Научно-исследовательский семинар

Бакалавриат 2023/2024

Статус: Курс обязательный (Политология и мировая политика)

Направление: 41.03.04. Политология

Кто читает: Департамент политологии и международных отношений

Где читается: Санкт-Петербургская школа социальных наук

Когда читается: 3-й курс, 3 модуль

Формат изучения: без онлайн-курса

Охват аудитории: для своего кампуса

Преподаватели: Аркатов Дмитрий Александрович, Рябов Дмитрий Олегович

Язык: английский

Кредиты: 2

Контактные часы: 20

Full Syllabus

Abstract

The primary aim of the course is to complement other methodological courses by offering a platform for the practice of social science research. Furthermore, a specific part of the course is dedicated to the introduction of case study research designs, methods, and techniques. The course consists of three main parts. The first (sessions 1-3) aims to deepen the students’ conceptual command in certain areas of positivistic research, focusing on epistemology, causality, trade-offs and pitfalls of research, etc. The second part (sessions 4-12) addresses the theory and practice of positivistic case study research. In this regard, the key issues will be: definition of a ‘case’; case selection strategies; comparative case studies; longitudinal case studies; mixed-method research. In the final, third part of the course (sessions 13-20), the students will work with quantitative framework exploring the basics of linear, logistic, and count models. They will discuss the scope and limits of the quantitative methods and apply them to real-world problems. They will also learn how to use R statistical software for data manipulation, visualisation, and statistical analysis.

Learning Objectives

to complement other methodological courses by offering a platform for the practice of social science research
Learn basic methods to analyze data quantitatively
Attain basic concepts and steps of textual analysis

Expected Learning Outcomes

Students are able to use basic methods of computational text mining.
Able to perform data collection and preparation for the analysis using text mining methods
able to formulate coherent research designs
formulates coherent theoretical framework for one's research projects

Course Contents

Discourse analysis as a methodology
Key analytical concepts of discourse analysis
Analysis of the domestic political discourse
Foreign policy discourse analysis
Analysis of the popular discourse
Introduction to text analysis in R: data types, web scraping and text mining
Tidy text format and sentiment analysis with R
TF-IDF approach to text analysis
Relationships between words
Topic modelling in R
Ontology and epistemology of political research
Research questions
Literature review
Theory
Designing empirical research
Peer-review discussion

Assessment Elements

Research Project
In-class Participation
Final Test
In-class participation
Students are expected to attend each seminar and regularly participate in discussions. The instructor grades the participation during the seminars based on the quality of answers, demonstration of engagement with the assigned readings and home tasks, and overall quantitative involvement in the in-class activities.
Home assignments
Students are expected to submit regular home assignments (announced in advance) based on the discussed topics and aimed at helping them to grasp the main concepts and apply them to their research designs.
Revision test
The revision test will consist of multiple-choice and open-ended questions covering the content of the first 5 seminars.
Research proposal
This is an individual written assignment and the main outcome of the research seminar. Students are expected to describe the research design of their future bachelor theses. The expected volume of the paper is 1500 words (+/- 10%), references and footnotes NOT INCLUDED.
methodological exercise
case study presentation
class participation
mid-term exam
quizzes
research paper
class participation
final exam

Interim Assessment

2021/2022 4th module
Attestation was conducted in 2021-2022 a.y. The formula was: 0,4*Written Assignment: Team Literature Review + 0,35*In-сlass Tests + 0,25*Final Assignment
2022/2023 2nd module
0.3 * case study presentation + 0.3 * case study presentation + 0.1 * class participation + 0.1 * class participation + 0.3 * methodological exercise + 0.3 * methodological exercise + 0.3 * mid-term exam + 0.3 * mid-term exam
2022/2023 3rd module
0.5 * 2022/2023 2nd module + 0.5 * 2022/2023 2nd module + 0.05 * class participation + 0.05 * class participation + 0.15 * final exam + 0.15 * final exam + 0.15 * quizzes + 0.15 * quizzes + 0.15 * research paper + 0.15 * research paper
2023/2024 3rd module
0.4 * Final Test + 0.4 * Final Test + 0.2 * In-class Participation + 0.2 * In-class Participation + 0.4 * Research Project + 0.4 * Research Project
2024/2025 2nd module
0.15 * Home assignments + 0.15 * Home assignments + 0.15 * In-class participation + 0.15 * In-class participation + 0.35 * Research proposal + 0.35 * Research proposal + 0.35 * Revision test + 0.35 * Revision test

Bibliography

Recommended Core Bibliography

Silge, J., & Robinson, D. (2017). Text Mining with R : A Tidy Approach (Vol. First edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1533983

Recommended Additional Bibliography

Lappin, S., Fox, C., & Clark, A. (2010). The Handbook of Computational Linguistics and Natural Language Processing. Chichester, West Sussex: Wiley-Blackwell. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=330500

Authors

KABANOV YURIY ANDREEVICH
SEMENOV ANDREY VLADIMIROVICH
RYABOV DMITRIY OLEGOVICH
GAL ANDRASH Андраш
ARKATOV DMITRIY ALEKSANDROVICH
STREMOUKHOV DENIS ALEKSANDROVICH

Course Syllabus