Evaluation of two interaction techniques for visualization of dynamic graphs
This addresses visualization usability problems for researchers and analysts working with dynamic network data, though it represents an incremental contribution.
The researchers evaluated two interaction techniques for dynamic graph visualization - layout stability adjustment and node/edge highlighting - through a controlled experiment. They found both techniques generally improved accuracy (sometimes with longer completion times), with highlighting outperforming stability adjustment except on the most complex tasks.
Several techniques for visualization of dynamic graphs are based on different spatial arrangements of a temporal sequence of node-link diagrams. Many studies in the literature have investigated the importance of maintaining the user's mental map across this temporal sequence, but usually each layout is considered as a static graph drawing and the effect of user interaction is disregarded. We conducted a task-based controlled experiment to assess the effectiveness of two basic interaction techniques: the adjustment of the layout stability and the highlighting of adjacent nodes and edges. We found that generally both interaction techniques increase accuracy, sometimes at the cost of longer completion times, and that the highlighting outclasses the stability adjustment for many tasks except the most complex ones.