This book explores the ways in which computational techniques for text mining can contribute to the history of ideas. Traditional approaches to intellectual history are based on the careful, close scrutiny of texts and contexts, reading at a human scale in order to construct lines of transmission and genealogies of ideas. These approaches have served us well: the history of political thought, for example, has established deeply researched canons of texts and writers that are widely accepted as being in dialogue with each other. Over the last twenty years, however, the migration of analogue archives to digital corpora has opened up the possibility of reading at scale, creating the conditions for inspecting the transmission of ideas across hundreds of thousands of texts. Most of these texts have been deemed too obscure or insignificant for sustained close attention, and they remain at the outer margins of our standard histories of ideas.