Instructor: Charles Pletcher (@pletcher)
TA: Zoë Spriggs (@zspriggs)
Meeting time: M 6-8:30 p.m.
Location: Miner Hall 112
Office hours: By appointment (cal.com/pletcher)
TA Office Hours: By appointment (cal.com/zspriggs)
Despite the recent proliferation in digital sources for a variety of literary fields and subfields, quantitative textual analysis has often been viewed as anathema to pursuits in the humanities. Rather than set computational and literary methods at odds, this course seeks to reconcile them through careful application of statistical methodologies alongside literary modes of inquiry. Far from a positivistic approach to literary texts, this course will guide students towards enriching their understanding of the texts that they study by taking a “distant reading” approach (cf. Moretti 2000) that complements, rather than supplants, close reading and critical analysis.
This course introduces humanists to the tools and methodologies of quantitative textual analysis through corpus linguistics. Using the Python programming language and interactive Jupyter notebooks, students will learn how to build and evaluate corpora related to their areas of expertise, and they will gain experience with basic statistics and probability theory, hypothesis testing and experiment design, and methods in sociolinguists, stylistics, and diachronic textual analysis. Students will gain substantial practical experience through weekly labs and homework assignments, culminating in a final presentation and paper aimed at publication.
It is reccomended that you use Visual Studio Code (https://visualstudio.microsoft.com/downloads/) for this course. Be sure to scroll down and download Visual Studio Code, not Visual Studio. Once installed, navigate to the left side of the screen and hover over the symbols until you find "Extensions" (it looks like 4 building blocks). Please search for and then install the "Jupyter" extension. Windows users should also install the "WSL" extension.
- Fork the repository.
Since Windows filenames do not allow the : character and URNs include the :, Windows users will need to use Windows Subsystem for Linux (WSL) to work with this repository.
If you have not used WSL before, you will need to install it.
- Open Windows Powershell (this can be done by searching "powershell" in the start menu)
- Run the following command: wsl --install
- Once the install is complete, open your files and navigate to the folder that you'd like to be working in.
- Right click and select "Open in Terminal"
- Once in the terminal, run the following command: wsl
- From here, you can clone the class repository by running the following command: git clone https://github.com/Tufts-2024-Quant-Text-Analysis/intro-text-analysis.git
- Now, you can open the local version of this repository in Visual Studio Code.
Code in Jupyter Notebooks is licensed under the MIT License, or the license of the libraries being used.
Other course materials are licensed under Creative Commons Attribution-Sharealike 4.0 (CC BY-SA 4.0).
See ./LICENSES for the full text of each license.