What is it about?
Qualitative data analysis software (QDAS) packages are a recent innovation. Little has been written concerning the research implications of differences in such QDAS packages’ functionalities, and how such disparities might contribute to contrasting analytical opportunities. Consequently, early-stage researchers may experience difficulties in choosing an apt QDAS for Twitter analysis. In response to both methodological gaps, this paper presents a software comparison across the four QDAS tools that support live Twitter data imports, namely, ATLAS.ti™, NVivo™, MAXQDA™ and QDA Miner™.
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Why is it important?
The article's findings may help guide Twitter social science researchers and others in QDAS tool selection: Notwithstanding large difference in QDAS pricing, it was surprising how much the tools varied for aspects of qualitative research organisation with live Twitter data. Notably, the quantum of data extracted for the same query differed, largely due to contrasts in the types and amount of data that the four QDAS could extract. Variations in how each supported visual organisation also shaped researchers’ opportunities for becoming familiar with Twitter users and their tweet content. Such disparities suggest that choosing a suitable QDAS for organising live Twitter data must dovetail with a researcher’s focus: ATLAS.ti accommodates scholars focused on wrangling unstructured data for personal meaning-making, while MAXQDA suits the mixed-methods researcher. QDA Miner’s easy-to-learn user interface suits a highly efficient implementation of methods, whilst NVivo supports relatively rapid analysis of tweet content.
Perspectives
This paper resulted from a lengthy interdisciplinary collaboration between authors with very different analytical dispositions: a qualitative data analyst, a pragmatist and a statistician. Although the study focuses on the qualitative research organisation of live Twitter data, it has academic value for qualitative researchers using QDAS tools to organise data imported from other social media platforms. Scholars ranging from the purely qualitative to those favouring strongly mixed methods are likely to face similar enablers and constraints when organising say, Reddit forum discussions or YouTube video commentary.
Dr Travis M Noakes
Cape Peninsula University of Technology
Read the Original
This page is a summary of: Noteworthy Disparities With Four CAQDAS Tools: Explorations in Organising Live Twitter Data, Social Science Computer Review, September 2023, SAGE Publications,
DOI: 10.1177/08944393231204163.
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