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Studying Literary History with Laten...

Riddell, Allen Beye.

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Studying Literary History with Latent Feature Models.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Studying Literary History with Latent Feature Models./
Author:	Riddell, Allen Beye.
Description:	54 p.
Notes:	Source: Masters Abstracts International, Volume: 51-06.
Contained By:	Masters Abstracts International51-06(E).
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536301
ISBN:	9781303044502

Studying Literary History with Latent Feature Models.
Riddell, Allen Beye.

Studying Literary History with Latent Feature Models. - 54 p.

Source: Masters Abstracts International, Volume: 51-06.

Thesis (M.S.)--Duke University, 2013.

Novelistic genres---such as gothic novels, epistolary novels, and Bildungsromane---were an abiding feature of literary production in the nineteenth century. Their appearance, disappearance, and transmission across national and linguistic boundaries continues to be an object of interest for scholars in literary history and sociology of culture. This thesis considers two non-parametric latent feature models of a corpus of British literary fiction and compares the models' representations with the judgments of literary historians. I find that the models agree with expert classifications of novelistic genre better than chance. This thesis contributes to efforts to validate latent feature models against human judgments and offers further confirmation that probabilistic models of text collections can support historical scholarship.

ISBN: 9781303044502Subjects--Topical Terms:

517247
Statistics.

Studying Literary History with Latent Feature Models.
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020 $a 9781303044502
035 $a (MiAaPQ)AAI1536301
035 $a AAI1536301
040 $a MiAaPQ $c MiAaPQ
100 1 $a Riddell, Allen Beye. $3 2101538
245 1 0 $a Studying Literary History with Latent Feature Models.
300 $a 54 p.
500 $a Source: Masters Abstracts International, Volume: 51-06.
500 $a Adviser: David Dunson.
502 $a Thesis (M.S.)--Duke University, 2013.
520 $a Novelistic genres---such as gothic novels, epistolary novels, and Bildungsromane---were an abiding feature of literary production in the nineteenth century. Their appearance, disappearance, and transmission across national and linguistic boundaries continues to be an object of interest for scholars in literary history and sociology of culture. This thesis considers two non-parametric latent feature models of a corpus of British literary fiction and compares the models' representations with the judgments of literary historians. I find that the models agree with expert classifications of novelistic genre better than chance. This thesis contributes to efforts to validate latent feature models against human judgments and offers further confirmation that probabilistic models of text collections can support historical scholarship.
590 $a School code: 0066.
650 4 $a Statistics. $3 517247
650 4 $a Literature, General. $3 1018152
690 $a 0463
690 $a 0401
710 2 $a Duke University. $b Statistical Science. $3 1023903
773 0 $t Masters Abstracts International $g 51-06(E).
790 $a 0066
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536301