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Wake Forest University

Big Data and the Rhetorical Narrative

Abstract

dc:description.abstract

This project effectively illustrates a tactic by which the constructs of narrative inquiry from a humanist perspective, in particular the rhetorical narrative tradition, can migrate into a larger methodology while simultaneously recognizing and training agents in narrative visualization via up-to-date computational tools. The Reddit platform in particular, served as a suitable illustration for a multifaceted approach to novel methods in narrative inquiry due to the free accessibility to online storytelling in addition to a substantial collection of unstructured data it offers. This permitted an effective exploration through means of analyzing mediated narratives while concurrently using computational methods to assemble, filter, and interpret "Reddit narratives." The project progresses in two parts. First I offer a model for contemporary rhetorical narrative analysis that embraces social media as a viable source of user-generated narrative data. The second half of the project illustrates a data analysis template that employs a rhetorical lens for the creation of narrative maps. Collectively this project proposes a model for continued rhetorical narrative inquiry that intersects at traditional qualitative analysis and the contemporary deployment of textual analytic software.

Degree

thesis:*
Grantor dc:publisher
Wake Forest University
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bowling, Roy Nathaniel

Subjects

dc:subject × 1

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10339/47448
OAI identifier oai:identifier
oai:wakespace.lib.wfu.edu:10339/47448

Chain of custody

source
Harvested from
Wake Forest University
Base URL
wakespace.lib.wfu.edu/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
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citation

Bowling, Roy Nathaniel. Big Data and the Rhetorical Narrative. Wake Forest University, 2014. http://hdl.handle.net/10339/47448