Ulrik Brandes holds a Chair of Information Science at the University of Konstanz. Ulrik is a leading scholar in Social Network Analysis. His research interests are centered on graph drawing and information visualization, efficient graph algorithms and experimental algorithms. He is one of the editors of “Network Science” (Cambridge University Press) and serves as board member of the International Network for Social Network Analysis (INSNA). Currently he is conducting a Reinhart Koselleck project on the algorithmic foundations of network theory, a project in cooperation with the social sciences.
The visualization social networks is a matter of choosing an effective design for the substance of interest. This is a difficult task by itself, but it is further complicated when the data render the design unsuitable. Following a general introduction to social network visualization, we will focus on the special case of networks which exhibit the small-world property. They are notoriously difficult to visualize because the relatively short distances cause most layout algorithms to create hairball-like diagrams. We will discuss an approach to untangle such hairballs by separating cohesive subgroups using the structural embeddedness of ties.