Interactive Visualization of Dynamic Social Networks

Understanding patterns and structural changes in an evolving social network at first glance and performing hands-on exploration of actors’ relationships and attributes are the primary goals of the dynamic social network visualizer “DySoN” (Dynamic Social Networks) presented in this work. A lot of work has been done over the past few years to find visual metaphors for changes in network structures, partly showing how streaming event data of social interactions could be visualized by an interactive three-dimensional model of interpolated ”tubes”, representing dynamic social proximity within a given set of actors during a given time period by using three dimensions of temporal information mapping: spatial density, color and size. Using the example of a collaboration network of musicians, “DySoN” takes event data and additional actor attributes from a relational database, calculates a virtual sociomatrix with proximity relations from it, builds a temporal graph object, applies a forcedirected graph layout method and constructs a NURBS model which is then displayed as Java3D geometry, complemented by a two-dimensional section view and a filterable table view of actors and attributes. 1 Motivation & Objectives Everybody has an idea of dynamic social structure, at least unconsciously, because some of the mechanisms that organize mankind into groups and hierarchies can be observed in real life when people form patterns with their bodies while interacting socially. In order to get an abstract view of relationships and their instantiations between actors in a social network, one can build upon these ”physical patterns” which may be measured and modeled mathematically, especially when considering mobile interaction schemes with communityor social network platforms [Gro05]. Besides such physical expressions of social relations a wealth of other highly dynamical features or indicators of social relations exist that may be modeled (see section 2). One of the most basic awareness class service which can be built upon such a dynamic social network model is a visualization which allows to intuitively recognize social distance and group structures. As the structure of social communities is subject to continuous changes, there is a clear demand for methods and software tools, that are able to analyze and visualize the evolution of networks [MMBd05, p. 1208ff]. Limited by visual and geometric constraints, a few basic metaphors for temporal or dynamic graphs and net-