Evaluation of a novel visualization for dynamic social networks

Adding temporal information to social network visualizations is still a challenging task despite previous research efforts. The dimension time is of great interest to analysts as it offers insights into various trends and patterns such as changing relationships between different actors or economic opportunities for businesses. Yet current approaches suffer from limitations that can be improved with the visualization design presented in this work. The visualization was developed considering aesthetic criteria and characteristics of adjacency matrices and node-link diagrams. In a formative evaluation process an artificial dataset was specifically created to examine dynamic social networks. A qualitative user study with observation and think-aloud protocols was conducted and analyzed with regard to the user's strategies, limitations of the visualization and potential additional features. The visualization appears to be suitable for all of the evaluated network tasks, however, path-related tasks were more challenging similar to the characteristics of matrix-based representations.