Distant reading, meaning the computational analysis of large text corpora, is a useful method for media studies as well as for literary analysis. In an era where social media platforms are central hubs of public exchanges and generate vast datasets, distant reading enables researchers to uncover patterns, trends, and biases at scale. Distant reading can also help to understand the spread of information across platforms, the formation of digital communities, and the influence of algorithms on public discourse.
At the Faculty of Arts and Social Sciences in Maastricht, we give students in the MA Digital Cultures an introduction to distant reading in our Machines of Knowledge course (DCU4008), using the beginner-friendly NLP suite Voyant Tools. Students are given podcast reviews from the Apple Store, comments from YouTube, and Mastodon posts as sample datasets to analyse power dynamics, cultural shifts, and user behaviours in relation to current societal concerns.
The course Machines of Knowledge at Maastricht University explores the transformation of the World Wide Web from a static information space to a dynamic, user-driven network of knowledge. We examine how content creation, sharing, and delivery have evolved and resulted in new economic, ethical, and legal challenges.
On the theoretical side, students engage with data feminism, postcolonialism, and public sphere theory. Basic skills in computational text analysis are taught in separate sessions and practiced in interactive lectues.
By the end of this course, students are able to:
- Critically analyse the curation, analysis, and preservation of web-based content.
- Harvest and analyse digital data using distant reading / text visualisation tools.
- Apply data feminist, postcolonial, and public sphere frameworks to digital knowledge production.
- Develop technical skills relevant for research and professional careers in media, marketing, and social media.
While this handbook was created for the skills sessions in a particular distant reading course at Maastricht University, the introductions to distant reading, the Voyant Tools workflow, and the case studies can easily be reused in other university courses or support students' self-study at home.
If you want to use this repository as a template to create your own educational resource, you can clone or download all the materials from the code section. Please make sure to credit Monika Barget and Maastricht University Press as initial content creators.
If you need help using this handbook, go to the GitHub repository behind it and feel free t open an issue. You can also contact the course coordinator via email.
- D’Ignazio, C. & Klein, L. (2020). Data Feminism. MIT Press.
- Fuchs, C. et al. (2010). Theoretical foundations of the web: cognition, communication, and co-operation.
- Sinclair, S. & Rockwell, S. (2016). Text Analysis and Visualization: Making Meaning Count.
- Mirowski, P. (2018). The future(s) of open science.
- Peters, M.A. & Besley, T. (2019). Digital archives in the cloud: Collective memory, institutional histories and the politics of information.