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Analyzing Qualitative Data
December 2, 2014
Having been to several international conferences on qualitative research recently, there has been a lot of discussion about the future of qualitative research, and the changes happening in the discipline and society as a whole. A lot of people have been saying that acceptance for qualitative research is growing in general: not only are there a large number of well-established specialist journals, but mainstream publications are accepting more papers based on qualitative approaches.
At the same time, there are more students in the UK at all levels, but especially starting Masters and PhD studies as I’ve noted before. While some of these students will focus solely on qualitative methods, many more will adopt mixed methods approaches, and want to integrate a smaller amount of qualitative data. Thus there is a strong need, especially at the Masters by research level, for software that’s quicker to learn, and can be well integrated into the rest of a project.
There is also the increasing necessity for academic researchers to demonstrate impact for their research, especially as part of the REF. There are challenges involved with doing this with qualitative research, especially summarising large bodies of data, and making them accessible for the general public or for targeted end users such as policy makers or clinicians. Quirkos has been designed to create graphical outputs for these situations, as well as interactive reports that end-users can explore in their own time.
But another common theme has emerged is the possibility of the qualitative field fracturing as it grows. It seems that there are at least three distinct user groups emerging: firstly there are the traditional users of in-depth qualitative research, the general focus of CAQDAS software. They are experts in the field, are experienced with a particular software package, and run projects collecting data with a variety of methods, such as ethnography, interviews, focus groups and document review.
Recently there has been increased interest in text analytics: the application of ‘big data’ to quantify qualitative sources of data. This is especially popular in social media, looking at millions of Tweets, texts, Facebook posts, or blogs on a particular topic. While commonly used in market research, there are also applications in social and political analysis, for example looking at thousands of newspaper articles for portrayal of social trends. This ‘bid data’ quantitative approach has never been a focus of Quirkos’ approach, although there are many tools out there that work in this way.
Finally, there is increasing interest in qualitative analysis from more mainstream users, people who want to do small qualitative research projects as part of their own organisation or business. Increasingly, people working in public sector organisations, HR or legal have text documents they need to manage and gain a deep understanding of.
Increasingly it seems that a one-size-fits-all solution to training and software for qualitative data analysis is not going to be viable. It may even be the case that different factions of approaches and outcomes will emerge. In some ways this may not be too dissimilar to the different methodologies already used within academic research (ie grounded / emergent / framework analysis), but the numbers of ‘researchers’ and the variety of paradigms and fields of inquiry looks to be increasing rapidly.
These are definitely interesting times to be working in qualitative research and qualitative data analysis. My only hope is that if such ‘splintering’ does occur, we keep learning from each other, and we keep challenging ourselves by exposure to alternative ways of working.