  Knowledge networks have become increasingly important as a changing
repository of data which can be represented, studied and modeled by using
complex networks concepts and methodologies. Here we report a study of
knowledge networks corresponding to the areas of Physics and Theology, obtained
from the Wikipedia and taken at two different dates separated by 4 years. The
respective two versions of these networks were characterized in terms of their
respective cross-relation signatures, being summarized in terms of modification
indices obtained for each of the nodes that are preserved among the two
versions. The proposed methodology is first evaluated on Erdos-Renyi (ER) and
Barabasi-Albert model (BA) networks, before being tested on the knowledge
networks obtained from the Wikipedia respectively to the areas of Physics and
Theology. In the former study, it has been observed that the nodes at the core
and periphery of both types of theoretical models yielded similar modification
indices within these two groups of nodes, but with distinct values when taken
across these two groups. The study of the Physics and Theology networks
indicated that these two networks have signatures respectively similar to those
of the BA and ER models, as well as that higher modification values being
obtained for the periphery nodes, as compared to the respective core nodes.
