Big Qual: A Guide to Breadth-and-Depth Analysis   

Susie Weller, Emma Davidson, Rosalind Edwards, Lynn Jamieson

Research output: Book/ReportBook

Abstract / Description of output

When social scientists think about big data, they often think in terms of quantitative data sets that can be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions. However, there exists a growing wealth of qualitative data sets, available through archives and other forms of data sharing. These data present new and exciting opportunities internationally for qualitative research. Pooling multiple qualitative data sets enhances the possibility of theoretical generalisability by increasing the diversity of sample populations and contexts. This can, in turn, strengthen claims from qualitative research about how social processes work.  

In Big Qual: A guide to Breadth-and-Depth analysis we present a new approach for working with large volumes of qualitative data. As the name suggests, the method brings together breadth and depth through an integration of computational and qualitative data analysis. This book covers everything researchers - both qualitative and quantitative - need to know about analysing large volumes of qualitative data, from sourcing and creating your data set, applying the method, and understanding the ethical and epistemological challenges.

After gaining a comprehensive overview of the rationale for, and value of, large-scale qualitative data analysis, the book takes readers through four stages of dealing with big qual that are akin to the process of discovery in archaeology:   

An enquiry-led overview of archived qualitative research: using meta data like an archaeologist uses photographs in an aerial survey.   

Computer-aided scrutiny across the breadth of selected data collections: to assess what merits closer investigation, like an archaeologist’s ground-based geophysical survey of an area.   

Analysis of multiple small samples of likely data: equivalent to digging shallow ‘test pits’ to find an area meriting deeper excavation.   

In-depth analysis: of the type familiar to qualitative researchers, like archaeological deep excavation.   

This aim is not to create a prescriptive method or methodology for students, researchers, and teachers of research methods to deploy. Rather, the book provides a guide to thinking through the possibilities of big qual and its relationship to qualitative research more generally. The breadth-and-depth approach can also function in a modular fashion, with each chapter of the book prompting readers to think differently about the relationship between theory and evidence, research questions and data. Combined with tried and tested linked multimedia resources, expert international case studies and a bespoke teaching data set, the book is a unique addition to textbooks seeking to analyze qualitative data using computational methods.

This book is intended for international audiences with a stake or interest in the use of qualitative data, regardless of discipline and methodological background. Since our approach meshes quantitative and qualitative approaches, we hope that it can be used to encourage collaborative and cross-disciplinary thinking. Given the continued rise of big data and the evolving possibilities it offers the humanities and social sciences, we hope that it will build capacity in the UK and internationally in ‘big qual’ research, and provoke new and exciting ways of thinking about, and working with, large volumes of qualitative data and its analysis.    
Original languageEnglish
PublisherPalgrave Macmillan
Number of pages205
ISBN (Electronic)9783031363245
ISBN (Print)9783031363238
Publication statusPublished - 5 Dec 2023

Keywords / Materials (for Non-textual outputs)

  • archival research
  • Big Data analytics
  • qualitative longitudinal research
  • big qual


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