PAD: a graphical and numerical enhancement of structural coding to facilitate thematic analysis of a literature corpus

TL;DR

This paper introduces PAD, an enhanced structural coding method using graph theory and statistics to facilitate thematic analysis of literature corpora, enabling more precise and quantifiable qualitative analysis.

Contribution

The paper presents a novel integration of causally bound codes, graph constructs, and statistical analysis into structural coding for literature analysis.

Findings

Enhanced coding captures causality and frequency effectively

Graph-based representation facilitates thematic analysis

Applicable to various qualitative research contexts

Abstract

We suggest an enhancement to structural coding through the use of (a) causally bound codes, (b) basic constructs of graph theory and (c) statistics. As is the norm with structural coding, the codes are collected into categories. The categories are represented by nodes (graph theory). The causality is illustrated through links (graph theory) between the nodes and the entire set of linked nodes is collected into a single directed acyclic graph. The number of occurrences of the nodes and the links provide the input required to analyze relative frequency of occurrence, as well as opening a scope for further statistical analysis. While our raw data was a corpus of literature from a specific discipline, this enhancement is accessible to any qualitative analysis that recognizes causality in its structural codes.