DASS and ANR-Lab launched a Magolego course on social networks in R for graduate students
The Data Analytics and Social Statistics (DASS) educational programme and the International Laboratory for Applied Network Research, with support from HSE Online, have launched an English-language course in the Magolego module, "Social Network Analysis with R." The course focuses on network analysis methodology in R and is open to both DASS students and other HSE Master's students.
The course developer and instructor is Stanislav Pashkov, associate professor of the Department of Economic Sociology and research fellow.
This course was developed specifically for the Master's program "Data Analytics and Applied Statistics," but following a pilot, registration is now open to other students in HSE's Master's programs. Nearly 50 students have enrolled in the course, representing various programs, including "Business Analytics and Big Data Systems," "Marketing: Digital Technologies and Marketing Communications," "Public Sociology and Digital Analytics," "Systems and Software Engineering," "Comparative Social Research," "Foreign Languages and Intercultural Communication," "Applied Political Science," and others. Students will immerse themselves in the world of network analysis, from the fundamental concepts of graph theory to the application of advanced methods in social science. They will learn to confidently work with network data in R, create network visualizations, and calculate key metrics using the igraph package. Upon completion of the course, graduates will be able to independently conduct a full analysis cycle, from data collection to interpretation of results. Classes are held in a convenient online format on the SmartLMS platform, with support for live seminars for in-depth coverage of topics.
Academic Director of the educational program "Data Analytics and Social Statistics" and Deputy Head of the International Laboratory of Applied Network Research
As a laboratory and educational program, our mission is to actively promote and make accessible modern applied network analysis methodology. The launch of this course is an important step in implementing our strategy. Our laboratory is actively developing educational products in network analysis (master's courses, continuing education programs, open intensive courses, and workshops). The network analysis course in R is one such product. Since our online master's program is offered in English, we developed this course in English. We are currently collaborating with HSE Online to create a Russian-language course, "Introduction to Network Analysis," which will be aimed at a wide range of users without programming knowledge and will be available next year to students, including those outside HSE, who wish to master this discipline in Russian.