🤖 AI Summary
This study addresses the lack of systematic understanding regarding the types and motivations of visual representations in qualitative research. Building upon and extending Verdinelli & Scagnoli’s (2013) work through a data-driven literature review, it conducts a content analysis of articles and their visualizations published between 2020 and 2022 in three leading qualitative methods journals. Integrating epistemological stance classification with visualization-type coding, the study innovatively combines correspondence analysis and cognitive network analysis for the first time. Findings indicate that while visualizations remain underutilized in qualitative research, their typological diversity is increasing, and the choice of graphical representation appears largely independent of the authors’ epistemological positions. These results offer both empirical grounding and methodological innovation for integrating interdisciplinary visualization tools into qualitative inquiry.
📝 Abstract
Little is known about the representations used in qualitative research studies and why. A data-driven literature review was employed to explore the use of media in qualitative research reporting. A study by Verdinelli & Scagnoli (2013) was replicated and extended by conducting a content analysis of papers and figures published across three qualitative methods journals between 2020 and 2022. Figures were categorized by types (e.g., matrix-based, Venn diagrams, flowcharts) and documents were grouped by their epistemological stances (i.e., objectivist, subjectivist, or constructivist) before conducting a correspondence analysis and epistemic network analysis. Our findings suggest that (1) visual media have remained largely absent, (2) figure types have be come more diverse and (3) the use of figure types is likely independent of epistemological stance but provide opportunities for further exploration. These findings provide a foundation for impactful integration of data visualization tools to enhance communicati ve power of findings across disciplines.