IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Computer-Aided Rhetorical Analysis

Computer-Aided Rhetorical Analysis
View Sample PDF
Author(s): Suguru Ishizaki (Carnegie Mellon University, USA)and David Kaufer (Carnegie Mellon University, USA)
Copyright: 2012
Pages: 21
Source title: Applied Natural Language Processing: Identification, Investigation and Resolution
Source Author(s)/Editor(s): Philip M. McCarthy (The University of Memphis, USA)and Chutima Boonthum-Denecke (Hampton University, USA)
DOI: 10.4018/978-1-60960-741-8.ch016

Purchase

View Computer-Aided Rhetorical Analysis on the publisher's website for pricing and purchasing information.

Abstract

This chapter presents a corpus-based text analysis tool along with a research approach to conducting a rhetorical analysis of individual text as well as text collections. The motivation for our computational approach, the system development, evaluation, and research and educational applications are discussed. The tool, called DocuScope, supports both quantitative and quantitatively-informed qualitative analyses of rhetorical strategies found in a broad range of textual artifacts, using a standard home-grown dictionary consisting of more than 40 million unique patterns of English that are classified into over 100 rhetorical functions. DocuScope also provides an authoring environment allowing investigators to build their own customized dictionaries according to their own language theories. Research published with both the standard and customized dictionaries is discussed, as well as tradeoffs, limitations, and directions for the future.

Related Content

Reinaldo Padilha França, Ana Carolina Borges Monteiro, Rangel Arthur, Yuzo Iano. © 2021. 21 pages.
Abdul Kader Saiod, Darelle van Greunen. © 2021. 28 pages.
Aswini R., Padmapriya N.. © 2021. 22 pages.
Zubeida Khan, C. Maria Keet. © 2021. 21 pages.
Neha Gupta, Rashmi Agrawal. © 2021. 20 pages.
Kamalendu Pal. © 2021. 14 pages.
Joy Nkechinyere Olawuyi, Bernard Ijesunor Akhigbe, Babajide Samuel Afolabi, Attoh Okine. © 2021. 19 pages.
Body Bottom