In practice: Analysing large datasets and developing methods for that

A quick post here but one that seeks to place the rather polemic and borderline-ranty previous post about realising the potential of CAQDAS tools into an applied rather than abstract context.

Here’s a quote that i really like:

The signal characteristic that distinguishes online from offline data collection is the enormous amount of data available online….

Qualitative analysts have mostly reacted to their new-found wealth of data by ignoring it. They have used their new computerized analysis possibilities to do more detailed analysis of the same (small) amount of data. Qualitative analysis has not really come to terms with the fact that enormous amounts of qualitative data are now available in electronic form. Analysis techniques have not been developed that would allow researchers to take advantage of this fact.

(Blank, 2008, p258)

I’m working on a project to analyse the NSS (National Student Survey) qualitative textual for Lancaster University (around 7000 comments). Next steps include analysing the PRES and PTES survey comments. But that;s small fry – the biggie is looking at the module evaluation data for all modules for all years (~130,000 comments!)

This requires using tools to help automate the classification, sorting and sampling of that unstructured data in order to be able to engage with interpretations. This sort of work NEEDS software – there’s a prevailing view that this either can’t be done (you can only work with numbers) or that it will only quantify data and somehow corrupt it and make it non-qualitative.

I would argue that isn’t the case – tools like those I’m testing and comparing including the ProSUITE from Provalis including QDA Miner/WordSTAT, Leximancer and NVivo Plus (incorporating Lexalytics) – enable this sort of working with large datasets based on principles of content analysis and data mining.

However these only go so far – they enable the classification of data and its sorting but there is still a requirement for more traditional qualitative methods of analysis and synthesis. I’ve been using (and hacking) framework matrices in NVivo Plus in order to synthesise and summarise the comments – an application of a method that is more overtly “qualitative data analysis” in a much more traditional vein but yet applied to and mediated by tools that enable application to much MUCh larger datasets than would perhaps normally be used in qual analysis.

And this is the sort of thing I’m talking about in terms of enabling the potential of the tools to guide the strategies and tactics used. But it took an awareness of the capabilities of these tools and an extended period of playing with them to find out what they could do in order to scope the project and consider which sorts of questions could be meaningfully asked, considered and explored as well. This seems to be oppositional to some of the prescriptions in the 5LQDA views about defining strategies separate from the capabilities of the tools – and is one of the reasons for taking this stance and considering it here.

Interestingly this has also led to a rejection of some tools (e.g. MaxQDA and ATLAS.ti) precisely due to their absence of functions for this sort of automated classification – again capabilities and features are a key consideration prior to defining strategies. However I’m now reassessing this as MaxQDA can do lemmatisation which is more advanced than NVivo plus…

This is just one example but to me it seems to be an important one to consider what could be achieved if we explore features and opportunities first rather than defining strategies that don’t account for those. In other words: a symbiotic exploration of the features and potentials of tools to shape and define strategies and tactics can open up new possibilities that were previously rejected rather than those tools and features necessarily or properly being subservient to strategies that fail to account for their possibilities.

On data mining and content analysis

I would highly recommend reading Leetaru (2012)  for a good, accessible overview of data mining methods and how these are used in content analysis. These give a clear insight into the methods, assumptions, applications and limitations of the aforementioned tools helping to demystify and open what can otherwise seem to be a black-box that automagically “does stuff”.

Krippendorf’s (2013) book is also an excellent overview of content analysis with several considerations of human-centred analysis using for example ATLAS.ti or NVivo as well as automated approaches like those available in the tools above.


Blank G. (2008) Online Research Methods and Social Theory. In: Fielding N, Lee RM and Blank G (eds) The SAGE handbook of online research methods. Los Angeles, Calif.: SAGE, 537-549.

Preview of Ch1 available at

Krippendorff, K. (2012). Content analysis: An introduction to its methodology. Sage.

Preview chapters available at

Leetaru, Kalev (2012). Data mining methods for the content analyst : an introduction to the computational analysis of content. Routledge, New York

Preview available at 


On agency and technology: relating to tactics, strategies and tools

This continues my response to Christina Silver’s tweet and blog post. While my initial response to one aspect of that argument was pretty simple this is the much more substantive consideration.

From my perspective qualitative research reached a crossroads a while ago, though actually I think crossroads is the wrong term here. A crossroads requires a decision, it is a place steeped in mystery and mythology (see ), I sometimes feel as though qualitative research did a very british thing: turned a crossroads into a roundabout thus enabling driving round and round rather than moving forwards or making a decision.

The crossroads was the explosion in the availability of qualitative data. Previously access to accounts of experience were rather limited – you had to go into the field and write about it, find people to interview, or use the letters pages of newspapers as a site of public discourse. These paper-based records were slow and time consuming to assemble, construct and analyse. For the sake of the metaphor that follows I shall refer to these as “the cavalry era” of qualitative research. Much romanticised and with doctrines that still dominate from the (often ageing, pre-digital) professoriat.

Then the digital didn’t so much happen as explode and social life expanded or shifted online:

For researchers used to gathering data in the offline world, one of the striking characteristics of online research is the sheer volume of data. (Blank, 2008, P539)


Qualitative analysts have mostly reacted to their new-found wealth of data by ignoring it. They have used their new computerized analysis possibilities to do more detailed analysis of the same (small) amount of data. Qualitative analysis has not really come to terms with the fact that enormous amounts of qualitative data are now available in electronic form. Analysis techniques have not been developed that would allow researchers to take advantage of this fact. (Blank, 2008, P.548)

Furthermore the same methods continue to dominate – the much vaunted reflexivity that lies at the heart of claims for authenticity and trustworthiness does not seem to have been extended to tools, methods:

Over the past 50 years the habitual nature of our research practice has obscured serious attention to the precise nature of the devices used by social scientists (Platt 2002, Lee 2004). For qualitative researchers the tape-recorder became the prime professional instrument intrinsically connected to capturing human voices on tape in the context of interviews. David Silverman argues that the reliance on these techniques has limited the sociological imagination: “Qualitative researchers’ almost Pavlovian tendency to identify research design with interviews has blinkered them to the possible gains of other kinds of data” (Silverman 2007: 42). The strength of this impulse is widely evident from the methodological design of undergraduate dissertations to multimillion pound research grant applications. The result is a kind of inertia, as Roger Stack argues: “It would appear that after the invention of the tape-recorder, much of sociology took a deep sigh, sank back into the chair and decided to think very little about the potential of technology for the practical work of doing sociology” (Slack 1998: 1.10).

My concern with the approach presented and advocated by Silver and Woolf is that it holds the potential to reinforce and prolong this inertia. There are solid arguments FOR that position – especially given the conservatism of academia, mistrust of software and the apparently un-slayable discourses (Paulus, lester & Britt, 2013), entrenched critical views and misconceptions of QDAS software that “by its very nature decontextualizes data or primarily supports coding [which] have caused concerned researchers” (Paulus, Woods, Atkins and Macklin, 2017)


New technologies enable new things – when they first arrive they are usually perhaps inevitably and restrictively fitted in to pre-existing approaches and methods, made subservient to old ways of doing things.

A metaphor – planes, tanks and tactics

I’ve been trying to think of a metaphor for this. The one I’ve ended up with is particularly militaristic and I’m not entirely comfortable with it – especially as metaphors sometimes invite over-extension which I fear may happen here. It also feels rather jingoistically “Boys Own” and British and may be alienating to key developers and methodologists in Germany. So comments on alternative metaphors would be MOST welcome, however given the rather martial themes around strategies and tactics used in Silver and Woolf’s (2015) paper and models for 5level QDA I’ll stick with it and explore tactics, strategies and technologies and how they historically related to two new technologies: the tank and the plane.

WW1 saw the rapid development of new and terrifying technologies in collision with old tactics and strategies for their use. The overarching strategies were the same (defeat the enemy) however the tactics used failed to take account of the potential of these new tools thus restricting their potential.

Cavalry were still deployed at the start of WW1. Even with the invention of tanks the tactics used in their early deployments were for mounted cavalry to follow up the breakthroughs achieved by tanks – with predictably disastrous failure at the battle of cambrai see ).

Planes were deployed from early in WW1 but in very limited capacities – as artillery spotters and as reconnaissance. Their potential to change warfare tactics were barely recognised nor exploited.

These strategies were developed by generals from an earlier era – still wedded to the cavalry charge as the ultimate glory. (See ). Which seems to be a rather appropriate metaphor for professorial supervision today with regard to junior academics and PhD students.

The point I’m seeking to make is to suggest that new technologies vary in their complexity, but they also vary in their potential. Old methods of working are used with new technologies and the transformative potential of those new technologies on methods or tactics to achieve strategic aims is often far slower, and can be slowed further when there is little immediate incentive to change (unlike say a destructive war) in the face of an established doctrine.

My view is therefore that those who do work with and seek to innovate with CAQDAS tools  need to seek to do more than just fit in with the professorial field-marshall Haig’s of our day and talk in terms of CAQDAS being “fine for breaching the front old chap you know use CAQDAS to open up the data but you send in the printouts and transcripts to really do the work of harrying the data, what what old boy”.

Meanwhile Big Data is the BIG THING – and this entire sphere of large datasets and access to public discourse and digital social life threatens to be ceded entirely to quantitative methods. Yet we have tools, methods and tactics to engage in that area meaningfully by drawing on existing approaches which have always been both qual and quant (with corpus linguistics and content analysis springing to mind).

Currently the scope of any transformation seems to be pitched to taking strategies from a “cavalry era” of qualitative research. My suggestion is that to realise the full potential of some of the tools now available in order to generate new, and extend existing, qualitative analysis practices into the diverse new areas of digital social life and digital social data we need to be bolder in proposing what these tools can achieve and what new questions and datasets can be worked with. And that means developing new strategies to enter new territories – which need to understand the potential of these tools and explore ways that they can transform and extend what is possible.

If, however, we were to place the potential of these tools as subservient to existing strategies and to attempt to locate all of the agency for their use with the user and the way that we “configure the user” (Grint and Woolgar, 1997) in relation to these tools through our pedagogies and demonstrations we could limit those potentials. Using NVivo Plus or QDA Miner/WordSTAT to reproduce what could be done with a tape recorder, paper, pen and envelopes seems akin to sending horses chasing after tanks. What I am advocating for (as well, not instead) is to also try to work out what a revolutionary engagement with the potential of the new tools we have would look like for qualitative analysis with big unstructured qualitative data and big unstructured qualitatitve data-ready tools.

To continue the parallel here – the realisation of what could be accomplish by combining the new technologies of tanks and planes together created an entirely new form of attacking warfare – named Blitzkrieg by the journalists who witnessed its lightning speed. This was developed to achieve the same overarching strategies as deployed in WW1 (conquering the enemy) but by considering the potential and integration of new tools it developed a whole new mid-level strategy and associated tactics that utilised and realised the potential of those relatively new technologies. Thus it avoided becoming bogged down in the nightmare of using the strategies and tactics from a bygone era of pre-industrial warfare with new technologies that prevented their effectiveness which dominated in WW1. My suggestion is that there is a new territory now – big data – and it is one that is being rapidly and extensively ceded to a very quantitative paradigm and methods. To make the kind of rapid advances into that territory in order to re-establish qualitative analysis as having relevance we need to be bolder in developing new strategies that utilise the tools rather than making these subservient to strategies from an earlier era in deference to a frequently luddite professoriat.

My argument thus simplifies to the idea that the potential of tools can and should productively shape not only the planning and consideration the territories now amenable to exertion and engagement but also the strategies and tactics to do that. Doing that involves engagement with the conceptualisation, design and thinking about what qualitative or mixed-methods studies are and what they can do in order that this potential is realised. From this viewpoint Blitzkrieg was performed into being by the new technologies of the tank and the plane and their combination with new strategies and tactics. These contrast with the earlier subsuming of the plane’s potential to merely being tools to achieve strategies that were conceptualised before its existence. A plane was there equivalent to a tree or a balloon for spotting cannon fire. Much of CAQDAS use today seems to be just like this – sending horses chasing after tanks – rather than seeking to achieve things that couldn’t be done without it and celebration that.

This is all rather abstract I know so I’ve tried to extend and apply this into a consideration of implementation in practice working with large unstructured datasets in a new post.


Back L. (2010) Broken Devices and New Opportunities: Re-imagining the tools of Qualitative Research. ESRC National Centre for Research Methods

Available from:


Lee, R. M. (2004) ‘Recording Technologies and the Interview in Sociology, 1920-2000’, Sociology, 38(5): 869-899

E-Print available at:

Platt, J. (2002) ‘The History of the Interview,’ in J. F. Gubrium and J. A. Holstein (eds) Handbook of the Interview Research: Context and Method, Thousand Oaks, CA: Sage pp. 35-54.

Limited Book Preview available at

Silverman D. (2007) A very short, fairly interesting and reasonably cheap book about qualitative research, Los Angeles, Calif.: SAGE.

Limited Book Preview at:

Slack R. (1998) On the Potentialities and Problems of a www based naturalistic Sociology. Sociological Research Online 3.

Available from:

Blank G. (2008) Online Research Methods and Social Theory. In: Fielding N, Lee RM and Blank G (eds) The SAGE handbook of online research methods [electronic resource]. Los Angeles, Calif. ; London : SAGE.

Grint K and Woolgar S. (1997) Configuring the user: inventing new technologies. The machine at work: technology, work, and organization. Cambridge, Mass.: Polity Press, 65-94.

Paulus TM, Lester JN and Britt VG. (2013) Constructing Hopes and Fears Around Technology. Qualitative Inquiry 19: 639-651.

Paulus T, Woods M, Atkins DP, et al. (2017) The discourse of QDAS: reporting practices of ATLAS.ti and NVivo users with implications for best practices. International Journal of Social Research Methodology 20: 35-47.

Silver C and Woolf NH. (2015) From guided-instruction to facilitation of learning: the development of Five-level QDA as a CAQDAS pedagogy that explicates the practices of expert users. International Journal of Social Research Methodology 18: 527-543.