Qualitative Data Analysis Software

Accepted manuscript, citeable as: de Wildt, L. (2020). Qualitative Data Analysis Software, in Possamai, A. & Blasi, A.J. (eds.) The SAGE Encyclopedia of the Sociology of Religion. Thousand Oaks, CA: SAGE Publications. Vol. 2, pp. 642-644. DOI: 10.4135/9781529714401.n366 Qualitative Data Analysis Software Since roughly the turn of the century, qualitative researchers can make use of qualitative data analysis software [QDAS, or CAQDAS: Computer-Assisted QDAS] such as ATLAS.ti, NVivo, and an increasing number of sophisticated, free options. While the basic premises and traditions of dealing with rich data have stayed the same for the purposes of qualitative analyses, these software packages are increasingly assisting researchers, including sociologists of religion, in making sense of large bodies of qualitative data. Such tools are only the latest technological continuation of pre-existing means of performing qualitative data analysis. Generally speaking, qualitative research concerns experiential data that are often considered ’rich’ data that aim to capture human experience. Such data are studied predominantly inductively, according to constructivist, symbolic interactionist or grounded theory approaches; and through methods including thick description, ethnography, content analysis, and various types of interviews – the analysis of which can be assisted by the use of computer software. Particularly in the case of the sociology of religion, making sense of widely disparate lifeworlds, beliefs and ritual practices can be supported by QDAS. Which software options are available, and how do they assist qualitative analysis? There are roughly two types of software suites available most generally, while additional attention will be given to free, open-source alternatives that are accessible to all. Roughly speaking, there is QDAS designed for qualitative analysis that includes quantitative options for mixed-method research (e.g., ATLAS.ti, Dedoose, MAXQDA, NVivo, R and QDA Miner), and purely qualitative software optimized solely for qualitative analysis (Aquad, Cassandre, Accepted manuscript, citeable as: de Wildt, L. (2020). Qualitative Data Analysis Software, in Possamai, A. & Blasi, A.J. (eds.) The SAGE Encyclopedia of the Sociology of Religion. Thousand Oaks, CA: SAGE Publications. Vol. 2, pp. 642-644. DOI: 10.4135/9781529714401.n366 CLAN, CAT, Compendium, ELAN, HyperRESEARCH, KH Coder, Quirkos and Transana). In practice, all of them will have similar core functionalities for the analysis of text sources, notes and transcriptions. Some additionally support multimedial source material such as audio and video (Aquad, Dedoose, ELAN, MAXQDA, NVivo, Transana), or even social network analysis (MAXQDA). Preferences are mostly based on platform (i.e., availability on Windows, Mac or Linux), personal experience (e.g., why switch to ATLAS.ti when one is used to NVivo?), institutional support (different university departments may choose to purchase specific software licenses as a group), and price. Within the last category, special mention should be made of freely accessible software that can be used without cost by students, early career researchers and independent researchers: Aquad, Cassandre, CLAN, CAT, Compendium, ELAN, KH Coder and Transana fit this prescription, as well as qdap and RQDA, two ‘packages’ for use within the R programming language – which is originally primarily a programming environment for statistical computing. General functions offered by these applications are many. These often include the ability to transcribe audio- or video-interviews within the programme, thus allowing text to remain synchronized with specific passages of interviews. Users are furthermore able to apply (textual and colour-coded) codes to text and multimedial sources according to standard principles of grounded theory and content analysis. Specifically, software coding offers the ability to ‘nest’ specific codes within overlapping or higher categories; using a limitless amount of codes that is curbed only by the researcher’s ability to make sense of and describe them. Codes can automatically be organized into themes, which are organically adjusted as codes evolve from open to closed coding. Within this software environment, both source material, literature, and all the overarching codes and themes remain adjustable in side-by- Accepted manuscript, citeable as: de Wildt, L. (2020). Qualitative Data Analysis Software, in Possamai, A. & Blasi, A.J. (eds.) The SAGE Encyclopedia of the Sociology of Religion. Thousand Oaks, CA: SAGE Publications. Vol. 2, pp. 642-644. DOI: 10.4135/9781529714401.n366 side analysis and at hand for constant comparative methods of analysis. In addition, QDA software often adds options for co-operative work – allowing multiple researchers to code and take notes simultaneously – and various visualization options that can make data insightful in various ways for both eventual readers; as well as for researchers to gain an overview on complex bodies of data during the process of analysis. Overall, however, such software is then primarily a continuation of previous technological means of organizing, categorizing and analysing qualitative data. That is, whether the researcher(s) organize their data by writing them out, printing them, (colour)coding data with sticky notes, markers, cutting and pasting pieces of paper into organized themes; or use computer software to organize codes: the mechanism is essentially the same. What counts for constant comparison, thick description, content analysis; and all the approaches that inform these and similar methods is this: they are fundamentally about human meaning-making. Constructions of societal and cultural meaning – whether on the individual or the group level – need to be meaningfully organized by human researchers. In the end, what differentiates Computer-Assisted Qualitative Data Analysis Software (CAQDAS) from quantitative data analysis software, is that while the latter can process complex calculations taking over human analysis through sheer computing power; qualitative data analysis software, by contrast, remains necessarily just a tool to aid human analysis. There is arguably always, at the heart of qualitative analysis, the need for a researcher to conceptually organize emic experiences into meaningfully differentiated etic categories. That is: to do analysis. In summary, qualitative data analysis software has granted qualitative analyses the ease of quick organization, the unambiguity of computers’ concreteness, a virtually limitless Accepted manuscript, citeable as: de Wildt, L. (2020). Qualitative Data Analysis Software, in Possamai, A. & Blasi, A.J. (eds.) The SAGE Encyclopedia of the Sociology of Religion. Thousand Oaks, CA: SAGE Publications. Vol. 2, pp. 642-644. DOI: 10.4135/9781529714401.n366 amount of possible codes to keep track of, and ways to allow for easy visualization and (online) co-operation. As such, qualitative data analysis software grants researchers a handy toolset to manage their data, while the fundamental workings of qualitative analysis and the role of the researcher have not changed. Lars de Wildt See also Qualitative Research, Social Constructivism, Interactionism, Interviews, Content Analysis. Further Reading Braun, Virginia, and Clarke, Victoria. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3 (2). pp. 77-101. doi: 10.1191/1478088706qp063oa de Wildt, Lars, & Aupers, Stef (2017). Bibles and BioShock: Affording Religious Discussion on Video Game Forums. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play (pp. 463-475). ACM. doi: 10.1145/3116595.3116625 Glaser, Barney, and Strauss, Anselm. (1967) The Discovery of Grounded Theory, Chicago: Aldine Transaction. doi: 10.4324/9780203793206-1 Ryan, Gery, & Bernard, H. Russel. (2000). Data management and analysis methods. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Qualitative Research (2nd ed., pp. 769-802). Thousand Oaks, CA: Sage.