A qualitative analysis framework using natural language processing and graph theory

This paper introduces a method of extending natural language-based processing of qualitative data analysis with the use of a very quantitative tool—graph theory. It is not an attempt to convert qualitative research to a positivist approach with a mathematical black box, nor is it a “graphical soluti...

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Autor principal: Patrick Tierney
Formato: article
Lenguaje:EN
Publicado: Athabasca University Press 2012
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Acceso en línea:https://doaj.org/article/a2a54324f8614989a940b38511aa0f51
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spelling oai:doaj.org-article:a2a54324f8614989a940b38511aa0f512021-12-02T17:15:38ZA qualitative analysis framework using natural language processing and graph theory10.19173/irrodl.v13i5.12401492-3831https://doaj.org/article/a2a54324f8614989a940b38511aa0f512012-11-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/1240https://doaj.org/toc/1492-3831This paper introduces a method of extending natural language-based processing of qualitative data analysis with the use of a very quantitative tool—graph theory. It is not an attempt to convert qualitative research to a positivist approach with a mathematical black box, nor is it a “graphical solution”. Rather, it is a method to help qualitative researchers, especially those with limited experience, to discover and tease out what lies within the data. A quick review of coding is followed by basic explanations of natural language processing, artificial intelligence, and graph theory to help with understanding the method. The process described herein is limited by neither the size of the data set nor the domain in which it is applied. It has the potential to substantially reduce the amount of time required to analyze qualitative data and to assist in the discovery of themes that might not have otherwise been detected. Patrick TierneyAthabasca University PressarticleQualitative analysisgraph theorynatural language processingSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 13, Iss 5 (2012)
institution DOAJ
collection DOAJ
language EN
topic Qualitative analysis
graph theory
natural language processing
Special aspects of education
LC8-6691
spellingShingle Qualitative analysis
graph theory
natural language processing
Special aspects of education
LC8-6691
Patrick Tierney
A qualitative analysis framework using natural language processing and graph theory
description This paper introduces a method of extending natural language-based processing of qualitative data analysis with the use of a very quantitative tool—graph theory. It is not an attempt to convert qualitative research to a positivist approach with a mathematical black box, nor is it a “graphical solution”. Rather, it is a method to help qualitative researchers, especially those with limited experience, to discover and tease out what lies within the data. A quick review of coding is followed by basic explanations of natural language processing, artificial intelligence, and graph theory to help with understanding the method. The process described herein is limited by neither the size of the data set nor the domain in which it is applied. It has the potential to substantially reduce the amount of time required to analyze qualitative data and to assist in the discovery of themes that might not have otherwise been detected.
format article
author Patrick Tierney
author_facet Patrick Tierney
author_sort Patrick Tierney
title A qualitative analysis framework using natural language processing and graph theory
title_short A qualitative analysis framework using natural language processing and graph theory
title_full A qualitative analysis framework using natural language processing and graph theory
title_fullStr A qualitative analysis framework using natural language processing and graph theory
title_full_unstemmed A qualitative analysis framework using natural language processing and graph theory
title_sort qualitative analysis framework using natural language processing and graph theory
publisher Athabasca University Press
publishDate 2012
url https://doaj.org/article/a2a54324f8614989a940b38511aa0f51
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