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Studying Literary History with Latent Feature Models

dc.contributor.advisor Dunson, David B
dc.contributor.author Riddell, Allen
dc.date.accessioned 2013-05-13T15:37:52Z
dc.date.available 2013-11-09T05:30:09Z
dc.date.issued 2013
dc.identifier.uri https://hdl.handle.net/10161/7312
dc.description.abstract <p>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.</p>
dc.subject Statistics
dc.subject Literature
dc.title Studying Literary History with Latent Feature Models
dc.type Master's thesis
dc.department Statistical Science
duke.embargo.months 6


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