  After the 2016 double dissolution election, the 45th Australian Parliament
was formed. At the time of its swearing in, the Senate of the 45th Australian
Parliament consisted of nine political parties, the largest number in the
history of the Australian Parliament. Due to the breadth of the political
spectrum that the Senate represented, the situation presented an interesting
opportunity for the study of political interactions in the Australian context.
Using publicly available Senate voting data in 2016, we quantitatively analyzed
two aspects of the Senate. Firstly, we analyzed the degree to which each of the
non-government parties of the Senate are pro- or anti-government. Secondly, we
analyzed the degree to which the votes of each of the non-government Senate
parties are in concordance or discordance with one another. We utilized the
fully-visible Boltzmann machine (FVBM) model in order to conduct these
analyses. The FVBM is an artificial neural network that can be viewed as a
multivariate generalization of the Bernoulli distribution. Via a maximum
pseudolikelihood estimation approach, we conducted parameter estimation and
constructed hypotheses test that revealed the interaction structures within the
Australian Senate. The conclusions that we drew are well-supported by external
sources of information.
