Worldwide bilateral geopolitical interactions network inferred from national disciplinary profiles

A disciplinary profile of a country is defined as the versor whose components are number papers produced in given discipline divided by overall production country. Starting from Essential Science Indicators (ESI) schema classification subject areas, we obtained yearly profiles worldwide graph, where on each node sits country, two time intervals 1988--1988 and 1992--2017, fall Berlin Wall being watershed. We analyze empirical pairwise cross-correlation matrices series profiles. The contrast with random matrix theory proves that, beyond measurement noise, bring genuine information. Arising Shannon theorem least-structured model consistent measured correlations, stationary probability distribution can be described Boltzmann related to generalized ${n}_{d}$-dimensional Heisenberg model. set network interactions has been inferred it, clusterization methods, hierarchical clustering, principal component analysis have applied. This allows obtaining characterization bilateral based physical modeling. simple geopolitical reveals consistency results gives boost deeper historical analysis. In order obtain optimal interactions, used pseudolikelihood approach. analytically computed its gradient. analytical computations deserve interest whatever inference Bayesian problem involving an