Enhancing Trustworthiness of Qualitative Findings: Using Leximancer for Qualitative Data Analysis Triangulation

Enhancing Trustworthiness of Qualitative Findings: Using Leximancer for Qualitative Data Analysis Triangulation

This paper offers an approach to enhancing trustworthiness of qualitative findings through data analysis triangulation using Leximancer, a text mining software that uses co-occurrence to conduct semantic and relational analyses of text corpuses to identify concepts, themes, and how they relate to on...

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Bibliographic Details
Published in:Qualitative report Vol. 25; no. 3; pp. 604 - 614
Main Authors: Lemon, Laura L, Hayes, Jameson
Format: Journal Article
Language:English
Published: Fort Lauderdale The Qualitative Report 01-03-2020
Subjects:
Coding
Computer Software
Credibility
Data analysis
Maya (People)
Qualitative research
Research Methodology
Researchers
Resistance (Psychology)
Semantics
Semiotics
Software
Statistical Analysis
Studies
Test Validity
Validity
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Summary:This paper offers an approach to enhancing trustworthiness of qualitative findings through data analysis triangulation using Leximancer, a text mining software that uses co-occurrence to conduct semantic and relational analyses of text corpuses to identify concepts, themes, and how they relate to one another. This study explores the usefulness of Leximancer for triangulation by examining 309 pages of previously analyzed interview data that resulted in a conceptual model. Findings show Leximancer to be an ideal tool for refining a priori conceptual models. The Leximancer analysis provided missing nuance from the a priori model, depicting the value of and connection between emergent themes. Dependability was also added to the findings by facilitating a better understanding of how participant quotes represent particular themes.
ISSN:1052-0147
2160-3715