While the social sciences have long drawn a distinction between “quantitative” and “qualitative” research, digital humanists oscillate between methods of ‘distant reading’ and ‘close reading’. Text analysis (as explored by the interdisciplinary Text Analysis Working Group) is a form of ‘distant reading’ that focuses on using computational methods (such as topic modeling or clustering) to analyze to large collections of texts in a semi-automated manner.
However, these computational approaches are only one of a set of methods at the disposal of digital humanists. Many research questions in both the social sciences and humanities require close and contextual reading of large amounts of data, such as interviews or diary entries. In the social sciences, this is approach referred to as “qualitative data analysis”, and it too can benefit from the application of digital tools, such as gathering sources together in a database or using qualitative data analysis software to ‘code’ collections of text. In the qualitative data analysis context, ‘coding’ refers to annotating texts in a systematic way and distinguishing themes and patterns with either analog tools (sticky notes, highlighters) or digital tools (Atlas.TI, NVivo).
The Qualitative Methods Group at the D-Lab explores a variety of these digital tools in their multi-faceted discussions of social science methods. In past meetings, scholars have shared their research and highlighted a methodological aspect of their work, such as analyzing archival documents. Though the theory that guides these inquiries varies among disciplines, digital humanists can learn much from these methods. Everyone is welcome.
The D-Lab also regularly hosts training that complements these qualitative methods. Past workshops have included:
- Intro to Qualitative Data Analysis: Coding and Technology
- From Coding Qualitative Data to Analyzing It
- Qualitative Data Analysis with Atlas.TI