Evaluation of two interaction techniques for visualization of dynamic graphs

TL;DR

This study evaluates two interaction techniques for dynamic graph visualization, showing that highlighting improves accuracy for most tasks, while layout stability adjustment can increase accuracy but may also increase task completion time.

Contribution

It provides empirical evidence on the effectiveness of interaction techniques in dynamic graph visualization, highlighting their impact on user accuracy and task performance.

Findings

Highlighting enhances accuracy for most tasks.

Layout stability adjustment can improve accuracy but may increase completion time.

Highlighting outperforms stability adjustment for many but not all tasks.

Abstract

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.