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Unpicking conversation nuances

A fresh slant on how to decipher true meaning when we talk to one another revealed the tantalising opportunities Micro ethnography offers, and the potential drawbacks.

It’s always great to hear from people from outside the industry. They give us a fresh perspective and inspire us to think of alternative ways to tackle our research. So, with an interest in how to pick up the true meaning in conversations, we attended AQR’s "Introduction to Micro ethnography" Spark event.

Micro ethnography, also known as conversational analysis, is the detailed study of real-life interactions and conversations. It was given by Sae Oshima PHD, senior lecturer of Corporate and Marketing Communications at Bournemouth University.

After video recording interactions, analysis involves the incredibly detailed transcription of relatively short pieces of conversation using a pretty complicated system of signs, symbols and notes. As well as the actual words spoken, the analysis looks at where conversation overlaps and makes notes for pitch, tone, pauses, silence, facial expressions, even when someone breathes.

Sae gave us many examples of where such detail has helped extract meaning. She showed how the word ‘Oh’ can mean many things such as a change of subject or surprise. Sae also timed how long a man took to chew his food and highlighted that, while he appeared friendly and open to the question he’d just been asked, he was actually stalling for time.

She’s used this approach for many things including the interaction between hairdressers and their customers, and between a Big Issue seller and passers-by. This all sounded great, but it can take a day to transcribe just five minutes of conversation. Impractical for most of us, unless focusing in on specific, short interactions.

It did, however, highlight the importance of listening back to our recordings, and watching video footage more closely. Also, taking into account the context within which human interactions take place, in order to draw the most accurate conclusions. And who knows? With the speed of advances in technology, the current labour-intensive approach to conversation analysis may become much easier in the future.

 

Helen Law
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