  Graph layout is the process of creating a visual representation of a graph
through a node-link diagram. Node-attribute graphs have additional data stored
on the nodes which describe certain properties of the nodes called attributes.
Typical force-directed representations often produce hairball-like structures
that neither aid in understanding the graph's topology nor the relationship to
its attributes. The aim of this research was to investigate the use of
node-attributes for graph layout in order to improve the analysis process and
to give further insight into the graph over purely topological layouts. In this
article we present graphTPP, a graph based extension to targeted projection
pursuit (TPP) --- an interactive, linear, dimension reduction technique --- as
a method for graph layout and subsequent further analysis. TPP allows users to
control the projection and is optimised for clustering. Three case studies were
conducted in the areas of influence graphs, network security, and citation
networks. In each case graphTPP was shown to outperform standard force-directed
techniques and even other dimension reduction methods in terms of clarity of
clustered structure in the layout, the association between the structure and
the attributes and the insights elicited in each domain area.

Graphics;Social and Information Networks