We combine unsupervised machine learning and econometric methods to study England’s print culture in the pivotal sixteenth and seventeenth centuries. Machine learning synthesizes the content of 57,863 texts comprising 83 million words into 110 topics. Topics include the expected, such as Natural Philosophy, and the unexpected, such as Baconian Theology. Timelines suggest that religious and political discourse gradually became less antagonistic and economic topics more prominent.