I have written about thematic analysis before (here), but when considering how to determine our thematic analysis choices, a useful tool is the flowchart accompanying this post. This allows us to consider:
- Data type. What the type of data we have? For example, is this text, versus non-text?
- Recording. How we have recorded and transcribed our data? Have we used verbatim or summary transcriptions? Have we used simple phonetics or emphasis and tone as well?
- Textual richness. How rich is the data? Is it long and complex? Is it full of metaphors? Is there a lot of in vivo coding needed? Is there a lot of missing data? Are there complex word lists? Is there a lot of repetition? There are some useful lists of considerations.
This little flowchart can give us some insight into just what decisions and the level of complexity we will encounter in coding and categorising our data, to understand the themes that are present in our data to make meaning - information - from that data.
And - in general - the more themes, the better.
Sam
References:
Ryan, G. W., & Bernard, H. R. (2003). Techniques to identify themes. Field Methods, 15(1), 85-109. http://doi.org/10.1177/1525822X02239569
Ai ?. CT
ReplyDeleteYes: I think we may go that way in the end, Chris: but I don't think AI has the grunt or depth yet :-)
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