Human Perception of Laid-Out Graphs
Combinatorial graphs are increasingly used for information presentation. They provide high information density and intuitive display of multiple relationships, while offering low cost because they can be created algorithmically. Essential to algorithmic graph layout is a set of rules that encode layout objectives. How these rules are related to inferences drawn from the graph by human observers is a largely unexplored issue. Thus, success or failure by algorithmic standards is only uncertainly related to perceptual effectiveness of the resulting layout. Human experimentation is the only way to correct this deficiency.
This poster describes empirical research conducted in 1994. Forty-six respondents, separated into naive and computer-aware groups, freely viewed a collection of graph layouts, providing semantic conclusions they reached on the basis of the layout, in the absence of any semantic attribution to nodes in themselves. We were interested in two questions. First, are semantic attributions consistent or random? If the former semantic objectives must be considered when creating layout rules or objective functions for automated graph layout. Second, if consistent semantic attributions exist, what are they? The remaining paragraphs of this abstract describe our results and conclusions.
Most importantly, all our observers agreed strongly as to the semantic content of specific graph layouts. There was no difference in interpretation between the group consisting of experienced programmers, and the group who had little exposure to computers. We were interested in possible differences because combinatorial graphs are extremely common in computer science curriculum material, and it’s possible that a group of programmers might agree because they had been exposed to a common set of layout conventions. The agreement between our two groups demonstrates that semantic conventions extend widely.