Master
2024/2025
Research Seminar "Computational Social and Network Sciences"
Type:
Compulsory course (Data Analytics and Social Statistics)
Area of studies:
Applied Mathematics and Informatics
Delivered by:
International Laboratory for Applied Network Research
Where:
Faculty of Social Sciences
When:
1 year, 1-4 module
Mode of studies:
offline
Open to:
students of one campus
Master’s programme:
Аналитика данных и прикладная статистика
Language:
English
ECTS credits:
6
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
- • 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
- 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
- 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
- Data visualization
- Results presentation
- Workshop on writing academic articles and submissions to scientific conferences
Assessment Elements
- Homeworks
- Final testFinal test on the materials of the course, open-ended questions may be included
Interim Assessment
- 2024/2025 4th module0.2 * Final test + 0.32 * Homeworks + 0.16 * Homeworks + 0.16 * Homeworks + 0.16 * Homeworks
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.