Магистратура
2025/2026
Научно-исследовательский семинар "Вычислительные социальные и сетевые науки"
Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус:
Курс обязательный (Аналитика данных и прикладная статистика / Data Analytics and Social Statistics)
Когда читается:
1-й курс, 1-4 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
6
Контактные часы:
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
- To familiarize students with the key concepts, theories, and principles of computational social science and network analysis, and to situate them within the broader logic of social research.
- To develop students' ability to design an empirical study — to formulate a research problem, questions, and hypotheses, operationalize key concepts, and select and justify appropriate computational and network methods and data sources.
- To develop practical skills for conducting an independent study — collecting, analyzing, and visualizing social and network data, interpreting results critically (including the responsible and reflective use of AI tools), and presenting findings in academic form as a course paper and a draft research article.
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
- Final testFinal test on the materials of the course, open-ended questions may be included
- Homeworks
Bibliography
Recommended Core Bibliography
- Doing social network research : network-based research design for social scientists, Robins, G., 2015
- Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., … Van Alstyne, M. (2009). Computational Social Science. Science, 323(5915), 721–723. https://doi.org/10.1126/science.1167742
- Social science research : principles, methods, and practices, Bhattacherjee, A., 2012
Recommended Additional Bibliography
- Computational social science : discovery and prediction, Alvarez, R. M., 2016
- Network science, Barabasi, A.-L., 2019