计算机科学
可视化
网络分析
编码(社会科学)
图形绘制
理论计算机科学
代表(政治)
图形
数据可视化
数据挖掘
图论
定性分析
定性研究
数学
统计
组合数学
物理
政治学
社会学
政治
法学
量子力学
社会科学
作者
Jennifer J. Pokorny,Alex Norman,Anthony P. Zanesco,Susan Bauer‐Wu,Baljinder K. Sahdra,Clifford D. Saron
出处
期刊:Psychological Methods
[American Psychological Association]
日期:2017-06-01
卷期号:23 (1): 169-183
被引量:74
摘要
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. (PsycINFO Database Record
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