Summer Timetable

POL2578H1F L0101

Topics in Methods

Computer-Assisted Textual Analysis

Themes

This course introduces graduate students to the state of the art in the field of computer-assisted textual analysis. The course includes an introduction to the Python programming language and seeks to achieve a balance between theory, concrete applications and lab exercises. We cover a wide range of methods, from basic statistics to advanced notions in natural language processing. In particular, the course features an introduction to machine learning and topic modelling (e.g. Latent Dirichlet Allocation), with illustrations based on real-world political corpora. By the end of this course, graduate students should be able to apply a variety of tools for textual analysis in their own research.

Texts

TBA

Format and Requirements

Familiarity with statistics (at the level of POL 2504 or equivalent) is strongly recommended for this course.