Corpus Linguistics: Topic and Dynamic Modeling

2026/2027

Academic Year

ENG

Instruction in English

5

ECTS credits

Delivered at:

Department of Foreign Languages

Course type:

Compulsory course

When:

2 year, 3, 4 module

Instructor

Gorina, Olga G.

Course Syllabus

Abstract

The course includes both theoretical and practical components, utilizing software tools for corpus and topic analysis. This course focuses on the study of corpus linguistics methods and topic/dynamic modeling of texts in the English language. The main research areas include corpus linguistics methods such as building and analyzing linguistic text corpora, extracting and processing lexical-grammatical characteristics of texts, applying statistical methods to identify patterns in corpora. Specifically, topic modeling covers identifying latent topical structures in large text collections, using machine learning methods (e.g., lda) for topic-based clustering and interpreting and visualizing topic models. Dynamic Modeling includes : analyzing changes in topical structures over time; identifying trends and evolution of topics in dynamic text collections; applying time series analysis methods to study the development of topical fields. The course is part of the major block and is delivered in person (offline). The prerequisite - Programming Languages for Natural Language Processing (in Russian), the postrequisite – Programming (Python).