Here’s a new journal article from Peter Turchin and his Seshat database to empirically test hypotheses about history.
In particular, what propels innovation and diffusion of military technologies, details of which are comparatively well preserved and which are often seen as drivers of broad socio-cultural processes? Here we analyze the evolution of key military technologies in a sample of pre-industrial societies world-wide covering almost 10,000 years of history using Seshat: Global History Databank. We empirically test previously speculative theories that proposed world population size, connectivity between geographical areas of innovation and adoption, and critical enabling technological advances, such as iron metallurgy and horse riding, as central drivers of military technological evolution. We find that all of these factors are strong predictors of change in military technology, whereas state-level factors such as polity population, territorial size, or governance sophistication play no major role. We discuss how our approach can be extended to explore technological change more generally, and how our results carry important ramifications for understanding major drivers of evolution of social complexity.
PLOS One
Glancing through the methods confirms my suspicion that big data or machine learning analyses pretty much start from old-school correlation and regression, then branch out (sometimes literally in things called “trees”) from there.