Digital Humanities at Berkeley Summer Institute: Computational Text Analysis

Scholars across multiple disciplines are finding themselves face-to-face with massive amounts of digitized data. In the humanities and many social science disciplines, this data is often in the form of unstructured text. This course will introduce students to cutting edge ways of structuring and analyzing digitized text-as-data, and will do so by exploring questions fundamental to the humanities. The ultimate goal is to encourage students to think about novel ways they can apply these techniques to their own data and research questions, and to provide the skills necessary to apply the methods in their own research. We will use the open source (and free!) programming language Python. We will also provide demonstration corpora.

Laura K. Nelson
Laura K. Nelson
Assistant Professor of Sociology

I use computational methods to study social movements, culture, gender, institutions, and the history of feminism. I’m particularly interested in developing transparent and reproducible text analysis methods for sociology using open-source tools.