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Regular version of the site

Research Seminar

2023/2024
Academic Year
ENG
Instruction in English
2
ECTS credits
Course type:
Compulsory course
When:
3 year, 3 module

Instructors

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

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

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
Course Contents

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
Assessment Elements

Assessment Elements

  • non-blocking Research Project
  • non-blocking In-class Participation
  • non-blocking Final Test
Interim Assessment

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
    Participation in the third block of the course is dependent on the successful completion of the mid-term exam; in this regard, GMT shall be at least 4 (‘satisfactory’). In case a student fails to gain at least a ‘satisfactory’ grade, one exam retake is provided.
  • 2022/2023 3rd module
    last year student have got their grades
  • 2023/2024 3rd module
    0.34 * Final Test + 0.33 * In-class Participation + 0.33 * Research Project
  • 2024/2025 2nd module
    According to the corressponding year's interim assessment elements
Bibliography

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