Across the humanities and social sciences, scholars increasingly use
quantitative methods to study textual data. Considered together, this
research represents an extraordinary event in the long history of
textuality. More or less all at once, the corpus has emerged as a
major genre of cultural and scientific knowledge. In Literary
Mathematics, Michael Gavin grapples with this development, describing
how quantitative methods for the study of textual data offer powerful
tools for historical inquiry and sometimes unexpected perspectives on
theoretical issues of concern to literary studies.
Student-friendly and accessible, the book advances this argument through
case studies drawn from the Early English Books Online corpus. Gavin
shows how a copublication network of printers and authors reveals an
uncannily accurate picture of historical periodization; that a
vector-space semantic model parses historical concepts in incredibly
fine detail; and that a geospatial analysis of early modern discourse
offers a surprising panoramic glimpse into the period's notion of world
geography. Across these case studies, Gavin challenges readers to
consider why corpus-based methods work so effectively and asks whether
the successes of formal modeling ought to inspire humanists to
reconsider fundamental theoretical assumptions about textuality and
meaning. As Gavin reveals, by embracing the expressive power of
mathematics, scholars can add new dimensions to digital humanities
research and find new connections with the social sciences.