A qualitative analysis framework using natural language processing and graph theory

Authors

  • Patrick Tierney Brock University

DOI:

https://doi.org/10.19173/irrodl.v13i5.1240

Keywords:

Qualitative analysis, graph theory, natural language processing

Abstract

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.

Author Biography

Patrick Tierney, Brock University

Ph.D. Student

Faculty of Education

Brock University

Published

2012-11-08

How to Cite

Tierney, P. (2012). A qualitative analysis framework using natural language processing and graph theory. The International Review of Research in Open and Distributed Learning, 13(5), 173–189. https://doi.org/10.19173/irrodl.v13i5.1240