I recently see examples of network analyses (such as centrality measures from network/graph theory) being applied on probabilistic graphical models (e.g. Gaussian graphical model) and there is a growing literature in psychology which continues to do the same.
I am reading the Machine learning textbook by Chris Bishop and I was wondering if there's a reason why most textbooks in computer science and mathematics (e.g. Bishop, Murphy, Lauritzen) tend to differentiate between graphical models and network analysis i.e. treat graphical models as multivariate statistical models and not as networks.
Is it just a matter of different perspectives between disciplines (psychology vs computer science/mathematics) or is there a (technical) reason why one should not conduct network analyses on graphical models? Thanks.