Dedoose Blog


Best Practices in Excerpting and Coding and Capitalizing on Dedoose Features


Pros and Cons

(Note that this post contains content largely extracted from an article by the authors currently under review for publication.  Please contact Dedoose Support if you wish to cite any content contained herein)

Summary—Context is King…Be a Chunker!

Context is King

Qualitative data allow us to learn about the rich, nature, complex, and contextualized ways in which our research participants experience their lives…the ‘how’ and ‘why’ of life, beyond the ‘what?’  So, simply, context is king.  The first step of the excerpting process involves deciding where an excerpt begins and ends.  There are two general styles of excerpting that we’ll call ‘splitting’ and ‘chunking.’  Splitters tend to create smaller excerpts that are tagged with small numbers of codes.  Chunkers tend to create larger excerpts and apply multiple codes. The professional academic researchers behind Dedoose strongly encourage more chunking when creating excerpts and, when one does so, you’ll more likely assure you’ve good context and you’ll have set up the project to take full advantage of the Dedoose analytic features.

For Splitters, imagine doing a search and retrieval for commonly coded excerpts after using a splitting style.  Results will get you many short excerpts completely out of context.  Remember when you are creating excerpts you are viewing or listening to the entire media file, so the context is there and the broader meanings are clear when you are engaged in process. Unfortunately for splitters, when they later review excerpts out of context they often find themselves needing to return to the context to be reminded of the broader meanings…bummer, this can be a real time-sink.  This is the primary reason we recommend a chunking style.

For Chunkers, two big benefits:

  • 1—excerpts contain sufficient context to understand why you applied particular codes
  • 2—many Dedoose analytic features, like the code co-occurrence matrix, are far more valuable when you are carrying out your analysis.

If you keep in mind that we collect and analyze qualitative data because of their richness and that smaller numbers of words carry far less meaning—particularly out of context—there is every reason in the world to join the Chunker community and embrace the valuable rich, deep, context in your data….for more, read on here at our article!


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Dey, I. (1993). Qualitative data analysis: A user-friendly guide for social scientists. London, UK: Routledge Kegan Paul.

Jehn, K. A. & Doucet, L. (1996). Developing categories from interview data: Text analysis and multidimensional scaling. Part 1. Cultural Anthropology Methods Journal 8(2), 15–16.

Jehn, K. A. & Doucet, L. (1997). Developing categories for interview data: Consequences of different coding and analysis strategies in understanding text. Part 2. Cultural Anthropology Methods Journal 9(1), 1–7.

Ryan, G. W. & Bernard, H. R. (2003). Techniques to identify themes. Field Methods, 15(1), 85-109.