Social scientists are more relevant than ever today. With increasing data availability, advancing technologies, and professionalized research methods, they are uniquely positioned to address complex social, economic, political, and cultural challenges. In times of rapid societal transformation and uncertainty, social scientists have a timely opportunity to shape a future that is inclusive, fair, innovative, sustainable, and prosperous.
Social Network Analysis (SNA) is a powerful, interdisciplinary research framework that maps and measures connectivity in our interconnected world. It identifies key players, the roles of groups and communities, and the flow of information, resources, and influence within networks. By uncovering relational mechanisms and testing network-building and disruption scenarios, SNA supports informed decision-making at personal, organizational, and policy levels.
This course explores the potential and limitations of SNA to drive meaningful change. Through readings and practical applications, you’ll rethink how the world works and grapple with imperfect data and tools. You'll also learn to make research actionable and impactful.
The course integrates SNA with mixed methods to expand analytic depth and practical interpretation, emphasizing data pre-processing and wrangling. Designed for interdisciplinary participants, it combines individual and group work on specific research projects, whether using your data or provided datasets. It covers new perspectives, software, and techniques, fostering a comprehensive understanding of SNA.- Instructor: Silvia Fierascu