Team transcribing: an approach to analysing and interpreting online acquaintance interviews as collaborative achievements

Despite applied linguists’ understanding of interview data as collaboratively co-constructed, less attention has focused on how the interviewer’s involvement in the communicative event of an interview might go on to shape the ways in which the data is transcribed, analysed and interpreted, with implications for the generation of new knowledge. This article puts forward a team transcribing approach which addresses potential biases and partialities, and highlights how new knowledge is collaboratively achieved through recognising and valuing the diversity of voices within a team. The approach is illustrated through discussion of a research project, Mobile Conversations in Context (MoCo), which combined online video-recorded acquaintance interviews with analysis of diary and mobile messaging data. The interview data was collaboratively transcribed and analysed by two researchers on the team who brought different perspectives to the data: R1 who conducted the interviews and produced initial transcripts; and R2 who multimodally annotated and analysed the transcripts. Our collaboration stretched from initial conversations to the process of writing this paper and revealed the different ways in which interviewees resisted being positioned by the interviewer as mobile messaging users and informants, which in turn highlighted assumptions and attitudes which shaped their mobile messaging practices, thus contributing to addressing the project’s research questions. We end by calling for the need to approach research data from multiple angles, even as a lone researcher, in the generation of new understandings.