Qualitative data analysis: Pointers to resources

Work in progress.

Qualitative research is common in information systems and other research fields that look into the interplay between technology and the social context, such as organizations or society. Qualitative data analysis is a step that happens during and after a qualitative field study. Various (often textual) data from interviews, observations, documents etc. are collected and need to be analyzed. The seemingly chaotic collection of data needs to be structured and used to produce new knowledge and new theories. Here I am collecting some resources that teach and give hints on how to do this type of analysis.

Here are some resources for you to read in order to get started:

  • For an introduction to qualitative analysis in information systems you should read Chapter 18 in the excellent “Researching Information Systems and Computing“. This chapter walks you through all the steps, starting from preparation of data, initial reading, coding, theme selection etc.
  • The short 3-pages article by Pope et al. gives a very brief overview, which I find very useful. It uses examples from healthcare domain but the methods are the same as in information systems.
  • For a more detailed description of the process of qualitative data analysis, specially about different ways to discover topics, categories and themes, see “Techniques to Identify Themes“. It is an easy-to-read article with a lot of examples. It discusses a variety of methods, and shows which ones are easier to use than others.
  • Most beginners to qualitative data use a method called thematic analysis. An excellent article that gives an introduction to this method is “Using thematic analysis in psychology“. The paper shows all the steps going from raw data to themes and to analysis and theory-building. Highly recommended. Don’t bother about the “psychology” in the title. The examples are from this field but the methods are generic.
  • Another paper on thematic analysis, but focusing on the software engineering field, is the paper by our own Daniela and Tore called “Recommended Steps for Thematic Synthesis in Software Engineering“. The paper shows how to use mind maps for analysis, and has a discussion of how to do a good synthesis.
  • If you are deploying a team of multiple coders, then developing and maintaining a codebook can be a good idea especially if you are doing a deductive analysis, meaning you already have a set of codes you want to look for in your data. In that case you can use this article for some tips: “Developing and Using a Codebook for the Analysis of Interview Data: An Example from a Professional Development Research Project“.

 

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