Do Boxes Affect Exploration Behavior and Performance in Group-in-a-box Layouts?

TL;DR

This study empirically examines how box size in group-in-a-box layouts influences user performance and attention, providing guidance for effective visualization design.

Contribution

It offers empirical evidence on the impact of box size on task accuracy and eye movements in GIB layouts, informing better design choices.

Findings

Box size significantly affects task accuracy.

Participants focus on internal edges rather than box size.

Eye-tracking shows attention on edges, not boxes.

Abstract

The group-in-a-box (GIB) layout is an efficient graph drawing method designed to visualize the group structure of graphs. The layout communicates group sizes and both within-group and between-group network structures simultaneously. The layout is characterized by its composition of multiple elements, including nodes, edges, and boxes. However, there is limited empirical guidance on how these elements should be combined. In this paper, we measured participants' task performance and eye movements while identifying the group with the largest number of internal edges. We investigated the effect of visualization elements on task performance while controlling the density of internal edges and the box size. The results revealed that the box size in a GIB layout significantly affects the task accuracy either positively or negatively while eye-tracking data suggests that participants focused on internal edges, not the box size. These findings contribute empirical guidance for GIB layout design and lay the groundwork for future research as GIB layout becomes more widely used.