Bachelor 2024/2025

Research Seminar

Type: Compulsory course (Political Science and World Politics)

Area of studies: Political Science

Delivered by: Department of Political Science and International Affairs

Where: Saint-Petersburg School of Social Sciences

When: 4 year, 1-3 module

Mode of studies: offline

Open to: students of one campus

Instructors: Denis Stremoukhov

Language: English

ECTS credits: 2

Course 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

• 9781491981627 - Silge, Julia; Robinson, David - Text Mining with R : A Tidy Approach - 2017 - O'Reilly Media - http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1533983 - nlebk - 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

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