Master
2025/2026
Working with Network Data
Type:
Compulsory course (Data Analytics and Social Statistics)
Delivered by:
International Laboratory for Applied Network Research
When:
2 year, 1-3 module
Open to:
students of one campus
Language:
English
Contact hours:
36
Course Syllabus
Abstract
This research seminar provides a comprehensive introduction to the methodologies and tools for working with network data in social sciences. The course covers the entire research cycle, from design to analysis and visualization, with a focus on the unique aspects of network-based research. Participants will explore fundamental network concepts, different types of network data, and methods for data collection, including surveys and qualitative approaches.
Key topics include data preparation, handling missing data, and applying social network analysis (SNA) techniques to derive meaningful insights. The course also emphasizes best practices for network data visualization and introduces popular SNA software tools. Ethical considerations in network research are addressed to ensure responsible conduct.
Designed for researchers and students, this seminar combines theoretical foundations with practical applications, equipping participants with the skills to design, execute, and interpret network-based studies effectively. By the end of the course, attendees will be proficient in leveraging network analysis to address complex research questions in social sciences.
Learning Objectives
- The aim of the Research seminar is to equip students with the skills to collect, prepare, analyze, and visualize network data, as well as to apply social network analysis (SNA) methods for addressing research questions in the social sciences. The course aims to develop a comprehensive understanding of network-based research design, ethical considerations, and practical tools for data-driven insights.
Expected Learning Outcomes
- Be able to develop and/or foster critical reviewing skills of published empirical research using applied statistical methods.
- Have basic academic writing skills in both English and Russian.
- Have oral presentation skills.
- Know the most recent advances in network science and applied statistics.
- Be able to understand the basic steps of the research process.
- Know the requirements and guidelines of scientific publishing both in Russia and abroad.
- Know topics, terminology, and principles of scientific research methods.
- Be able to to criticize constructively and determine existing issues with applied linear models in published work.
Course Contents
- Research design in social sciences
- Network-based research design
- Types of network data
- Network data collection
- Network data preparation
- Network data analysis
- Network data visualization
- SNA software
- Ethics and integrity in network-based research
Assessment Elements
- Final ProjectSome requirements: • The project is implemented individually. • This final project is 0.5 of your final grade. • The main aim of the project is not (just) to provide the results, but to show how well you can work with network data, providing reflection on the main stages of the project’s implementation. • Basically, you need to put together a set of homework assignments that you implemented during the course, taking into account the feedback you received. • You will need to work with a network dataset (either primary data collected by yourself or secondary data taken from any repository). You can work with the same dataset that you used during the class. • The project should be implemented in the form of a written report, formatted according to the general standards. If the project is not formatted accordingly, we can reduce the grade to -1 point of the final grade. Description of the Final project: 1. Research area. Write an introduction describing your research interests in network analysis. Please provide a shot literature review on the topic and discuss some papers which you find relevant to this research area. Provide some general information on these papers (methodology, some particularities in sense of analysis) and write why you regard them as valuable for your topic. 2. Research question. Based on this topic you have chosen, write certain research questions that you have chosen in this project to be studied with network analysis. 3. Research design. Draw up a research design for the study dealing with the questions you came up with. Make a conclusion about the most suitable type (types) of networks for your study, and explain your choice. 4. Data and methodology. Provide information about the source of the data. • Describe how the data were collected and preprocessed, and how network file was created. Please reflect on whether the data is reliable and valid. • Describe the resulted network: what are the nodes, links, and their attributes. Write in which formats this information is stored. Describe the files numerically: how many nodes, links, and attributes you have. 5. Data analysis. Describe the general strategy of your data analysis. Then: 1. Provide Exploratory analysis for your data: o Visualize the whole network, or the most important part(s) of network, which can help you to describe the network, or to create some hypotheses. o Compute basic statistics (e.g. degree distribution, degree correlation, clustering coefficient, path length distribution, etc.) 2. Provide Confirmatory analysis grounded on specific, pre-existing hypotheses or theories (if any for your research): o Compute network characteristics and make their interpretation: such as centrality (degree, closeness, betweenness, etc.), clustering coefficient, homophily coefficient, average distance, diameter, and other characteristics applicable to your research. 6. Network visualization. Provide a visualization of the network, or most important part(s) of network, considering the requirements for “nice” network visualizations. Write, why you consider this visualization as a good example of network data image. 7. Conclusions. Write the main findings of your network data analysis. 8. Ethical issues. Describe possible ethical or integrity violations that might occur during your research and describe the ways you used to prevent them. 9. Reflection. Provide information on the type of software you use at all stages of your study. Make a reflection on any difficulties you encountered on different stages of your study.
- Homeworks8 consecutive homeworks on the materials of the research seminar
Bibliography
Recommended Core Bibliography
- Doing social network research : network-based research design for social scientists, Robins, G., 2015
- Nooy, W. de, Batagelj, V., & Mrvar, A. (2011). Exploratory Social Network Analysis with Pajek: Vol. Rev. and expanded 2nd ed. Cambridge University Press.
- Nooy, W. de, Mrvar, A., & Batagelj, V. (2005). Exploratory Social Network Analysis with Pajek. New York: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=138973
- Research methods in social relations, Hoyle, R. H., 2002
- The SAGE Handbook of Social Network Analysis, , 2011
Recommended Additional Bibliography
- Brewerton, P., & Millward, L. (2001). Organizational Research Methods : A Guide for Students and Researchers. London: SAGE Publications Ltd. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=251199
- Bryman, A. (1989). Research Methods and Organization Studies. London: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=97175
- Maruyama, G., & Ryan, C. S. (2014). Research Methods in Social Relations (Vol. 8th ed). Malden, Mass: Wiley-Blackwell. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=798826
- Sword, H. (2012). Stylish Academic Writing. Cambridge, Mass: Harvard University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=464125