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.

中文翻译：

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PAD：结构编码的图形和数字增强，以促进文献语料库的主题分析

我们建议通过使用（a）因果约束代码，（b）图论的基本结构和（c）统计来增强结构编码。作为结构编码的规范，代码被收集到类别中。类别由节点表示（图论）。因果关系通过节点之间的链接（图论）来说明，整个链接节点集被收集到一个单一的有向无环图中。节点和链接的出现次数提供了分析相对出现频率所需的输入，并为进一步的统计分析开辟了空间。虽然我们的原始数据是来自特定学科的文献语料库，但任何在其结构代码中识别因果关系的定性分析都可以访问这种增强。