Qualitative software and tools for ‘close reading’ in the Digital Humanities

Qualitative software and tools for ‘close reading’ in the Digital Humanities

The Digital Humanities movement is a growing paradigm that aims to explore the new possibilities created by the availability of huge archives of data, and powerful digital tools that can explore them rapidly. This allows researchers to explore, connect and interpret vast amounts of data in ways that were not possible before. In essence, it can be seen as a vast field of secondary analysis – we can look for trends in language, history and culture across all of written history, or examine one era across huge swaths of documents to gauge the mood or reasons behind changes in society. It has applications in many different disciplines including history, media studies, art, archaeology and linguistics.

It has been argued that digital humanities involves the study of new ways to read texts that were not possible or too time consuming before. For example, one can explore the word choices of a prodigious writer like Thomas Aquinas (Burdick et al. 2012), or everything a newspaper wrote about for 50 years (Wijfjes 2017). It’s a field in which librarians have become important facilitators, able to discover, curate and connect archives with methods of interoperation.

These approaches often focus on the quantification or statistical analysis of huge datasets, so are often associated with big data, and what is called ‘distance reading’. Here, statistics or visualisations give a cursory overview of a large number of texts, so allow a quick glance across many different sources. One of the seminal books in this area is Moretti’s Distant Reading (2013), which essentially argues that if scholars focus on just close reading one or two works, they are unable to get a sense of any wider objective ‘truth’. It feels to me like the debates about small sample sizes in qualitative research: how can you know objective and widely applicable facts by looking an only a few cases?

In both cases this is a bit of a false argument – the discussion is around two very different research methods, which are applied in very different research questions. A scholar who has devoted themselves to only reading Goethe’s Faust would be unlikely to claim that through this they understand all literature (or the human condition). In the same way, a qualitative researcher would be unlikely to claim they knew how to get everyone to stop using cars and ride bikes because they had interviewed three professional race cyclists.

Doubtless, it is a fantastic opportunity to be able to search through vast archives in the humanities to find particular words or topics, and this can help discovery of relevant sources that would otherwise have been overlooked. However, there is still a strong need in digital humanities research for ‘close reading’. Wilkens (2012) also notes that “We may very well still need to read some of the texts closely, but text-mining methods allow us to direct our scarce attention to those materials in which we already have reason to believe we will find relevant information”.

For researchers in fields where qualitative (primary) research is quite common, it is often suprising to discover that there is little use of traditional qualitative analysis software, like Nvivo, Atlas.TI, MAXQDA or Quirkos in the Digital Humanities. Instead, many practitioners have created their own web-based tools for ‘coding’ or tagging qualitative data sets from scratch, or new ones like Annotation Studio or Catma have evolved for specific fields and needs. It’s one of those weird silos of thinking and terminology that occur when fields and disciplines don’t overlap much – often people are doing the same thing but calling it something else. For example, few would call ‘close reading’ qualitative analysis, although it often involves some of the same approaches and conceptualisations.

With the new REFI exchange format for qualitative software, there is the potential to reach out to colleagues in the Digital Humanities and discuss how qualitative software like Quirkos can engage better with other tools and approach, and vice versa. A common file format allows for much more exchange between people in the same fields, but also new ones. If a tool such as Catma implemented the REFI standard, people would be able to use different ways of reading and exploring the data offered by different software, perhaps discovering new ways of interpreting and performing ‘close reading’.

Previously we’ve seen very few people from the humanities and Digital Humanities (like those using historical archives) use Quirkos for qualitative analysis. Initially this was because of the lack of rich text support (which is now integrated into Quirkos 2), but also because many of these researchers simply aren’t looking for or aware of ‘qualitative analysis software’. But for those that have seen it, there has been strong desire to use a tool like Quirkos to perform close reading of resources in the humanities. Those that want to try this out can download the free trial of Quirkos, and see if it helps in their research endeavours. Yet, this is also early days of two evolving paradigms, and it will be interesting to see how new developments (like the REFI format) impact their respective fields in the next few years.