Macroanalysis: Digital Methods and Literary HistoryIn this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections. |
Common terms and phrases
accuracy algorithm analysis approach assignments Austen author gender authorship Bildungsroman British novel chapter chronological plotting chunks classes classifier close reading cluster context corpus correlation data set decade Dickens digital humanities distance employed ethnic evidence example explore fact female authors Figure Franco Moretti genre signals Google Gothic Gothic novel graph identify immigrants industrial novels influence interpretation Ireland Irish American Irish American fiction Irish American literature Irish authors Irish novels Jane Austen KWIC labeled lexical richness linguistic literary history Literary Lab literary scholars literary studies machine macro macroanalysis male mean Melville metadata methods Moby Dick Moretti Newgate novel Ngram Ngram Viewer nineteenth-century novel titles novelistic outliers p-value percent pronouns prose provides readers relative frequency sample Sense and Sensibility silver-fork similar specific style stylometry text mining text segment text-analysis theme tion topic modeling tradition trends usage words writers