Network analysis for the visualization and analysis of qualitative data

Jennifer J. Pokorny, Alex Norman, Anthony P. Zanesco, Susan Bauer-Wu, Baljinder K. Sahdra, Clifford D. Saron

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures. Here, as a proof of concept, we applied this method to a set of interview transcripts that had been coded in 2 different ways and the resultant network graphs were examined. The creation of network graphs allows researchers an opportunity to view and share their qualitative data in an innovative way that may provide new insights and enhance transparency of the analytical process by which they reach their conclusions.

Original languageEnglish
Pages (from-to)169-183
Number of pages15
JournalPsychological Methods
Volume23
Issue number1
DOIs
StatePublished - Mar 2018

Bibliographical note

Publisher Copyright:
© 2017 American Psychological Association.

Keywords

  • Interviews
  • Network graphs
  • Networks
  • Qualitative methods
  • Visualization

ASJC Scopus subject areas

  • Psychology (miscellaneous)

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