Corpus Linguistics: Topic and Dynamic Modeling

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

5

Кредиты

Кто читает:

Департамент иностранных языков

Статус:

Курс обязательный

Когда читается:

2-й курс, 3, 4 модуль

Преподаватель

Горина Ольга Григорьевна

Course Syllabus

Abstract

The course introduces corpus linguistics as a methodology that has transformed the understanding of language in the 20th–21st centuries. The focus is on the shift from intuitive and prescriptive models to empirical, probabilistic analysis of actual language use. Students explore the history and philosophy of the corpus approach and acquire basic methods for identifying systemic language patterns (frequency, collocation, keywords, semantic prosody). The lecture component is built around classical research and established methodology. The seminar component involves independent exploration of current academic literature and emerging research directions (multimodal corpora, corpora and AI, corpus resources for different languages, automation of analysis).

Learning Objectives

• To develop students' fundamental understanding of corpus methodology and their ability to critically evaluate current directions in the field.
• To master key concepts of corpus linguistics.
• To learn how to formulate research questions addressable through corpus methods.
• To develop skills in analysing and interpreting corpus data.
• To build competence in working with academic literature and presenting research findings.
• To assess the role of corpus data in language teaching, translation, lexicography, and contemporary social research.

Expected Learning Outcomes

• Define and apply core terminology
• Formulate a research question and select corpus tools
• Interpret corpus data and identify patterns
• Compare register variation and pragmatic strategies
• Conduct an independent corpus-based study

Course Contents

• MODULE III Introduction. From Intuition to Data.
• History of Corpus Linguistics.
• Corpus Typology.
• Corpus Design Principles.
• The Annotation Problem: From Markup to Interpretation.
• Corpus Managers: Logic of Search and Interpretation.
• Frequency and Zipf's Law.
• Concordance and Collocation. Lexico-grammatical Profiling.
• Semantic Prosody: From Word to Context.
• Keywords.
• Clusters (N-grams, Lexical Bundles).
• MODULE IV Corpora in Language Teaching: Data-Driven Learning.
• Corpus methods applied to various linguistic phenomena.
• Corpus Resources Across Languages.
• Applied Cases: Corpus and Lexicography.
• From N-grams to Embeddings.
• Modern Corpus Managers: From SARA to Intelligent Platforms.
• Ethics in Corpus Research and New Data Types.
• Closing Discussion: Corpus Linguistics in the Age of AI.

Assessment Elements

• Tests and Quizzes
• Attendance
• Seminar /Lecture Participation and Homework
• Module 3 Project: Term Project
• Module 4 Project: Research Project

Interim Assessment

• 2026/2027 4th module
  0.2 * Seminar /Lecture Participation and Homework + 0.3 * Module 3 Project: Term Project + 0.1 * Attendance + 0.3 * Module 4 Project: Research Project + 0.1 * Tests and Quizzes

Bibliography

Recommended Core Bibliography

• 9789027268716 - Boulton, Alex; Lenko-Szymanska, Agnieszka - Multiple Affordances of Language Corpora for Data-driven Learning - 2015 - John Benjamins Publishing Company - http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=987719 - nlebk - 987719
• A mosaic of corpus linguistics : selected approaches, , 2010
• McEnery, T., & Hardie, A. (2012). Corpus Linguistics : Method, Theory and Practice. Cambridge: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=408835

Recommended Additional Bibliography

• Corpora in applied linguistics : current approaches, , 2016
• New trends in corpora and language learning, , 2012

Authors

• GORINA OLGA GRIGOREVNA
• Ursul Natalia Valerevna