Year: 2015
Type: conference-abstract
Abstract: Since the 18th century, the novel has been one of the defining forms of English writing, a mainstay of popular entertainment and academic criticism. Despite its importance, however, there are few computational studies of the large-scale structure of novels—and many popular representations for discourse modeling do not work very well for novelistic texts. This paper describes a high-level representation of plot structure which tracks the frequency of mentions of different characters, topics and emotional words over time. The representation can distinguish with high accuracy between real novels and artificially permuted surrogates; characters are important for eliminating random permutations, while topics are effective at distinguishing beginnings from ends.
Author: Micha Elsner
Institution: The Ohio State University
Language: English
Subfield: Literature and Literary Theory
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: hybrid
Funder: Princeton University
OpenAlex ID: W2219280948