  We investigate static and dynamic topologies of a 2-mode real world
university-industry cooperation network. Due to its large size and complex
structure, we choose to use statistical proxies for this goal. Among the
findings, we shall call attention to the rank-size distribution of the firm
node degrees with power law signature log-linear behavior. Which invokes hints
of a complex network architecture, as a counterpoint to the random case. We
compare furthermore the rank-size distributions of both modes with other
real-world 2-mode large-scale networks and draw parallels for their causes.
Moreover, we investigate structural change in the network by computing
Robins-Alexander clustering coefficients in a rolling window fashion in order
to capture topological change in the network temporal evolution. Findings
suggest that network stability is achieved after a short transition phase of
high clustering and cross-correlation.
