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Blog – Conversation analysis, tips & lessons learned

To say time has flown by in the month since my last blog is an understatement! I have spent most of my study time researching what to do when starting a conversation analytic analysis and watching my video data and noting interesting things happening. I also went on holiday (woo!) and attended an in-person event with other PGRs who are using discursive methods such as conversation analysis (CA), discursive psychology (DP) and ethnomethodology (EM) which was just so amazing after the last year of PhD all being online. But let’s get back to the topic in hand!

When I think about the initial steps of a conversation analytic project, I suppose my analysis actually began quite a while back in the first year of my PhD. I have been lucky enough that my data was collected previously by one of my supervisors and I have not had to collect this myself. Because of having had access to the data from the time I started the PhD in October 2021, I had previously watched quite a lot of the videos and used some clips from the videos for presentations at events/conferences. But I had not previously started examining the data more fully and systematically.

Felicity used the Jefferson Transcription System for her recorded videos.

The starting point

In CA, there is an interest in beginning an analysis with what is termed ‘unmotivated looking’, which was pioneered by Harvey Sacks, one of the founders of the CA approach. This means that you should begin analysis without preformed ideas about what you are looking for in the data – what the data is or what it represents. You should be open to any phenomena rather than searching for something already identified in the literature or which personally interests you. This is something that is not always practical for some projects using CA, especially those which will have an applied practical outcome [1].

In my case, I began with an interest in identity maintenance in interaction (so not completely unmotivated, but this is what my PhD project centres on). But I was not sure what I would be looking at specifically in the data – other than things related to displaying identity and helping to support the identity of people living with dementia (which is a very large range of things indeed!). I began by looking at the ‘own home’ setting in my dataset – recordings of interactions between heterosexual couples in their home environment, where one of them is living with a dementia diagnosis. I became interested in instances where memory is invoked – where past experiences are talked about or elicited by others. Initially, I have found what seems to be different kinds of ways of accessing or talking about memories. There are instances where memories are brought up by the person living with dementia or their partner in a way which seems to be reminiscing about memories they both share – or which one party has which relates to something they are both discussing. On the other hand, there are instances where memory ‘testing’ or ‘probing’ is used (so far exclusively by the partner without dementia) to try and get the person living with dementia to access a memory or piece of information such as a person’s name. So far, it seems the former is more supportive of the person living with dementia’s identity, and the latter seems unsupportive. This is however still very early days, and I imagine my eventual analysis will be different to my current thinking.

I will now go over some tips and lessons I have learned from my first month of analysis.

Top tips for the analysis process

Thank you for taking the time to read this blog, I hope parts have been useful to you for your own analysis or just for understanding how a conversation analytic project can be started. However, this is just one way to begin and as ten Have (2007) says, “there are many ways in which one can approach data in a CA project” (p.124).


Felicity Slocombe

Author

Felicity Slocombe [5]is a first year PhD Student from Loughborough University. Felicity’s research focuses on identity and dementia and how identity can be managed interactionally – how we can help support identity of people living with dementia through our conversations. Driven by a family connection to dementia, and writing each month on a range of topics from her work, and that of her wider group ACTInG (Applied Cognition Technology and Interaction Group), and sharing news from her training and events.

Follow @fliss_slocombe [6]