Humans are connected by various social relations. When aggregated, we speak of social networks. This course discusses how social networks are structured, how they change over time and how they affect the individuals that they connect. It integrates social theory with practical knowledge of cutting-edge statistical methods and applications from a number of scientific disciplines.
The aim is to enable students to contribute to social networks research and to be discriminating consumers of modern literature on social networks. Students will acquire a thorough understanding of social networks theory (1), practical skills in cutting-edge statistical methods (2) and their applications in a number of scientific fields (3). In particular, at the end of the course students will - Know the fundamental theories in social networks research (1) - Understand core concepts of social networks and their relevance in different contexts (1, 3) - Be able to describe and visualize networks data in the R environment (2) - Understand differences regarding analysis and collection of network data and other type of survey data (2) - Know state-of-the-art inferential statistical methods and how they are used in R (2) - Be familiar with the core empirical studies in social networks research (2, 3) - Know how network methods can be employed in a variety of scientific disciplines (3)
Performance assessment information (valid until the course unit is held again)