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Regular version of the site
Master 2023/2024

Research Seminar "Computational Social and Network Sciences"

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type: Elective course
Area of studies: Applied Mathematics and Informatics
When: 1 year, 1-4 module
Mode of studies: offline
Open to: students of one campus
Master’s programme: Applied Statistics with Network Analysis
Language: English
ECTS credits: 6
Contact hours: 48

Course Syllabus

Abstract

This research seminar is aimed at supporting the process of academic and industrial research, covering the main research stages, such as topic selection, research design, choice of methodology, data collection, literature review, and results’ presentation. These aspects are discussed from the perspectives of Computational Social and Network Sciences, which allows students to gain a deeper knowledge of the current trends and methodological and theoretical advancements in these fields. Current ideas, problems, and projects in the fields of Network analysis and Computational social sciences are presented at the seminar. The research seminar is aimed at developing and stimulating students' skills of research and publication activity.
Learning Objectives

Learning Objectives

  • • Support the process of Term paper preparation
  • • Prepare the student for independent research work
  • • Develop skills for discussion and objective assessment of scientific research
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to justify the chosen research methodology
  • be able to present research results
  • have written and oral speech within the stated research topic
  • • students can competently organize the process of research work in terms of all necessary stages
  • • students can develop a research design of the project
  • • students can justify the chosen research methodology
  • • students can make a comprehensive literature review
  • • students can present research results in various formats of scientific outcomes (Term paper, presentation, scientific paper)
  • • students have written and oral skills in presenting and discussing various research topics
Course Contents

Course Contents

  • Introduction to Computational Social and Network Sciences
  • Research design in Computational Social and Network Science
  • Starting points of research
  • Literature review
  • Data types
  • Data measurement
  • Data collection
  • Data manipulation
  • Data analysis
Assessment Elements

Assessment Elements

  • blocking Homeworks
  • blocking Final presentation
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.4 * Final presentation + 0.6 * Homeworks
Bibliography

Bibliography

Recommended Core Bibliography

  • Rainer Bauböck, Donatella Della Porta, Ignacio Lago, & Camil Ungureanu. (2012). What methodological “wars” methodological pluralism? Revista Española de Ciencia Política, (29), 11. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.2385852644e540ab804dd172189cabdd

Recommended Additional Bibliography

  • Richard Paul, & Linda Elder. (2019). The Miniature Guide to Critical Thinking Concepts and Tools: Vol. 8th ed. The Foundation for Critical Thinking.
  • Waller, A. (2010). Philosophical Foundations for the Practices of Ecology. Biologist, 57(3), 150.

Authors

  • BOLDYREVA LYUBOV VLADIMIROVNA
  • Klimov Ivan Aleksandrovich