Abstract
Background: Epistemic Network Analysis (ENA) is a unified, quantitative - qualitative method aiming to draw from both methodological worlds by leveraging a data set containing raw and quantified qualitative data, as well as metadata about data providers or the data itself. ENA generates network models depicting the relative frequencies of co-occurrences for each unique pair of codes in designated segments of qualitative data. Methods: This step-by-step tutorial demonstrates how to model qualitative data with ENA through its quantification via coding and segmentation. Data was curated with the Reproducible Open Coding Kit (ROCK), a human- and machine-readable standard for representing coded qualitative data, enabling researchers to document their workflow, as well as organize their data in a format that is agnostic to software of any kind. Results: ENA allows researchers to obtain insights otherwise unavailable by depicting relative code frequencies and co-occurrence patterns, facilitating a comparison of those patterns between groups and individual data providers. Conclusions: ENA aids reflexivity, moves beyond code frequencies to depict their interactions, allows researchers to easily create post-hoc groupings of data providers for various comparisons, and enables conveying complex results in a visualization that caters to both qualitative and quantitative sensibilities.