This is an activity course augmenting the topical project seminar 851-0586-03 Applied Network Science with a research paper that combines the discussion of a result from the literature with work of their own (as conducted in the associated project seminar). Papers are cross-reviewed and revised before their final submission.

We study applications of network science methods, this time in the domain of social media.Topics are selected for diversity in research questions and techniques.Student teams present results from the recent literature, possibly with replication, in a mini-conference at the end of the lecture period.

This colloquium offers an opportunity to discuss recent and ongoing research and scientific ideas in the behavioral sciences, both at the micro- and macro-levels of cognitive, behavioral and social science.The colloquium features invited presentations from internal and external researchers as well as presentations of doctoral students close to submitting their dissertation research plan.

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.

Network science is a distinct domain of data science that is characterized by a specific kind of data being studied.While areas of application range from archaeology to zoology, we concern ourselves with social networks for the most part.Emphasis is placed on descriptive and analytic approaches rather than theorizing, modeling, or data collection.

Study project involving network data in a selected field.

Soccer analytics refers to the use of data in tactical decision-making, recruitment, strategic planning, and fan engagement in association football. This course is first and foremost about data, problems, and methods. They are discussed, however, with reference to the broader context of measurement and data science in sports and society.

If you can't measure it, you can't manage it. Explorations into mathematical foundations and societal implications of measuring humans, processes, and things in an increasingly datafied world.