Бакалавриат
2026/2027
Научно-исследовательский семинар "Подготовка и написание курсовой работы"
ID 912376
Статус:
Курс обязательный (Международная программа «Международные отношения и глобальные исследования»)
Кто читает:
Факультет мировой экономики и мировой политики
Где читается:
Факультет мировой экономики и мировой политики
Когда читается:
3-й курс, 1-3 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Контактные часы:
36
Course Syllabus
Abstract
Discourse Analysis: During this course, students will become familiar with the discourse theories of Ernesto Laclau and Chantal Mouffe, Nico Carpentier, Norman Fairclough, Teun A. van Dijk, as well as with Robert Entman's theory of media framing. They will also explore key analytical methods based on these theories and learn how to apply them in practice;
Quantitative Text Analysis: The course is organised around three main families of approaches: frequency and dictionary-based analysis, sentiment, stance and text classification and thematic analysis. Students also receive a practical introduction to Google Colab and Python Jupiter for basic operations with textual datasets and use generative AI for supervised text annotation and classification. The component concludes with the design and discussion of a small independent research project based on textual data;
Quantitative studies, regressions: The course is organised around three main families of approaches: frequency and dictionary-based analysis, sentiment, stance and text classification and thematic analysis. Students also receive a practical introduction to Google Colab and Python Jupiter for basic operations with textual datasets and use generative AI for supervised text annotation and classification. The component concludes with the design and discussion of a small independent research project based on textual data;
Quantitative studies, regressions: the course will consider machine learning techniques that could be used for academic research on key issues in international relations and public policy, including decision trees, gradient boosting, neural networks, etc. The course will also offer ready-made AI tools, developed using machine learning methods and neural networks, to collect and analyse relevant literature.