Demography of Literary Form: Probabilistic Models for Literary History

<p>Digitization of library collections has made millions of books, newspapers, and academic journal articles accessible. These resources present an opportunity for historians interested in identifying patterns in cultural production that emerge over the space of decades or even centuries. For...

Full description

Bibliographic Details
Main Author: Riddell, Allen
Other Authors: Hayles, Katherine
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10161/7210
id ndltd-DUKE-oai-dukespace.lib.duke.edu-10161-7210
record_format oai_dc
spelling ndltd-DUKE-oai-dukespace.lib.duke.edu-10161-72102013-11-10T03:30:19ZDemography of Literary Form: Probabilistic Models for Literary HistoryRiddell, AllenLiteratureSociologyHistory<p>Digitization of library collections has made millions of books, newspapers, and academic journal articles accessible. These resources present an opportunity for historians interested in identifying patterns in cultural production that emerge over the space of decades or even centuries. For example, considerable interest has been expressed in studying the emergence, decline, and transmission across national and linguistic boundaries of literary form in the tens of thousands of novels published in Europe in the eighteenth and nineteenth centuries. Navigating such a large collection of texts, however, requires the use of quantitative methods rarely used in literary studies; the single, direct reading of even a thousand texts exceeds the time and resources available to most historians.</p><p>This dissertation demonstrates the application of probabilistic model of texts in the study of literary history. The major finding of the dissertation is that regularities previously identified by literary historians can be captured by probabilistic models. Following the first chapter, "How to Read 22,198 Journal Articles: Studying the History of German Studies Using Topic Models," which introduces representations of texts used in the dissertation, chapter 3, "Inferring Novelistic Genre in the English Novel, 1800-1836," and chapter 4, "Networks of Literary Production," illustrate the contribution probabilistic models of novelistic production are positioned to make to long-standing questions in literary history. Both chapters are concerned with the detection and description of empirical regularities in surviving nineteenth-century English novels, such as the recurrence of novelistic genres--e.g., gothic, silver fork, and national tale novels. Chapter 3 makes use of a corpus that includes a random sample of novels published in the British Isles between 1800 and 1836. The use of a random sample and of probabilistic methods, both uncommon in literary studies, serves to develop new conceptual resources for future work in literary history and the sociology of literature.</p>DissertationHayles, Katherine2013Dissertationhttp://hdl.handle.net/10161/7210
collection NDLTD
sources NDLTD
topic Literature
Sociology
History
spellingShingle Literature
Sociology
History
Riddell, Allen
Demography of Literary Form: Probabilistic Models for Literary History
description <p>Digitization of library collections has made millions of books, newspapers, and academic journal articles accessible. These resources present an opportunity for historians interested in identifying patterns in cultural production that emerge over the space of decades or even centuries. For example, considerable interest has been expressed in studying the emergence, decline, and transmission across national and linguistic boundaries of literary form in the tens of thousands of novels published in Europe in the eighteenth and nineteenth centuries. Navigating such a large collection of texts, however, requires the use of quantitative methods rarely used in literary studies; the single, direct reading of even a thousand texts exceeds the time and resources available to most historians.</p><p>This dissertation demonstrates the application of probabilistic model of texts in the study of literary history. The major finding of the dissertation is that regularities previously identified by literary historians can be captured by probabilistic models. Following the first chapter, "How to Read 22,198 Journal Articles: Studying the History of German Studies Using Topic Models," which introduces representations of texts used in the dissertation, chapter 3, "Inferring Novelistic Genre in the English Novel, 1800-1836," and chapter 4, "Networks of Literary Production," illustrate the contribution probabilistic models of novelistic production are positioned to make to long-standing questions in literary history. Both chapters are concerned with the detection and description of empirical regularities in surviving nineteenth-century English novels, such as the recurrence of novelistic genres--e.g., gothic, silver fork, and national tale novels. Chapter 3 makes use of a corpus that includes a random sample of novels published in the British Isles between 1800 and 1836. The use of a random sample and of probabilistic methods, both uncommon in literary studies, serves to develop new conceptual resources for future work in literary history and the sociology of literature.</p> === Dissertation
author2 Hayles, Katherine
author_facet Hayles, Katherine
Riddell, Allen
author Riddell, Allen
author_sort Riddell, Allen
title Demography of Literary Form: Probabilistic Models for Literary History
title_short Demography of Literary Form: Probabilistic Models for Literary History
title_full Demography of Literary Form: Probabilistic Models for Literary History
title_fullStr Demography of Literary Form: Probabilistic Models for Literary History
title_full_unstemmed Demography of Literary Form: Probabilistic Models for Literary History
title_sort demography of literary form: probabilistic models for literary history
publishDate 2013
url http://hdl.handle.net/10161/7210
work_keys_str_mv AT riddellallen demographyofliteraryformprobabilisticmodelsforliteraryhistory
_version_ 1716613902456848384