ConnectedText; any case studies?

Posted by Dr Andus
Mar 23, 2012 at 03:10 AM

Most recently I’ve started using CT as a qualitative data analysis solution, to code textual data, for which I used NVivo in the past. This is what I do:

1. I take a 20,000 word document (a transcript of an interview) and paste it into CT as a new ‘topic’ (document).
2. I dock the table of contents window on the left, and have the edit view of the document on the right of it.
3. I start reading through the document and “code” it by adding in headings (up to 5 levels).
4. As headings are added, they start showing up in the TOC pane in the left, so I can see the hierarchy of the themes (codes).
5. When a large enough thematic group emerges (under a top-level heading), I use the “cut to new topic” command to remove that chunk of text from the current topic, so it becomes a topic of its own. This way the text I’m working on is gradually reducing in size, and eventually becomes the central (home) page from which the coded topics become linked.
6. I open the Navigator pane to see the relationship between the ‘home page’ and the associated coded pages (between 5-10 documents).
7. Then I open the Topics and Categories panes and dock them to the right-hand side of the CT window. Then I proceed adding the newly created topics (documents or pages) to the relevant categories.
8. I then review each newly created coded topic and write a conclusion section, which contains the conclusions drawn from the given material, basically the findings of the research.
9. Once I’ve done that for each new topic, I return to the ‘home page’ of this group of topics (which was the topic I started out with but which now only contains the links to these coded topics) and I use the “including parts of topics” command to incorporate all the conclusion sections from the coded topics. Essentially I’m extracting (or abstracting) the findings of the various sections.
10. Once my topic home page contains the extracted findings, I then consolidate these findings into a final set of findings (another level of abstraction).
11. As a final step, I use the “including parts of topics” command to extract this final set of findings and include them in my “Findings” topic, which should be the top level findings page for the entire research project.

So basically what I have done here is I have carried out a qualitative analysis of textual research data, by “coding the data” (thematising it), and then carry out several operations of abstraction, by drawing out and consolidating the research findings. I like to think about it as a “bubbling up” process, as I’m going from the particular text (the interview transcript) and I gradually move to a more abstract (higher) level, by dragging out the findings, reaching eventually the top level of abstraction, which will constitute the theoretical contribution of my study.