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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Detalles Bibliográficos
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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Sumario: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.