Using network analysis for rapid, transparent, and rigorous thematic analysis: A case study of online distance learning

Abstract

In thematic analysis, themes construction can be performed manually by the researcher or automatically by a computer. Both methods have strengths and weaknesses. This article introduces a strategy that involves the role of both researcher and computer to construct themes from qualitative data in a rapid, transparent, and rigorous manner. The strategy makes use of network analysis and is demonstrated by employing a case study on students’ perceptions of online distance learning they experienced during the COVID-19 pandemic. The themes-construction strategy consists of four systematic phases, namely (1) determining unit of analysis and coding; (2) constructing the code co-occurrence matrix; (3) conducting network analysis; and (4) generating, reviewing, and reporting the themes. The strategy is successfully demonstrated in generating themes from the data with modularity value Q = 0.34. The application of network analysis in this strategy allows researchers to automatically generate themes from qualitative data using mathematical algorithms, represent these themes visually using network graph, and interpret the themes to answer the research questions.