Bachelor 2025/2026

Computational Methods for Text Analysis

Type: Elective course (Sociology and Social Informatics)

Delivered by: Department of Sociology

When: 3 year, 1, 2 module

Open to: students of all HSE University campuses

Instructors: Yaroslav Snarski

Language: English

Course Syllabus

Abstract

For social science research, written text provide essential data for studying media and political discourse, ideology, conflict, sentiment and political affiliation and many other things. With a growing availability of larger digital collections of texts it is tempting to scale the research up in terms of the population studied (e.g. “all social media users of a town”), time spans (e.g. “all of the Post-Soviet history”), and geographical scope (e.g. “all educational migration in Russia”). Computational methods for text analysis are expected to help where traditional content analysis is not feasible. During the course we will cover basic word statistics, various exploratory methods, supervised and unsupervised modeling of text phenomena. Data Culture level (0.2.2 — Basic level: Programming + Data Analysis) will be achieved through studying methods of preprocessing and transformation of text data, as well as supervised and unsupervised methods of text analysis, such as topic modeling, classification, semantic analysis.