Extremes Are Better: Investigating Mental Map Preservation in Dynamic Graphs

Research on effective algorithms for efficient graph layout continues apace, and faster technology has led to increasing research on algorithms for the depiction of dynamic graphs which represent changing relational information over time. Like the static layout algorithms that preceded these, empirical work lags behind their design, and assumptions are made about how users' comprehension may be enhanced without human data to support them. This paper presents an experiment investigating an existing dynamic layout algorithm, focusing on the effect of the preservation of the mental map on comprehension. The results indicate that extremes produce better performance, suggesting that individual preference may be important.