  The spatial preferred attachment (SPA) model is a model for networked
information spaces such as domains of the World Wide Web, citation graphs, and
on-line social networks. It uses a metric space to model the hidden attributes
of the vertices. Thus, vertices are elements of a metric space, and link
formation depends on the metric distance between vertices. We show, through
theoretical analysis and simulation, that for graphs formed according to the
SPA model it is possible to infer the metric distance between vertices from the
link structure of the graph. Precisely, the estimate is based on the number of
common neighbours of a pair of vertices, a measure known as {\sl co-citation}.
To be able to calculate this estimate, we derive a precise relation between the
number of common neighbours and metric distance. We also analyze the
distribution of {\sl edge lengths}, where the length of an edge is the metric
distance between its end points. We show that this distribution has three
different regimes, and that the tail of this distribution follows a power law.
