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-26T02:15:35.000Z (over 3 years ago)
- Last Synced: 2025-02-17T09:43:35.544Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 85 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: readme.MD
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README
# *Salve munde*: Philology at the Command Line (or an “exploratory” approach to Latin)
*Written by [diyclassics](https://diyclassics.github.io). Last updated 10.25.2022.*
This repo contains notebooks for an workshop at Trinity University on 10.27.2022 on learning to explore Latin text with Python
These notebooks can be run in Binder (all data/models already available) here:
[](https://mybinder.org/v2/gh/diyclassics/exploratory-philology-trinity/HEAD?labpath=notebooks)
## Description
Where should Latinists get started with computational analysis of literary texts? Which programming language? Which formats? Which tools? In this talk, discussing my latest project Exploratory Philology, I argue that the place to start is with the (digitized) texts themselves. Building on Nick Montfort’s exploratory paradigm of learning “how to think with computation” in the humanities, I show how working through a series of constrained philological problems—anything from counting color terms to searching for acrostics to generating random text—can at the same time help us use code to learn about the languages and to use the languages to help us learn to code. The workshop will give participants (no prior experience necessary!) the opportunity to read, write, and revise Python scripts to manipulate Latin texts and discover new things about them.
## Links
- [Classical Language Toolkit](https//cltk.org)
- [CLTK Readers](https://github.com/diyclassics/cltk_readers)
- CLTK Tesserae Corpora: [Latin](https://github.com/cltk/lat_text_tesserae) [Greek](https://github.com/cltk/grc_text_tesserae)
## Recommended reading
- Montfort, N. 2021. *Exploratory Programming for the Arts and Humanities*. 2nd edition. Cambridge, MA: MIT Press.
- Rockwell, G., and Sinclair, S. 2016. *Hermeneutica: Computer-Assisted Interpretation in the Humanities*. Cambridge, MA: MIT Press.
## Further reading
- Bengfort, B., Bilbro, R., and Ojeda, T. 2018. *Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning*. Sebastopol, CA: O’Reilly.
- Karsdorp, F., Kestemont, M., and Riddell, A. 2021. *Humanities Data Analysis: Case Studies with Python*. Princeton: Princeton University Press.
- Lane, H., Hapke, H., and Howard, C. 2019. *Natural Language Processing in Action: Understanding, Analyzing, and Generating Text with Python*. Shelter Island, NY: Manning Publications.
- Mattingly, W. 2021. "Latin Natural Language Processing" on YouTube. [https://www.youtube.com/playlist?list=PL2VXyKi-KpYuKYUkf1aODP4vHpOh7yvjr].
- Walsh, M. 2021. *Introduction to Cultural Analytics & Python*. [https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html].